Chapter 8: Hypothesis Testing for One Population Mean, Variance, and Proportion

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Chapter 8: Hypothesis Testing for One Population Mean, Variance, and Proportion"

Transcription

1 Chapter 8: Hypothesis Testing for One Population Mean, Variance, and Proportion Learning Objectives Upon successful completion of Chapter 8, you will be able to: Understand terms. State the null and alternative hypotheses. Use the 5 steps to test hypotheses for both the critical value and p-value. Test specific hypothesized values for means, variances, and proportions. Describe the relationship between type I and type II errors. Given a value for the test statistic, find the p-value. I. General Concept Hypothesis testing or a decision-making process between 2 choices about a population parameter called: the null hypothesis and the alternate or research hypothesis. A. Kinds of Hypotheses The null hypothesis (H 0 ) states that the parameter equals a specific value (or in Chapter 9 two parameters are equal). The alternative hypothesis (H 1 ) states the parameter is different from a specific value (or in Chapter 9 the alternate hypothesis is a difference between two parameters). B. Hypotheses Testing Methods The traditional or crticial value method which is a location method. The P-value (prob-value) method which is a comparison or areas method. C. Common Phrases used in Testing > Is greater than, Is increased Is greater than or equal to, Is at least = Is equal to, Has not changed < Is less than, Is decreased or reduced from Is less than or equal to, Is at most Is not equal to, Has changed from Dr. Janet Winter, Stat 200 Page 1

2 D. Very Important Notation H 0 : Always has the = sign; Northing is different from the usual. H 1 : Called the research or the alternative hypothesis; includes the direction the researcher hopes to justify, it will always be <, >, or. E. Stating the Null and Alternate Hypotheses I. II. Question 1 Example: Calcium is the most abundant mineral in the body and also one of the most important. It works with phosphorous to build and maintain bones and teeth. The recommended daily allowance (RDA) of calcium is 800 milligrams. Assume we want to test whether people with income below the poverty level receive an average less than the RDA of 800mg.. H 0 : μ = 800 H 1 : μ < 800 Example: The R.R. Bowker Company of New York collects information on the retail prices of books. In 2000, the standard deviation of the price of history books was $3.25. Suppose this company wishes to determine whether this year s standard deviation is higher than the standard deviation price in H 0 : σ = 3.25 H 1 : σ > 3.25 A researcher is concerned that the mean weight of honey bees is more than 11g. a) H 0 : μ = 11 H 1 : μ 11 b) H 0 : μ = 11 H 1 : μ > 11 c) H 0 : μ = 11 H 1 : μ < 800 d) I do not know. Question 2 The variance in the amount of salt in granola is different from 3.42mg. a) H 0 : σ = 3.42 H 1 : σ 3.42 b) H 0 : σ 3.42 H 1 : σ = 3.42 c) H 0 : σ 2 = 3.42 H 1 : σ d) H 0 : σ H 1 : σ 2 = 3.42 Dr. Janet Winter, Stat 200 Page 2

3 Question 3 3% of homes remain unsold after 6 months in Newark, NJ. It is assumed that homes in the vicinity of the college have a faster sales rate. What null and alternate hypotheses should be used to test this theory? a) H 0 : p =.03 H 1 : p.03 b) H 0 : p =.03 H 1 : p >.03 c) H 0 : p =.03 H 1 : p <.03 d) H 0 : p <.03 H 1 : p =.03 Question 4 A company that produces snack food uses a machine to package the product in 454 gram quantities. They wish to test the machine. Question 5 The NCAA believes 57.6% of football injuries occur during practice. A head trainer thinks this is too high. Question 6 A manufacturer of machine parts must have a standard deviation in measurement not more than 0.32 mm. Use a sample of 25 parts to test if the standard deviation is outside of the requirement. F. Statistical Tests I. Process A statistical test compares the sample statistic with the null hypothesized value to decide whether or not the null hypothesis should be rejected. The numerical value obtained from a statistical test is called the test value or test statistic. II. Errors a) Possible Outcomes of a Hypothesis Test H 0 True H 0 False Reject H 0 Error Type I Correct Decision Do not reject H 0 Correct Decision Error Type II Dr. Janet Winter, Stat 200 Page 3

4 b) Types of Errors A Type I error occurs if one rejects the null hypothesis when it is true. o The maximum probability of committing a type I error: P (type I error) α o The probability of rejecting a true null hypothesis. o Also called the level of significance or α. o Set by the researcher. If not stated, use A Type II error occurs if one does not reject the null hypothesis when it is false. o P (type II error) = β o The probability of not rejecting a false null hypothesis. o Decreases when α increases. c) Level of significance Maximum probability of type I error P(type I error) The probability of rejecting a true null hypothesis Set by researcher If not note, use 0.05 d) α (alpha) and β (beta) Probabilities In most hypothesis testing situations, β cannot easily be computed. However, decreasing either alpha or beta increases the other. II. Hypothesis Testing of a Specified Value for the Population Mean: The Traditional or Critical Value Method (This is a comparison of locations method ) A. Terms I. The rejection region is the range of test values that indicates a significant difference exists between the sample statistic and the hypothesized parameter. The critical value marks the start of the rejection region or critical region. If the test statistic is located in the critical region, the null hypothesis should be rejected. II. The non-critical or non-rejection region is the range of values of the test value that indicates that the difference was probably due to chance. If the test value is located in the non-critical region, the null hypothesis should not be rejected. Dr. Janet Winter, Stat 200 Page 4

5 III. Critical Value (c.v.) Separates the critical region or rejection region from the non-critical region or nonrejection region. It is determined from the appropriate table. It is based on the significance level and the alternate hypothesis. B. Finding Critical Values I. Concepts for One-Tailed Tests The critical region or rejection region is only on ONE side of the center value for the distribution or in one tail. It is Right-tailed or left-tailed, depending on the direction of the inequality of the alternate hypothesis. The area of one tail is equal to the level of significance. a) Left-Tailed z-tests or t-tests H 0 : μ = k H 1 : μ < k This is a left tailed test since the alternate hypothesis has the < symbol. Since the alternate hypothesis is less than k, the rejection region is to the left of a negative z critical value. Critical region Noncritical region -z 0 Note: Whenever the alternative hypothesis is less than, the rejection region is to the left of the center of the normal distribution. H 1 contains < which points to the left like a left pointing arrow. Dr. Janet Winter, Stat 200 Page 5

6 To find a left tailed z critical value (c.v.), locate the level of significance or alpha in the center portion of the Normal Probability Table. Move your hand along the row to the left to find the units and tenths digits for z. Next, move your hand to the top of the column to find the hundredth digits for z. Notice this value is negative. To find a left tailed t critical value, use the t table. Find the one tailed α row at the top of the table. Use the column with the specified value of α for the problem. Move your hand down this column to the row for the df in the problem. Affix a negative sign to this value because the cv is less than 0. Example: For a left-tailed test, find critical z for α = Since the test is left-tailed, alternate hypothesis contains a less than and the rejection region is on the left. Locate inside of the normal probability table. Move along the row to the left to Again, starting at , move to the top of the column to.03. The critical value is ( ). The rule would be to reject the null hypothesis if the test value is less than or equal to b) Right-Tailed z-tests or t-tests H 0 : μ = k H 1 : μ > k This is a right tailed test since the alternate hypothesis has the > symbol. Dr. Janet Winter, Stat 200 Page 6

7 Since the alternate hypothesis is more than k, the rejection region is to the right of a positive c.v. Noncritical region 1 α Critical region α 0 +z Note: Whenever the alternative hypothesis is greater than or has the > symbol, the rejection region is to the right of the critical value (c.v.) and to the right of the center of the normal distribution. H 1 contains > which points to the right like a right pointing arrow. To find a one tailed, right tailed z critical value (c.v.), locate (1 α) or 1 minus the level of significance in the center portion of the Normal Probability Table. Move your hand along the row to the left to find the units and tenths digits for z and move your hand to the top of the column to find the hundredth digits for z. Notice this c.v. is positive. To find a one tailed, right tailed t critical value, use the t-table. Use the one tailed row at the top of the page. Find the column for t and move your hand down this column until you reach the row for n 1 degrees of freedom. The entry at the intersection of column t and row df is the c.v. DO NOT MAKE IT NEGATIVE. Dr. Janet Winter, Stat 200 Page 7

8 Example: Use the z table to find the critical value for a right-tailed test for α = Since the test is right-tailed, the alternate hypothesis contains the more than symbol and, the rejection region is on the right. Locate 1.05 =.9500 inside the normal probability table. Since it is exactly half way between 1.64 and 1.65, the critical value would be or rounded to two decimal places it would be Thus reject for any test value is greater than or equal to II. Concepts for Two-Tailed Tests The alternative hypothesis always has H0 : μ = k H1 : μ k Since the alternative hypothesis has, the test statistic can be either on the right or on the left of the center. The null hypothesis is rejected when the test value is in either of 2 critical or rejection regions (one on the left and one on the right). It is necessary to find critical values (c.v.) for both sides. The critical values are opposites (only f the z and t tables or cv = ± c value). The sum of the areas in the two tails is equal to the level of significance or alpha. That is, each tail has probability or area Note: every two-tailed test has the sign, 2 critical values, and 2 rejection regions. Each tail has probability or area. Dr. Janet Winter, Stat 200 Page 8

9 Example: Using the z-table, find the critical values for a two tailed test when α = For a two-tailed test, the alternative hypothesis will be not equal to and the rejection region is on the right and left with each area 0.01/2 = To find the critical value on the left, locate inside the normal probability table. The left critical value is or rounded to two decimal places is Using symmetry, the critical value one the right is The rule would be to reject the null hypothesis for any text value greater than or equal to 2.58 AND also to reject the null hypothesis for any test value smaller than CV = ± 2.58 Question 7 Using the z-table, find the critical value for a right tailed test with =.025. Question 8 Use the z-table, find the critical value for a left tailed test with =.10. Question 9 Use the z-table, find the critical values for a two tailed test with =.05. III. Combining Concepts Example: In 2002, the mean age of an inmate on death row was 40.7 years, according to data obtained from the U.S. Department of Justice. A sociologist wants to test the statement using the 0.10 level of significance. State the null and alternate hypotheses. State the critical value or values, and the rejection rule. Dr. Janet Winter, Stat 200 Page 9

10 Since the sociologist is not implying a direction, there is none and the hypotheses are: H 0 : μ = 40.7 H 1 : μ 40.7 Since the alternative hypothesis is, the test is two tailed with 0.10/2 = 0.05 probability in each tail. Use the Normal Probability table backwards to find the z value with 0.05 in the left tail. The left critically value is z = By symmetry the right critical value is the opposite or The rule is to reject the null hypothesis if the test statistic is either greater than 1.65 or less than CV = ± Question 10 An energy official thinks that the oil output per well has declined from the 1998 level of 11.1 barrels per day. Use the.001 level of significance. State the null and alternative hypotheses. State the critical value or values, and the rejection rule. C. Hypothesis Testing Process using the Critical Value or Traditional Method (location method) 1. State the hypothesis. 2. Compute the test value or test statistic. 3. Find the critical value or beginning of the rejection region or regions from the appropriate table. 4. Decide to reject or fail to reject the null hypothesis based on the location of the test value. 5. Record a conclusion in terms of the situation in the problem. Note: This is very, very important MEMORIZE THIS!!! Dr. Janet Winter, Stat 200 Page 10

11 I. Test Statistics (to test the value of the Population Mean) 1. z Test for the Population Mean Use z when σ, the population standard deviation, is know and either n 30 or the population is normally distributed. Z = X μ σ/ n z = (X μ) σ (n) Where: X = sample mean μ= hypothesized population mean σ= population standard deviation n= sample size 2. t Test for the Population Mean Use the t Test when σ is not known and either n 30 or the population is normally distributed. t = X μ s/ n df: n 1 t = (X μ) (s (n)) Your calculator work will be the same for every problem testing the specified value for the mean. II. Problems: Example: According to the USA Today, the average age of commercial jets in the U.S. is 14 years. An executive of a large airline selects a sample of 36 planes. The average age of the jets in this sample is 11.8 years. The population standard deviation is 2.7 years. At the 0.01 level of significance, is the data sufficient to conclude that the average age of the planes in this company is less than the national average? 1. State the null and alternate hypotheses H 0 : μ = 14 H 1 : μ < Find the test statistic z = = ( ) = 4.89 *Use z since the population standard deviation is stated and n = NOTICE THAT THE TEST VALUE IS COMPUTED USING SAMPLE DATA. Dr. Janet Winter, Stat 200 Page 11

12 3. Find the critical value. This is a one tailed test with a level of significance equal to 0.01 or the probability in the left tail is Since this is a z test statistic, use the normal probability table to find: c.v. = NOTICE THAT THE REJECTION REGION IS DEFINED BY A TABLED CRITICAL VALUE. 4. Since is less than or the test value is in the rejection region, reject the null hypothesis. 5. The data supports an average age of the planes in the executive s airline to be less than the national average of 14 years. Example: Two researchers measured the ph of randomly selected lakes in the Southern Alps: It is assumed that ph is a normally distributed random variable. Based on this sample data, can we conclude that on average, lakes in the Southern Alps are non-acidic or have a ph higher than 6.0? Use your calculator to find the sample average and sample standard deviation. Since the researcher used a random samples of lakes, use X and s from the calculator. X = 6.60 s =.672 n = Since there is a concern about a ph higher than 6.0 use: H 0 : μ = 6.0 H 1 : μ > Use the t test statistic since the population standard deviation is not given but the variable is normally distributed with n = 15 < 30. t = ( ) = ( ). 672 (15) = NOTICE THAT THE TEST VALUE IS COMPUTED USING SAMPLE DATA. 3. Use the t-table with df: 15 1 = 14 to find c.v. = The rejection region is to the right of NOTICE THAT THE REJECTION REGION IS DEFINED BY A TABLED CRITICAL VALUE. 4. Since the test value 3.46 is larger than the c.v. = 1.761, it is in the rejection region. Reject the null hypothesis. 5. Since the null hypothesis is rejected, it is removed and the hypothesis that remains is the alternate hypothesis. The data supports an average ph greater than 6.0 for lakes in the Southern Alps. Dr. Janet Winter, Stat 200 Page 12

13 Question 11 Concerned that adult females under 51 years are not getting adequate iron intake, a statistician selected a random sample of women under 51 years old and found the listed iron intake in milligrams for a 24-hour period. Use a 5% level of significance and test his concern. Assume RDA for iron is 18mg and assume it is a normally distributed random variable Question 12 To see if young men ages 8 through 17 years spend an average of $24.44 per shopping trip to a local mall, the manager surveyed 33 young men and found the average amount spent per visit was $ The standard deviation of the sample was $3.70. Assume the amount spent on a shopping trip is normally distributed. At α = 0.02, can it be concluded that the average amount spent at a local mall is not equal to the national average of $24.44? III. Hypothesis Testing: P value, prob value or comparison of areas method A. Computation of P For a one-tailed test: the P-value is the area from the test statistic to more extreme values in the direction of the alternative hypothesis. For a two-tailed test: the P-value is twice the area from the test statistic to the end of the tail. If the test value is less than zero, the area is to the left. If the test value is more than zero, the area is to the right. B. Process for the P-value Method (comparison of areas method) 1. State the hypotheses. 2. Compute the test value. 3. Find the P-value or area in the tail or tails past the test statistic. Notice the test statistic is used to find the P-value. 4. Decision Rule: reject the null hypothesis whenever p is less than or equal to the level of significance. If P-value, reject the null hypothesis If P-value >, fail to reject the null hypothesis NOTE: This is very, very important MEMORIZE THIS!!! 5. Record a conclusion related to the problem. Dr. Janet Winter, Stat 200 Page 13

14 C. TI-83 Directions for Normal and T Probability (Use the 2 nd function VARS to access DISTR) 1. Use 2 nd function VARS to enter the DISTR Menu 2. Select normalcdf (for z) or tcdf (for t) 3. For z, enter the values for the left end point and the right endpoint (separated by commas) for the area or probability to be determined normalcdf (left endpoint, right endpoint) For H 1 : μ < μ 0, p = normalcdf (-100, test value) For H 1 : μ > μ 0, p = normal cdf (test value, 100) For H 1 : μ μ 0, p = 2normal cdf ( test value, 100) 4. For t, enter the values for the left and right endpoints and degrees of freedom for t. tcdf (left endpoint, right endpoint, df) For H 1 : μ < μ 0, p = tcdf (-100, test value, df) For H 1 : μ > μ 0, p = tcdf (test value, 100, df) For H 1 : μ μ 0, p = tcdf ( test value, 100, df) Refer to the Chapter 6 Guide for more information on the normalcdf. Example: The average stopping distance of a school bus traveling 50 miles per hour is usually 26 feet (Snapshot, USA TODAY, March 12, 1992). A group of automotive engineers determined the average stopping distance for 30 randomly selected busses, traveling 50 miles per hour to be feet. The standard deviation of the population was 3 feet. Use this data to test if the average stopping distance is actually less than 264 feet. Use the P-value method with α = H 0 : μ = 264 H 1 : μ < z = X μ σ n = = ( ) 3 30 = *Use z since the population standard deviation is stated and n = * 3. Since this is a one tailed test, find the area less than or P(z < -3.10) = The P-value is.0010 = normalcdf (-100, -3.10) 4. Reject the null hypothesis since P =.0010 < α = The data supports an average stopping distance less than 264 feet. Dr. Janet Winter, Stat 200 Page 14

15 Example: Critical Value Method The average salary of graduates entering the actuarial field is reported to be $ To test this figure, a statistics professor surveyed 20 graduates. Their average salary is $53,228 with a standard deviation of $4000. Assume that these salaries are normally distributed and use the critical value method with a 0.05 level of significance to test the reported $ X = $53, 228 s = $4,000 n = H 0 : μ = 50,000 H 1 : μ $50, t = X μ s = 53,228 50, = n c.v. = ± d.f. = The test statistic 3.61 is further out in the tail past the cv = Reject the null hypothesis. 5. The data is sufficient to reject or refute an average salary equal to $50,000. Example: P Value Method The average salary of graduates entering the actuarial field is reported to be $ To test this figure, a statistics professor surveyed 20 graduates. Their average salary is $53,228 with a standard deviation of $4000. Assume that these salaries are normally distributed and use P-value method with a 0.05 level of significance to test the reported $ H 0 : μ = 50,000 H 1 : μ $50, t = X μ s n 0 = 53,228 50, = For a two tailed test, be sure to double the tail area past the test statistic. 4. Find twice the area in the tail from the test value to the end of the left tail or P = 2P(t < -3.61) = 2tcdf(-100, -3,61, 19) =.0019 Dr. Janet Winter, Stat 200 Page 15

16 5. Since P is less than the level of significance 0.05, reject the null hypothesis. 6. The data is sufficient to reject an average salary equal to $50,000. Example: In 2001, the mean household expenditure for energy was $1493, according to data obtained from the U.S. Energy Information Administration. An economist wants to know whether this amount has changed significantly from its 2001 level. Using a random sample of 35 household, she finds the mean expenditure (in 2001 dollars) for energy during the most recent year to be $1618, with standard deviation $321. Complete the test for the economist at the 0.05 level of significance using the P-value method.. X = 1618, s = 321, n = H 0 : μ = 1493 H 1 : μ Use t since the standard deviation for the population is not given and n=35 >30 t = X μ s n = = ( ) = This is a two tailed test since the alternate hypothesis has. The degrees of freedom are n 1 or 35-1 = 34 Calculator: P = 2P(t >2.30) =2tcdf (2.30,100, 34) =.0277 Table: Using the row for degrees of freedom 34, 2.30 is between the values (go to the top of its column) with two tailed probability 0.05 AND (go to the top of its column) with two tailed probability This means P is bounded by 0.05 and 0.02 or 0.02 < P < From the calculator, P =.0277 and P <.05. Reject the null hypothesis. From the table, since the upper bound for P is 0.05, P <.05. Reject the null hypothesis. 5. The data is sufficient to reject an average energy expenditure equal to $1493. Dr. Janet Winter, Stat 200 Page 16

17 Question 13 Last year the average cost of a concert ticket was $ This year, a random sample of 15 recent concerts had an average price of $62.30 with a variance of $ At the 0.05 level of significance, can it be concluded that the cost has increased? Question 14 A study published in the American Journal of Psychiatry measured the effect of alcohol on the developing hippocampus, or the portion of the brain responsible for long term memory. 3 To determine if the volume of the hippocampus is less than the normal 9.02 cm for adolescents who abuse alcohol, the research used a sample of 12 adolescents with alcohol 3 abuse problems. The average weight of their hippocampus was 8.10 cm with a standard 3 deviation of 0.7 cm. Use the 0.01 level of significance. Question 15: The U.S. golf Association requires that golf balls have a diameter that is 1.68 inches. An engineer for the USGA wishes to discover whether Maxfli XS golf balls have a mean diameter different from 1.68 inches. A random sample of Maxfli Xs golf balls was selected. Assume the diameters are normally distributed and test with a 0.10 type one error rate. Conduct the test using the P-value method Using a calculator find: X = , s = , n = 12 and then conduct the test. Question 16: A Gallup Poll stated that women visit their physician an average of 5.8 times a year. The number of physician visits for 2007 is listed below for 20 randomly selected women: Assume that the number of physician visits is normally distributed. At the 0.05 level of significance can we conclude that the Gallup Poll average is correct? Use the p-value method. μ = 5.8 Use a calculator to find: X = 3.85 n = 20 s = 2.52 =0.05 Dr. Janet Winter, Stat 200 Page 17

18 IV.Hypothesis Tests for a Proportion (Always use z) A. Formula Use this method only when np 5 and n(1 p) 5 z = where p p pq n = (p p) (p q n) p = X n p = hypothesized proportion n = sample size Note: the positions of the sample proportion p and the hypothesized proportion p in the formula. B. Problem Characteristics: all involve a hypothesis about a percent, proportion, or fraction change all percents, proportions, or fractions to four place decimals before computing the test statistic If necessary, form p = X where x is the count of the number of success and n is the n maximum number of tries p = X is derived from data n Example: In a survey conducted by the American Animal Hospital Association, 37% of the respondents state that they talk to their pets on the answering machine or telephone. A veterinarian thought this percent was high. He randomly selected 150 pet owners. 54 of them responded that they speak to their pet on the answering machine or telephone. Use this data to run the test at the 0.10 level using the p-value method. P = 0.37 p = 54 = is derived from data H 0 : p = 0.37 H 1 : p < 0.37 (claim) 2. The test statistic is: z = = (.36.37) ( ) = -.26 (.37)(.63) Since this is a one tailed test, find the area less than or P = P(z < -0.26) =.3974 or P = normalcdf(-100, -.26) = Fail to reject the null hypothesis since P =.3974 > α = The data does not support less than 37% of pet owners talking to their pets on the telephone or answering machine. Dr. Janet Winter, Stat 200 Page 18

19 Question 17: It has been reported that 40% of the adult population over 60 use . From a random sample of 180 adults, 65 used . At = 0.01, is there sufficient evidence to conclude that the proportion differs from 40%? Use the P-value method. Question 18: USA TODAY reported that 63% of Americans will take a vacation this summer. In a survey of 143 Americans 85 were planning to vacation this summer. Use this data to test the USA TODAY report at the 0.05 level of significance with the critical value method. V. Hypothesis Tests for One Variance (always use the Chi-Squre Test) A. Formula With d.f. = n 1 where Notice the position of the sample variance and the hypothesized variance in this formula. B. Review of Chi-Square Distributions The chi-square distributions are a family of probability distributions identified by degrees of freedom (n-1) with: 1. Zero or positive values 2. Distribution skewed to the right 3. One mode slightly to the left of the degrees of freedom Important: The mode slightly left of degrees of freedom Chi-Square Distributions depend on degrees of freedom Note: as df increases the curve moves to the right If degrees of freedom are not listed in the table, use the closest smaller value. Dr. Janet Winter, Stat 200 Page 19

20 C. Comments Also used to test a value of a standard deviation (square the sample and hypothesized standard deviation to find the variances) Can be left tailed, right tailed, or two tailed Left tailed test statistics should be to the left of df Right tailed test statistics should be to the right o df Two tailed test statistics can be either on the left or the right of the df Mark the df slightly to the right of the mode. Now you know the approximate location of the center. The value of the c.v. is always positive for x 2 Example: A researcher believes that the standard deviation of the number of cars stolen each year is less than 15. For a sample of 12 years, the standard deviation for the number of stolen aircrafts is Use = 0.05 and the critical value method for the test. Since the researcher believes that the standard deviation of the number of cars stolen each year is less than 15, the test is a left tailed test. The test statistics should be on the left of the df and the critical value will be to the left of the degrees of freedom which is approximately at the mode. The p-value will be the area from the test statistic to the left end of the tail. 1. H 0 : σ = 15 H 1 : σ < x 2 = (n 1)s2 σ 2 = (12 1) = = *Since this is a left tailed test, use the 1- = =.95 x 2 column. With df: n 1 = 12 1 = 11 to find c.v. 3. C.V. = d.f. = 11 Note: This c.v. is always positive Dr. Janet Winter, Stat 200 Page 20

21 4. The test statistic 9.04 is not less than the critical value Do not reject the null hypothesis. 5. The data is not sufficient to reject a standard deviation equal to 15. D. TI-83 Calculator: P-values for the Chi-Square Statistics For left tailed tests, the test statistic is left of df and p is the area from zero to the test statistics or the area on the left or p = (0, test statistic, df) For right tailed tests, the test statistic is right of df and p is the area from the test value to the end of the right tail or p = (test statistic, 1000, df) For two tailed tests, first determine if the test value is to the right or left of the df If the test value is less than df, p = 2 (0, test statistic, df) If the test value is greater than df, p = 2 (test statistic, 1000, df) Example: A random sample of 20 different kinds of doughnuts had the calories listed above. At = 0.01, is there sufficient evidence to conclude that the standard deviation of calorie content is greater than 20 calories? Use the critical value method Use your calculator to find the sample standard deviation. s = H 0 : H 1 : The c.v. is For a right tailed test, the cv is to the right of degrees of freedom. Since the test statistic is further to the right than the cv, reject the null hypothesis. 5. The data is sufficient to support a standard deviation greater than 20. Dr. Janet Winter, Stat 200 Page 21

22 Question 19: The manager of a large company is concerned about the variability of the time that it takes a telephone call to be transferred to the correct office in her company. A sample of 15 calls is selected, and the transfer time is recorded. The standard deviation of the sample is 1.8 minutes. At = 0.01, test if the population standard deviation is more than 1.2 minutes. Use the P-value method. Question 20: The data below is a random sample of home run totals for National League Champions from 1938 to At the 0.05 level of significance, is there sufficient evidence to conclude that the variance is smaller than 70? Use the prob-value method and the cv method VI.Summary A statistical hypothesis is a conjecture about a population mean, proportion, or variance. There are two hypotheses: the null hypothesis states that there is no difference (=) and the alternative hypothesis specifies a difference ( <, >, or ). Researchers compute a test value from the sample data to decide whether the null hypothesis should or should not be rejected. If null hypothesis is rejected, the difference between the population parameter and the sample statistic is said to be significant. The difference is determined to be significant when either: the test value falls in the critical region or the p-value is less than or equal to α, the level of significance of the test. The significance level of a test is the probability of committing a type I error. The significance level is usually specified in the problem. The default value for the level of significance is A type I error occurs when the null hypothesis is rejected when it is true. The type II error can occur when the null hypothesis is not rejected when it is false. Dr. Janet Winter, Stat 200 Page 22

23 Answer: Question 1 A researcher is concerned that the mean weight of honey bees is more than 11g. a) H 0 : μ = 11 H 1 : μ 11 b) H0 : μ = 11 H1 : μ > 11 c) H 0 : μ = 11 H 1 : μ < 800 d) I do not know. Answer: Question 2 The variance in the amount of salt in granola is different from 3.42mg. a) H 0 : σ = 3.42 H 1 : σ 3.42 b) H 0 : σ 3.42 H 1 : σ = 3.42 c) H0 : σ 2 = 3.42 H1 : σ d) H 0 : σ H 1 : σ 2 = 3.42 Answer: Question 3 3% of homes remain unsold after 6 months in Newark, NJ. It is assumed that homes in the vicinity of the college have a faster sales rate. What null and alternate hypotheses should be used to test this theory? a) H 0 : p =.03 H 1 : p.03 b) H 0 : p =.03 H 1 : p >.03 c) H0 : p =.03 H1 : p <.03 d) H 0 : p <.03 H 1 : p =.03 Answer: Question 4 A company that produces snack food uses a machine to package the product in 454 gram quantities. They wish to test the machine. H0 : μ = 454 H1 : μ 454 Answer: Question 5 The NCAA believes 57.6% of football injuries occur during practice. A head trainer thinks this is too high. H0 : p =.576 H1 : p <.576 Answer: Question 6 A manufacturer of machine parts must have a standard deviation in measurement not more than 0.32 mm. Use a sample of 25 parts to test if the standard deviation is outside of the requirement. H0: σ = 0.32 H1: σ > 0.32 Dr. Janet Winter, Stat 200 Page 23

24 Answer: Question 7 Use the z-table, find the critical value for a right tailed test with α =.025. Since this is a right tailed test, the alternate hypothesis has a greater than symbol and the rejection region is on the right. Locate =.0750 inside the normal probability table. Moving to the left and then moving to the top of the table, the z value is The c.v. is 1.96 and the rule would be to reject the null hypothesis if the test value is greater than Answer: Question 8 Use the z-table, find the critical value for a left tailed test with α =.10. Since the test is left-tailed, alternate hypothesis contains a less than and the rejection region is on the left. Locate inside of the normal probability table. Move along the row to the left to Again, starting at 0.100, move to the top of the column to.08. The critical value is ( ). The rule would be to reject the null hypothesis if the test value is less than or equal to Dr. Janet Winter, Stat 200 Page 24

25 Answer: Question 9 Use the z-table, find the critical values for a two tailed test with α =.05. For a two-tailed test, the alternate hypothesis will be not equal to and the rejection region is on the right and left with each area 0.05/2 = To find the critical value on the left, locate inside the normal probability table. The left critical value is Using symmetry, the critical value on the right is The rule would be to reject the null hypothesis for any test value greater than or equal to 1.96 AND also to reject the null hypothesis for any test value smaller than CV = ± 1.96 Answer: Question 10 An energy official thinks that the oil output per well has declined from the 1998 level of 11.1 barrels per day. Use the.001 level of significance. State the null and alternate hypotheses. State the critical value or values, and the rejection rule. Since the energy official thinks that the oil output per well has declined, the hypotheses are: H 0 : μ = 11.1 H 1 : μ < 11.1 The test is left tailed since the alternate hypothesis has the < symbol. The rejection area in the one tail is equal to the level of significance or.001. Use the Normal Probability table backwards to find the z value with in the left tail. There are several z values with left tail probability equal to Use the center z value or The rule is to reject the null hypothesis if the test statistic is less than Dr. Janet Winter, Stat 200 Page 25

26 Answer: Question 11 Concerned that adult females under 51 years are not getting adequate iron intake, a statistician selected a random sample of women under 51 years old and found the listed iron intake in milligrams for a 24-hour period. Use a 5% level of significance and test his concern. Assume RDA for iron is 18mg and iron intake is normally distributed Use a calculator to find: X = 14.99, s = 3.22, n = H 0 : μ = 18.0 H 1 : μ < 18.0 (claim) not getting enough calcium translates into an alternate hypothesis μ < Use t since the population standard deviation is not given and the distribution is normal. ( ) t = = ( ) (16) = Use the t-table with df 16 1 = 15, because the population standard deviation σ is not given, but the variable is normally distributed. c.v. = Since this is a left-tailed test, the rejection region is to the left of Since the test value is to the left of c.v.=-1.753, it is in the rejection region. Reject the null hypothesis. 5. The data is sufficient to support the average daily iron intake is less than 18 for women under 51 years. Answer: Question 12 To see if young men ages 8 through 17 years spends an average of $24.44 per shopping trip to a local mall, the manager surveyed 33 young men and found the average amount spent per visit was $ The standard deviation of the sample was $3.70. Assume that the amount spent is normally distributed. At α = 0.02, can it be concluded that the average amount spent at a local mall is not equal to the national average of $24.44?. 1. H 0 : μ = $24.44 H 1 : μ $ t = ( ) = ( ) (33) = c.v. = ± df: 32. Dr. Janet Winter, Stat 200 Page 26

27 Do not reject the null hypothesis is the test statistic and is not less than , nor is it greater than The data is not sufficient to reject a mean average spending per shopping trip for men 8 through 17 years equal to $ Answer: Question 13 Last year the average cost of a concert ticket was $ This year, a random sample of 15 recent concerts had an average price of $62.30 with a variance of $ Assume the price of concert tickets is normally distributed. At the 0.05 level of significance, can it be concluded that the cost has increased? Use the critical value and the P-value method. n = 15 X =$62.30 s 2 = $90.25 Critical Value Method: 1. H 0 : μ = $54.80 H 1 : μ > $54.80 (claim) Use the t table to find the critical value with 0.05 in the one tail column and df 14 c.v. = Since the test statistic (3.06) is further out in the tail past the cv, reject the null hypothesis. 5. The data supports an increase in the average cost of concert tickets. Dr. Janet Winter, Stat 200 Page 27

28 P-value Method: 1. H 0 : μ = $54.80 H 1 : μ > $54.80 (claim) 2. t = X μ s n = = Find the area in the tail to the right of 3.06 (the test statistic) with df 15 1 = 14. The closest value on the chart is Since the area in the tail to the right of is.005, the area in the tail to the right of 3.06 would have to be less than.005 OR p <.005 using the formula p=tcdf (3.00, 100, 14) 4. Since P <.005, it is less than the level of significance which is.05. Reject the null hypothesis since p is less than alpha. 5. The data supports an average price greater than $ Answer: Question 14 A study published in the American Journal of Psychiatry measured the effect of alcohol on the developing hippocampus, or the portion of the brain responsible for long term memory. To 3 determine if the volume of the hippocampus is less than the normal 9.02 cm for adolescents who abuse alcohol, the research used a sample of 12 adolescents with alcohol abuse problems. The 3 3 average weight of their hippocampus was 8.10 cm with a standard deviation of 0.7 cm. Use the 0.01 level of significance. 1. H 0 : μ = 9.02 H 1 : μ < 9.02 (claim) 2. t = X μ s n = = ( ) = *Use t since the population standard deviation is not stated and n = 12 * Dr. Janet Winter, Stat 200 Page 28

29 3. Use the row with df: 12 1 to find the area less than is not on the table is the number closes to it. P = P( t < -4.55) < P(t < ) =.005 So, the P-value less than Reject the null hypothesis since P <.005 < α = The data supports a decrease in the size of the long term memory portion of the brain for adolescent who abuse alcohol. Answer: Question 15 The U.S. golf Association requires that golf balls have a diameter that is 1.68 inches. An engineer for the USGA wishes to discover whether Maxfli XS golf balls have a mean diameter different from 1.68 inches. A random sample of Maxfli Xs golf balls was selected. Assume the diameters are normally distributed and test with a 0.10 type one error rate. Conduct the test using the P-value method Using a calculator find: X = , s = , n = H 0 : μ = 1.68 (claim) H 1 : μ t = X μ s n = = ( ) = 0.77 *Use t since the population standard deviation is not stated, but the diameters are normally distributed with n = Since this is a two tailed test, find twice the area greater than 0.87 or P = 2P(t > 0.77) = 2tcdf( 0.77, 1000, 11) = Fail to reject the null hypothesis since P =.4575 > α = The data is not sufficient to reject an average diameter equal to Dr. Janet Winter, Stat 200 Page 29

30 Answer: Question 16 A Gallup Poll stated that women visit their physician an average of 5.8 times a year. The number of physician visits for 2007 is listed below for 20 randomly selected women: Assume that the number of physician visits is normally distributed. At the 0.05 level of significance can we conclude that the Gallup Poll average is correct? Use the p-value method. μ = 5.8 X = 3.85 n = 20 s = 2.52 = H 0 : μ = 5.8 H 1 : μ For a two tailed test, be sure to double the area past the test statistic. P = 2P (t <-3.46) with the TI-83: P = 2tcdf (-100, -3.46, 19) =.0026 with table F and df = 19, is smaller than the smallest value in that row is in the two tailed column.01 so, P < For calculator, since p =.0026 is less than alpha =.0500, reject the null hypothesis 5. For table work, since P <.01, it is also less that =.05. Reject the null hypothesis. 6. The data is sufficient to refute or reject an average number of yearly physician visits equal to 5.8 for females. Answer: Question 17 It has been reported that 40% of the adult population over 60 use . From a random sample of 180 adults, 65 used . At = 0.01, is there sufficient evidence to conclude that the proportion differs from 40%? Use the P-value method. p = 0.40 q = H 0 : p = 0.40 H 1 : p *Note: c.v. = ±2.58 Dr. Janet Winter, Stat 200 Page 30

31 3. For a two tailed test, the p-value is twice the area or probability in the tail past the test statistic. Table: P = 2P (z < -1.07) = 2(.1423) =.2846 TI-83: P = 2 normalcdf(-100, -1.07) = Since p = is not less than 0.01, do not reject the null hypothesis. 5. The data does not support a proportions using different from 40%. Answer: Question 18 USA TODAY reported that 63% of Americans will take a vacation this summer. In a survey of 143 Americans 85 were planning to vacation this summer. Use this data to test the USA TODAY report at the 0.05 level of significance with the critical value method. p = 0.63 q = H 0 : p = 0.63 (claim) H 1 : p C.V. = ± is not located in the rejection region which is further out in the tail from the c.v. Do not reject the null hypothesis. 5. The data is not sufficient to reject 63% of Americans will vacation this summer. Answer: Question 19 The manager of a large company is concerned about the variability of the time that it takes a telephone call to be transferred to the correct office in her company. A sample of 15 calls is selected, and the transfer time is recorded. The standard deviation of the sample is 1.8 minutes. At = 0.01, test if the population standard deviation is more than 1.2 minutes. Use the P-value method. = 0.01 s = 1.8 n = 15 d.f. = H 0 : = 1.2 H 1 : > This is a right tailed test, and the test statistic 31.5 is to the right of df = 14. Use right tail. 4. P value = < 0.01 Reject the null hypothesis. 5. The data does not support a standard deviation more than 1.2 minutes. Dr. Janet Winter, Stat 200 Page 31

32 Answer: Question 20 The data below is a random sample of home run totals for National League Champions from 1938 to At the 0.05 level of significance, is there sufficient evidence to conclude that the variance is smaller than 70? Use the prob-value method and the cv method Critical Value Answer: 1. a 2. a 3. cv = The rejection region is to the left of the cv since this is a left tailed test. 4. Fail to reject the null hypothesis since the test statistic 8.43 is not in the rejection region. 5. The data does not support a variance in the number of home runs smaller than 70. P-value Answer: a 2. a 3. Since this is a left tailed test, the p-value is the area between 0 and the test statistic or For table answers use the df line for 13 p >.10 and is not less than = Since p is not less than the level of significance of 0.05, do not reject the null hypothesis 5. The data does not support a variance in the number of home runs smaller than 70. Dr. Janet Winter, Stat 200 Page 32

Hypothesis Testing. Bluman Chapter 8

Hypothesis Testing. Bluman Chapter 8 CHAPTER 8 Learning Objectives C H A P T E R E I G H T Hypothesis Testing 1 Outline 8-1 Steps in Traditional Method 8-2 z Test for a Mean 8-3 t Test for a Mean 8-4 z Test for a Proportion 8-5 2 Test for

More information

Z-table p-values: use choice 2: normalcdf(

Z-table p-values: use choice 2: normalcdf( P-values with the Ti83/Ti84 Note: The majority of the commands used in this handout can be found under the DISTR menu which you can access by pressing [ nd ] [VARS]. You should see the following: NOTE:

More information

Hypothesis Testing --- One Mean

Hypothesis Testing --- One Mean Hypothesis Testing --- One Mean A hypothesis is simply a statement that something is true. Typically, there are two hypotheses in a hypothesis test: the null, and the alternative. Null Hypothesis The hypothesis

More information

5/31/2013. Chapter 8 Hypothesis Testing. Hypothesis Testing. Hypothesis Testing. Outline. Objectives. Objectives

5/31/2013. Chapter 8 Hypothesis Testing. Hypothesis Testing. Hypothesis Testing. Outline. Objectives. Objectives C H 8A P T E R Outline 8 1 Steps in Traditional Method 8 2 z Test for a Mean 8 3 t Test for a Mean 8 4 z Test for a Proportion 8 6 Confidence Intervals and Copyright 2013 The McGraw Hill Companies, Inc.

More information

Null Hypothesis H 0. The null hypothesis (denoted by H 0

Null Hypothesis H 0. The null hypothesis (denoted by H 0 Hypothesis test In statistics, a hypothesis is a claim or statement about a property of a population. A hypothesis test (or test of significance) is a standard procedure for testing a claim about a property

More information

Chapter Additional: Standard Deviation and Chi- Square

Chapter Additional: Standard Deviation and Chi- Square Chapter Additional: Standard Deviation and Chi- Square Chapter Outline: 6.4 Confidence Intervals for the Standard Deviation 7.5 Hypothesis testing for Standard Deviation Section 6.4 Objectives Interpret

More information

Section 7.1. Introduction to Hypothesis Testing. Schrodinger s cat quantum mechanics thought experiment (1935)

Section 7.1. Introduction to Hypothesis Testing. Schrodinger s cat quantum mechanics thought experiment (1935) Section 7.1 Introduction to Hypothesis Testing Schrodinger s cat quantum mechanics thought experiment (1935) Statistical Hypotheses A statistical hypothesis is a claim about a population. Null hypothesis

More information

Hypothesis testing: Examples. AMS7, Spring 2012

Hypothesis testing: Examples. AMS7, Spring 2012 Hypothesis testing: Examples AMS7, Spring 2012 Example 1: Testing a Claim about a Proportion Sect. 7.3, # 2: Survey of Drinking: In a Gallup survey, 1087 randomly selected adults were asked whether they

More information

LAB 4 INSTRUCTIONS CONFIDENCE INTERVALS AND HYPOTHESIS TESTING

LAB 4 INSTRUCTIONS CONFIDENCE INTERVALS AND HYPOTHESIS TESTING LAB 4 INSTRUCTIONS CONFIDENCE INTERVALS AND HYPOTHESIS TESTING In this lab you will explore the concept of a confidence interval and hypothesis testing through a simulation problem in engineering setting.

More information

8 6 X 2 Test for a Variance or Standard Deviation

8 6 X 2 Test for a Variance or Standard Deviation Section 8 6 x 2 Test for a Variance or Standard Deviation 437 This test uses the P-value method. Therefore, it is not necessary to enter a significance level. 1. Select MegaStat>Hypothesis Tests>Proportion

More information

Chapter 8. Hypothesis Testing

Chapter 8. Hypothesis Testing Chapter 8 Hypothesis Testing Hypothesis In statistics, a hypothesis is a claim or statement about a property of a population. A hypothesis test (or test of significance) is a standard procedure for testing

More information

Chapter 7. Section Introduction to Hypothesis Testing

Chapter 7. Section Introduction to Hypothesis Testing Section 7.1 - Introduction to Hypothesis Testing Chapter 7 Objectives: State a null hypothesis and an alternative hypothesis Identify type I and type II errors and interpret the level of significance Determine

More information

Hypothesis Testing with One Sample. Introduction to Hypothesis Testing 7.1. Hypothesis Tests. Chapter 7

Hypothesis Testing with One Sample. Introduction to Hypothesis Testing 7.1. Hypothesis Tests. Chapter 7 Chapter 7 Hypothesis Testing with One Sample 71 Introduction to Hypothesis Testing Hypothesis Tests A hypothesis test is a process that uses sample statistics to test a claim about the value of a population

More information

CHAPTER 9 HYPOTHESIS TESTING

CHAPTER 9 HYPOTHESIS TESTING CHAPTER 9 HYPOTHESIS TESTING The TI-83 Plus and TI-84 Plus fully support hypothesis testing. Use the key, then highlight TESTS. The options used in Chapter 9 are given on the two screens. TESTING A SINGLE

More information

Final Exam Practice Problem Answers

Final Exam Practice Problem Answers Final Exam Practice Problem Answers The following data set consists of data gathered from 77 popular breakfast cereals. The variables in the data set are as follows: Brand: The brand name of the cereal

More information

Calculating P-Values. Parkland College. Isela Guerra Parkland College. Recommended Citation

Calculating P-Values. Parkland College. Isela Guerra Parkland College. Recommended Citation Parkland College A with Honors Projects Honors Program 2014 Calculating P-Values Isela Guerra Parkland College Recommended Citation Guerra, Isela, "Calculating P-Values" (2014). A with Honors Projects.

More information

The alternative hypothesis,, is the statement that the parameter value somehow differs from that claimed by the null hypothesis. : 0.5 :>0.5 :<0.

The alternative hypothesis,, is the statement that the parameter value somehow differs from that claimed by the null hypothesis. : 0.5 :>0.5 :<0. Section 8.2-8.5 Null and Alternative Hypotheses... The null hypothesis,, is a statement that the value of a population parameter is equal to some claimed value. :=0.5 The alternative hypothesis,, is the

More information

Hypothesis Testing. Concept of Hypothesis Testing

Hypothesis Testing. Concept of Hypothesis Testing Quantitative Methods 2013 Hypothesis Testing with One Sample 1 Concept of Hypothesis Testing Testing Hypotheses is another way to deal with the problem of making a statement about an unknown population

More information

Two-Sample T-Tests Assuming Equal Variance (Enter Means)

Two-Sample T-Tests Assuming Equal Variance (Enter Means) Chapter 4 Two-Sample T-Tests Assuming Equal Variance (Enter Means) Introduction This procedure provides sample size and power calculations for one- or two-sided two-sample t-tests when the variances of

More information

The Goodness-of-Fit Test

The Goodness-of-Fit Test on the Lecture 49 Section 14.3 Hampden-Sydney College Tue, Apr 21, 2009 Outline 1 on the 2 3 on the 4 5 Hypotheses on the (Steps 1 and 2) (1) H 0 : H 1 : H 0 is false. (2) α = 0.05. p 1 = 0.24 p 2 = 0.20

More information

Chapter 9, Part A Hypothesis Tests. Learning objectives

Chapter 9, Part A Hypothesis Tests. Learning objectives Chapter 9, Part A Hypothesis Tests Slide 1 Learning objectives 1. Understand how to develop Null and Alternative Hypotheses 2. Understand Type I and Type II Errors 3. Able to do hypothesis test about population

More information

HypoTesting. Name: Class: Date: Multiple Choice Identify the choice that best completes the statement or answers the question.

HypoTesting. Name: Class: Date: Multiple Choice Identify the choice that best completes the statement or answers the question. Name: Class: Date: HypoTesting Multiple Choice Identify the choice that best completes the statement or answers the question. 1. A Type II error is committed if we make: a. a correct decision when the

More information

Chapter 8 Hypothesis Testing

Chapter 8 Hypothesis Testing Chapter 8 Hypothesis Testing Chapter problem: Does the MicroSort method of gender selection increase the likelihood that a baby will be girl? MicroSort: a gender-selection method developed by Genetics

More information

E205 Final: Version B

E205 Final: Version B Name: Class: Date: E205 Final: Version B Multiple Choice Identify the choice that best completes the statement or answers the question. 1. The owner of a local nightclub has recently surveyed a random

More information

Chapter 8 Introduction to Hypothesis Testing

Chapter 8 Introduction to Hypothesis Testing Chapter 8 Student Lecture Notes 8-1 Chapter 8 Introduction to Hypothesis Testing Fall 26 Fundamentals of Business Statistics 1 Chapter Goals After completing this chapter, you should be able to: Formulate

More information

Stats Review Chapters 9-10

Stats Review Chapters 9-10 Stats Review Chapters 9-10 Created by Teri Johnson Math Coordinator, Mary Stangler Center for Academic Success Examples are taken from Statistics 4 E by Michael Sullivan, III And the corresponding Test

More information

Chapter III. Testing Hypotheses

Chapter III. Testing Hypotheses Chapter III Testing Hypotheses R (Introduction) A statistical hypothesis is an assumption about a population parameter This assumption may or may not be true The best way to determine whether a statistical

More information

Chapter 8 Hypothesis Testing Chapter 8 Hypothesis Testing 8-1 Overview 8-2 Basics of Hypothesis Testing

Chapter 8 Hypothesis Testing Chapter 8 Hypothesis Testing 8-1 Overview 8-2 Basics of Hypothesis Testing Chapter 8 Hypothesis Testing 1 Chapter 8 Hypothesis Testing 8-1 Overview 8-2 Basics of Hypothesis Testing 8-3 Testing a Claim About a Proportion 8-5 Testing a Claim About a Mean: s Not Known 8-6 Testing

More information

Hypothesis Testing Population Mean

Hypothesis Testing Population Mean Z-test About One Mean ypothesis Testing Population Mean The Z-test about a mean of population we are using is applied in the following three cases: a. The population distribution is normal and the population

More information

1. What is the critical value for this 95% confidence interval? CV = z.025 = invnorm(0.025) = 1.96

1. What is the critical value for this 95% confidence interval? CV = z.025 = invnorm(0.025) = 1.96 1 Final Review 2 Review 2.1 CI 1-propZint Scenario 1 A TV manufacturer claims in its warranty brochure that in the past not more than 10 percent of its TV sets needed any repair during the first two years

More information

CHAPTER 11 SECTION 2: INTRODUCTION TO HYPOTHESIS TESTING

CHAPTER 11 SECTION 2: INTRODUCTION TO HYPOTHESIS TESTING CHAPTER 11 SECTION 2: INTRODUCTION TO HYPOTHESIS TESTING MULTIPLE CHOICE 56. In testing the hypotheses H 0 : µ = 50 vs. H 1 : µ 50, the following information is known: n = 64, = 53.5, and σ = 10. The standardized

More information

9-3.4 Likelihood ratio test. Neyman-Pearson lemma

9-3.4 Likelihood ratio test. Neyman-Pearson lemma 9-3.4 Likelihood ratio test Neyman-Pearson lemma 9-1 Hypothesis Testing 9-1.1 Statistical Hypotheses Statistical hypothesis testing and confidence interval estimation of parameters are the fundamental

More information

Chapter 8: Hypothesis Testing of a Single Population Parameter

Chapter 8: Hypothesis Testing of a Single Population Parameter Chapter 8: Hypothesis Testing of a Single Population Parameter THE LANGUAGE OF STATISTICAL DECISION MAKING DEFINITIONS: The population is the entire group of objects or individuals under study, about which

More information

HYPOTHESIS TESTING: POWER OF THE TEST

HYPOTHESIS TESTING: POWER OF THE TEST HYPOTHESIS TESTING: POWER OF THE TEST The first 6 steps of the 9-step test of hypothesis are called "the test". These steps are not dependent on the observed data values. When planning a research project,

More information

Tests of Hypotheses: Means

Tests of Hypotheses: Means Tests of Hypotheses: Means We often use inferential statistics to make decisions or judgments about the value of a parameter, such as a population mean. For example, we might need to decide whether the

More information

4. Continuous Random Variables, the Pareto and Normal Distributions

4. Continuous Random Variables, the Pareto and Normal Distributions 4. Continuous Random Variables, the Pareto and Normal Distributions A continuous random variable X can take any value in a given range (e.g. height, weight, age). The distribution of a continuous random

More information

Unit 29 Chi-Square Goodness-of-Fit Test

Unit 29 Chi-Square Goodness-of-Fit Test Unit 29 Chi-Square Goodness-of-Fit Test Objectives: To perform the chi-square hypothesis test concerning proportions corresponding to more than two categories of a qualitative variable To perform the Bonferroni

More information

Two Related Samples t Test

Two Related Samples t Test Two Related Samples t Test In this example 1 students saw five pictures of attractive people and five pictures of unattractive people. For each picture, the students rated the friendliness of the person

More information

Business Statistics, 9e (Groebner/Shannon/Fry) Chapter 9 Introduction to Hypothesis Testing

Business Statistics, 9e (Groebner/Shannon/Fry) Chapter 9 Introduction to Hypothesis Testing Business Statistics, 9e (Groebner/Shannon/Fry) Chapter 9 Introduction to Hypothesis Testing 1) Hypothesis testing and confidence interval estimation are essentially two totally different statistical procedures

More information

8-2 Basics of Hypothesis Testing. Definitions. Rare Event Rule for Inferential Statistics. Null Hypothesis

8-2 Basics of Hypothesis Testing. Definitions. Rare Event Rule for Inferential Statistics. Null Hypothesis 8-2 Basics of Hypothesis Testing Definitions This section presents individual components of a hypothesis test. We should know and understand the following: How to identify the null hypothesis and alternative

More information

HYPOTHESIS TESTING (ONE SAMPLE) - CHAPTER 7 1. used confidence intervals to answer questions such as...

HYPOTHESIS TESTING (ONE SAMPLE) - CHAPTER 7 1. used confidence intervals to answer questions such as... HYPOTHESIS TESTING (ONE SAMPLE) - CHAPTER 7 1 PREVIOUSLY used confidence intervals to answer questions such as... You know that 0.25% of women have red/green color blindness. You conduct a study of men

More information

7 Hypothesis testing - one sample tests

7 Hypothesis testing - one sample tests 7 Hypothesis testing - one sample tests 7.1 Introduction Definition 7.1 A hypothesis is a statement about a population parameter. Example A hypothesis might be that the mean age of students taking MAS113X

More information

Sampling and Hypothesis Testing

Sampling and Hypothesis Testing Population and sample Sampling and Hypothesis Testing Allin Cottrell Population : an entire set of objects or units of observation of one sort or another. Sample : subset of a population. Parameter versus

More information

Math 251, Review Questions for Test 3 Rough Answers

Math 251, Review Questions for Test 3 Rough Answers Math 251, Review Questions for Test 3 Rough Answers 1. (Review of some terminology from Section 7.1) In a state with 459,341 voters, a poll of 2300 voters finds that 45 percent support the Republican candidate,

More information

Point Biserial Correlation Tests

Point Biserial Correlation Tests Chapter 807 Point Biserial Correlation Tests Introduction The point biserial correlation coefficient (ρ in this chapter) is the product-moment correlation calculated between a continuous random variable

More information

Review #2. Statistics

Review #2. Statistics Review #2 Statistics Find the mean of the given probability distribution. 1) x P(x) 0 0.19 1 0.37 2 0.16 3 0.26 4 0.02 A) 1.64 B) 1.45 C) 1.55 D) 1.74 2) The number of golf balls ordered by customers of

More information

Difference of Means and ANOVA Problems

Difference of Means and ANOVA Problems Difference of Means and Problems Dr. Tom Ilvento FREC 408 Accounting Firm Study An accounting firm specializes in auditing the financial records of large firm It is interested in evaluating its fee structure,particularly

More information

Two-Sample T-Tests Allowing Unequal Variance (Enter Difference)

Two-Sample T-Tests Allowing Unequal Variance (Enter Difference) Chapter 45 Two-Sample T-Tests Allowing Unequal Variance (Enter Difference) Introduction This procedure provides sample size and power calculations for one- or two-sided two-sample t-tests when no assumption

More information

Wording of Final Conclusion. Slide 1

Wording of Final Conclusion. Slide 1 Wording of Final Conclusion Slide 1 8.3: Assumptions for Testing Slide 2 Claims About Population Means 1) The sample is a simple random sample. 2) The value of the population standard deviation σ is known

More information

An Introduction to Statistics Course (ECOE 1302) Spring Semester 2011 Chapter 10- TWO-SAMPLE TESTS

An Introduction to Statistics Course (ECOE 1302) Spring Semester 2011 Chapter 10- TWO-SAMPLE TESTS The Islamic University of Gaza Faculty of Commerce Department of Economics and Political Sciences An Introduction to Statistics Course (ECOE 130) Spring Semester 011 Chapter 10- TWO-SAMPLE TESTS Practice

More information

T-test in SPSS Hypothesis tests of proportions Confidence Intervals (End of chapter 6 material)

T-test in SPSS Hypothesis tests of proportions Confidence Intervals (End of chapter 6 material) T-test in SPSS Hypothesis tests of proportions Confidence Intervals (End of chapter 6 material) Definition of p-value: The probability of getting evidence as strong as you did assuming that the null hypothesis

More information

Chapter 2. Hypothesis testing in one population

Chapter 2. Hypothesis testing in one population Chapter 2. Hypothesis testing in one population Contents Introduction, the null and alternative hypotheses Hypothesis testing process Type I and Type II errors, power Test statistic, level of significance

More information

Estimating and Finding Confidence Intervals

Estimating and Finding Confidence Intervals . Activity 7 Estimating and Finding Confidence Intervals Topic 33 (40) Estimating A Normal Population Mean μ (σ Known) A random sample of size 10 from a population of heights that has a normal distribution

More information

THE FIRST SET OF EXAMPLES USE SUMMARY DATA... EXAMPLE 7.2, PAGE 227 DESCRIBES A PROBLEM AND A HYPOTHESIS TEST IS PERFORMED IN EXAMPLE 7.

THE FIRST SET OF EXAMPLES USE SUMMARY DATA... EXAMPLE 7.2, PAGE 227 DESCRIBES A PROBLEM AND A HYPOTHESIS TEST IS PERFORMED IN EXAMPLE 7. THERE ARE TWO WAYS TO DO HYPOTHESIS TESTING WITH STATCRUNCH: WITH SUMMARY DATA (AS IN EXAMPLE 7.17, PAGE 236, IN ROSNER); WITH THE ORIGINAL DATA (AS IN EXAMPLE 8.5, PAGE 301 IN ROSNER THAT USES DATA FROM

More information

Class 19: Two Way Tables, Conditional Distributions, Chi-Square (Text: Sections 2.5; 9.1)

Class 19: Two Way Tables, Conditional Distributions, Chi-Square (Text: Sections 2.5; 9.1) Spring 204 Class 9: Two Way Tables, Conditional Distributions, Chi-Square (Text: Sections 2.5; 9.) Big Picture: More than Two Samples In Chapter 7: We looked at quantitative variables and compared the

More information

Box plots & t-tests. Example

Box plots & t-tests. Example Box plots & t-tests Box Plots Box plots are a graphical representation of your sample (easy to visualize descriptive statistics); they are also known as box-and-whisker diagrams. Any data that you can

More information

1. Rejecting a true null hypothesis is classified as a error. 2. Failing to reject a false null hypothesis is classified as a error.

1. Rejecting a true null hypothesis is classified as a error. 2. Failing to reject a false null hypothesis is classified as a error. 1. Rejecting a true null hypothesis is classified as a error. 2. Failing to reject a false null hypothesis is classified as a error. 8.5 Goodness of Fit Test Suppose we want to make an inference about

More information

Statistics for Management II-STAT 362-Final Review

Statistics for Management II-STAT 362-Final Review Statistics for Management II-STAT 362-Final Review Multiple Choice Identify the letter of the choice that best completes the statement or answers the question. 1. The ability of an interval estimate to

More information

Section 8-1 Pg. 410 Exercises 12,13

Section 8-1 Pg. 410 Exercises 12,13 Section 8- Pg. 4 Exercises 2,3 2. Using the z table, find the critical value for each. a) α=.5, two-tailed test, answer: -.96,.96 b) α=., left-tailed test, answer: -2.33, 2.33 c) α=.5, right-tailed test,

More information

Hypothesis Testing (unknown σ)

Hypothesis Testing (unknown σ) Hypothesis Testing (unknown σ) Business Statistics Recall: Plan for Today Null and Alternative Hypotheses Types of errors: type I, type II Types of correct decisions: type A, type B Level of Significance

More information

How to Conduct a Hypothesis Test

How to Conduct a Hypothesis Test How to Conduct a Hypothesis Test The idea of hypothesis testing is relatively straightforward. In various studies we observe certain events. We must ask, is the event due to chance alone, or is there some

More information

Graphing calculators in teaching statistical p-values to elementary statistics students

Graphing calculators in teaching statistical p-values to elementary statistics students Graphing calculators in teaching statistical p-values to elementary statistics students ABSTRACT Eric Benson American University in Dubai The statistical output of interest to most elementary statistics

More information

Chapter 1 Hypothesis Testing

Chapter 1 Hypothesis Testing Chapter 1 Hypothesis Testing Principles of Hypothesis Testing tests for one sample case 1 Statistical Hypotheses They are defined as assertion or conjecture about the parameter or parameters of a population,

More information

Module 5 Hypotheses Tests: Comparing Two Groups

Module 5 Hypotheses Tests: Comparing Two Groups Module 5 Hypotheses Tests: Comparing Two Groups Objective: In medical research, we often compare the outcomes between two groups of patients, namely exposed and unexposed groups. At the completion of this

More information

Chapter 9: Hypothesis Testing GBS221, Class April 15, 2013 Notes Compiled by Nicolas C. Rouse, Instructor, Phoenix College

Chapter 9: Hypothesis Testing GBS221, Class April 15, 2013 Notes Compiled by Nicolas C. Rouse, Instructor, Phoenix College Chapter Objectives 1. Learn how to formulate and test hypotheses about a population mean and a population proportion. 2. Be able to use an Excel worksheet to conduct hypothesis tests about population means

More information

I. Basics of Hypothesis Testing

I. Basics of Hypothesis Testing Introduction to Hypothesis Testing This deals with an issue highly similar to what we did in the previous chapter. In that chapter we used sample information to make inferences about the range of possibilities

More information

Chapter 8. Professor Tim Busken. April 20, Chapter 8. Tim Busken. 8.2 Basics of. Hypothesis Testing. Works Cited

Chapter 8. Professor Tim Busken. April 20, Chapter 8. Tim Busken. 8.2 Basics of. Hypothesis Testing. Works Cited Chapter 8 Professor April 20, 2014 In Chapter 8, we continue our study of inferential statistics. Concept: Inferential Statistics The two major activities of inferential statistics are 1 to use sample

More information

Statistics 100 Sample Final Questions (Note: These are mostly multiple choice, for extra practice. Your Final Exam will NOT have any multiple choice!

Statistics 100 Sample Final Questions (Note: These are mostly multiple choice, for extra practice. Your Final Exam will NOT have any multiple choice! Statistics 100 Sample Final Questions (Note: These are mostly multiple choice, for extra practice. Your Final Exam will NOT have any multiple choice!) Part A - Multiple Choice Indicate the best choice

More information

Two-sample hypothesis testing, I 9.07 3/09/2004

Two-sample hypothesis testing, I 9.07 3/09/2004 Two-sample hypothesis testing, I 9.07 3/09/2004 But first, from last time More on the tradeoff between Type I and Type II errors The null and the alternative: Sampling distribution of the mean, m, given

More information

Regression. Name: Class: Date: Multiple Choice Identify the choice that best completes the statement or answers the question.

Regression. Name: Class: Date: Multiple Choice Identify the choice that best completes the statement or answers the question. Class: Date: Regression Multiple Choice Identify the choice that best completes the statement or answers the question. 1. Given the least squares regression line y8 = 5 2x: a. the relationship between

More information

Nonparametric Statistics

Nonparametric Statistics 1 14.1 Using the Binomial Table Nonparametric Statistics In this chapter, we will survey several methods of inference from Nonparametric Statistics. These methods will introduce us to several new tables

More information

(pronounced kie-square ; text Ch. 15) She s the sweetheart of The page from the Book of Kells

(pronounced kie-square ; text Ch. 15) She s the sweetheart of The page from the Book of Kells Applications (pronounced kie-square ; text Ch. 15) She s the sweetheart of The page from the Book of Kells Tests for Independence is characteristic R the same or different in different populations? Tests

More information

Statistics 641 - EXAM II - 1999 through 2003

Statistics 641 - EXAM II - 1999 through 2003 Statistics 641 - EXAM II - 1999 through 2003 December 1, 1999 I. (40 points ) Place the letter of the best answer in the blank to the left of each question. (1) In testing H 0 : µ 5 vs H 1 : µ > 5, the

More information

Notes 8: Hypothesis Testing

Notes 8: Hypothesis Testing Notes 8: Hypothesis Testing Julio Garín Department of Economics Statistics for Economics Spring 2012 (Stats for Econ) Hypothesis Testing Spring 2012 1 / 44 Introduction Why we conduct surveys? We want

More information

NCSS Statistical Software

NCSS Statistical Software Chapter 06 Introduction This procedure provides several reports for the comparison of two distributions, including confidence intervals for the difference in means, two-sample t-tests, the z-test, the

More information

12 Hypothesis Testing

12 Hypothesis Testing CHAPTER 12 Hypothesis Testing Chapter Outline 12.1 HYPOTHESIS TESTING 12.2 CRITICAL VALUES 12.3 ONE-SAMPLE T TEST 247 12.1. Hypothesis Testing www.ck12.org 12.1 Hypothesis Testing Learning Objectives Develop

More information

AP Statistics 2002 Scoring Guidelines

AP Statistics 2002 Scoring Guidelines AP Statistics 2002 Scoring Guidelines The materials included in these files are intended for use by AP teachers for course and exam preparation in the classroom; permission for any other use must be sought

More information

HYPOTHESIS TESTING (ONE SAMPLE) - CHAPTER 7 1. used confidence intervals to answer questions such as...

HYPOTHESIS TESTING (ONE SAMPLE) - CHAPTER 7 1. used confidence intervals to answer questions such as... HYPOTHESIS TESTING (ONE SAMPLE) - CHAPTER 7 1 PREVIOUSLY used confidence intervals to answer questions such as... You know that 0.25% of women have red/green color blindness. You conduct a study of men

More information

Chapter 4. iclicker Question 4.4 Pre-lecture. Part 2. Binomial Distribution. J.C. Wang. iclicker Question 4.4 Pre-lecture

Chapter 4. iclicker Question 4.4 Pre-lecture. Part 2. Binomial Distribution. J.C. Wang. iclicker Question 4.4 Pre-lecture Chapter 4 Part 2. Binomial Distribution J.C. Wang iclicker Question 4.4 Pre-lecture iclicker Question 4.4 Pre-lecture Outline Computing Binomial Probabilities Properties of a Binomial Distribution Computing

More information

Psychology 60 Fall 2013 Practice Exam Actual Exam: Next Monday. Good luck!

Psychology 60 Fall 2013 Practice Exam Actual Exam: Next Monday. Good luck! Psychology 60 Fall 2013 Practice Exam Actual Exam: Next Monday. Good luck! Name: 1. The basic idea behind hypothesis testing: A. is important only if you want to compare two populations. B. depends on

More information

Lecture 42 Section 14.3. Tue, Apr 8, 2008

Lecture 42 Section 14.3. Tue, Apr 8, 2008 the Lecture 42 Section 14.3 Hampden-Sydney College Tue, Apr 8, 2008 Outline the 1 2 the 3 4 5 the The will compute χ 2 areas, but not χ 2 percentiles. (That s ok.) After performing the χ 2 test by hand,

More information

Stats on the TI 83 and TI 84 Calculator

Stats on the TI 83 and TI 84 Calculator Stats on the TI 83 and TI 84 Calculator Entering the sample values STAT button Left bracket { Right bracket } Store (STO) List L1 Comma Enter Example: Sample data are {5, 10, 15, 20} 1. Press 2 ND and

More information

Hypothesis Testing hypothesis testing approach formulation of the test statistic

Hypothesis Testing hypothesis testing approach formulation of the test statistic Hypothesis Testing For the next few lectures, we re going to look at various test statistics that are formulated to allow us to test hypotheses in a variety of contexts: In all cases, the hypothesis testing

More information

A POPULATION MEAN, CONFIDENCE INTERVALS AND HYPOTHESIS TESTING

A POPULATION MEAN, CONFIDENCE INTERVALS AND HYPOTHESIS TESTING CHAPTER 5. A POPULATION MEAN, CONFIDENCE INTERVALS AND HYPOTHESIS TESTING 5.1 Concepts When a number of animals or plots are exposed to a certain treatment, we usually estimate the effect of the treatment

More information

STA 2023H Solutions for Practice Test 4

STA 2023H Solutions for Practice Test 4 1. Which statement is not true about confidence intervals? A. A confidence interval is an interval of values computed from sample data that is likely to include the true population value. B. An approximate

More information

Statistics 2014 Scoring Guidelines

Statistics 2014 Scoring Guidelines AP Statistics 2014 Scoring Guidelines College Board, Advanced Placement Program, AP, AP Central, and the acorn logo are registered trademarks of the College Board. AP Central is the official online home

More information

NCSS Statistical Software. One-Sample T-Test

NCSS Statistical Software. One-Sample T-Test Chapter 205 Introduction This procedure provides several reports for making inference about a population mean based on a single sample. These reports include confidence intervals of the mean or median,

More information

Pearson's Correlation Tests

Pearson's Correlation Tests Chapter 800 Pearson's Correlation Tests Introduction The correlation coefficient, ρ (rho), is a popular statistic for describing the strength of the relationship between two variables. The correlation

More information

Hypothesis testing - Steps

Hypothesis testing - Steps Hypothesis testing - Steps Steps to do a two-tailed test of the hypothesis that β 1 0: 1. Set up the hypotheses: H 0 : β 1 = 0 H a : β 1 0. 2. Compute the test statistic: t = b 1 0 Std. error of b 1 =

More information

MCQ TESTING OF HYPOTHESIS

MCQ TESTING OF HYPOTHESIS MCQ TESTING OF HYPOTHESIS MCQ 13.1 A statement about a population developed for the purpose of testing is called: (a) Hypothesis (b) Hypothesis testing (c) Level of significance (d) Test-statistic MCQ

More information

Lecture Notes Module 1

Lecture Notes Module 1 Lecture Notes Module 1 Study Populations A study population is a clearly defined collection of people, animals, plants, or objects. In psychological research, a study population usually consists of a specific

More information

9.1 Basic Principles of Hypothesis Testing

9.1 Basic Principles of Hypothesis Testing 9. Basic Principles of Hypothesis Testing Basic Idea Through an Example: On the very first day of class I gave the example of tossing a coin times, and what you might conclude about the fairness of the

More information

Hypothesis testing for µ:

Hypothesis testing for µ: University of California, Los Angeles Department of Statistics Statistics 13 Elements of a hypothesis test: Hypothesis testing Instructor: Nicolas Christou 1. Null hypothesis, H 0 (always =). 2. Alternative

More information

For instance, a car dealer advertises that its new small truck gets 35 miles per gallon, on the average.

For instance, a car dealer advertises that its new small truck gets 35 miles per gallon, on the average. Hypothesis Testing: Single Mean and Single Proportion Introduction One job of a statistician is to make statistical inferences about populations based on samples taken from the population. Confidence intervals

More information

PASS Sample Size Software

PASS Sample Size Software Chapter 250 Introduction The Chi-square test is often used to test whether sets of frequencies or proportions follow certain patterns. The two most common instances are tests of goodness of fit using multinomial

More information

Hypothesis Testing. Steps for a hypothesis test:

Hypothesis Testing. Steps for a hypothesis test: Hypothesis Testing Steps for a hypothesis test: 1. State the claim H 0 and the alternative, H a 2. Choose a significance level or use the given one. 3. Draw the sampling distribution based on the assumption

More information

Introduction to Hypothesis Testing. Copyright 2014 Pearson Education, Inc. 9-1

Introduction to Hypothesis Testing. Copyright 2014 Pearson Education, Inc. 9-1 Introduction to Hypothesis Testing 9-1 Learning Outcomes Outcome 1. Formulate null and alternative hypotheses for applications involving a single population mean or proportion. Outcome 2. Know what Type

More information

Chapter 7. Hypothesis Testing with One Sample

Chapter 7. Hypothesis Testing with One Sample Chapter 7 Hypothesis Testing with One Sample 7.1 Introduction to Hypothesis Testing Hypothesis Tests A hypothesis test is a process that uses sample statistics to test a claim about the value of a population

More information

Comparing Two Groups. Standard Error of ȳ 1 ȳ 2. Setting. Two Independent Samples

Comparing Two Groups. Standard Error of ȳ 1 ȳ 2. Setting. Two Independent Samples Comparing Two Groups Chapter 7 describes two ways to compare two populations on the basis of independent samples: a confidence interval for the difference in population means and a hypothesis test. The

More information

Math 10. Hypothesis Testing Design. Math 10 Part 6 Hypothesis Testing. Maurice Geraghty, 2011 1. Procedures of Hypotheses Testing

Math 10. Hypothesis Testing Design. Math 10 Part 6 Hypothesis Testing. Maurice Geraghty, 2011 1. Procedures of Hypotheses Testing Procedures of Hypotheses Testing Math 1 Part 6 Hypothesis Testing Maurice Geraghty, 21 1 2 Hypotheses Testing Procedure 1 General Research Question Decide on a topic or phenomena that you want to research.

More information