Report of for Chapter 2 pretest

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Report of for Chapter 2 pretest"

Transcription

1 Report of for Chapter 2 pretest Exam: Chapter 2 pretest Category: Organizing and Graphing Data 1. "For our study of driving habits, we recorded the speed of every fifth vehicle on Drury Lane. Nearly every car traveled right at the speed limit or a little over, but there were some that were 10 mph under, even fewer at 20 mph under, and one car that crept by a just 15 mph. On the basis of the central tendency calculation on our data, we drew conclusions about all drivers on this stretch of road." The proper central tendency value calculated from the data is the Correct Answer population median; sample median; population mean (m); sample mean (`X). In this situation, the speed (ratio scale) of every fifth vehicle was recorded. The first thing to note then is that the researchers have generated data from a systematic random sample. We would also note that the shape of the distribution was negatively skewed with a few very slow speeds and most at or slightly over the speed limit. In a negatively skewed distribution, the median is not senstive to outlying data and thus would present a clearer summary than the mean of driver performance on the targeted stretch of road. Since the data represent a sample, the sample median would be the correct response to this question. Help: none Confident: 36/100 Central tendency measures: statistics - parameters: 67 Mean, Median, and Mode in frequency distributions: 66 Time of problem: 0 minutes seconds 2. Which of the following is not an accurate statement of one of the conventions your text used in establishing class intervals?

2 Use not fewer than 10 or more than 20 class intervals; Class intervals should start with an odd number or a multiple of 10; The largest scores should be at the top of the list of class intervals; Correct Answer All of the above are correct statements. All are correct answers. There are 4 general criteria or guidelines for establishing class intervals. 1. The number of intervals should be between 10 and The class interval should be convenient size. For example, Use an odd number such as 3, 5, or 7 for the interval width to make it easy to compute the midpoint of the interval. Use widths of 10, 20, 50, or 100 where appropriate to make it easy for the reader to "understand" the intervals. When displaying test data based on a 100 point scale, 10-point intervals like 50-59, 60-69, 70-79, 80-89, and make sense to most folks because they correspond in general to letter grade distributions. 3. Begin each class interval with a multiple of i. 4. The largest scores should go at the top of the distribution. Confident: 73/100 Frequency Distributions: 67 Time of problem: 0 minutes seconds 3. A frequency distribution with a mean of 100 and a median of 90 is Correct Answer positively skewed; negatively skewed; neither positive nor negative; cannot be determined from the information given.

3 Positively skewed is the correct answer. In a symmetrical distribution, the mode=mean=median. If I know that the mean is greater than the median, I know that there must be some high scores in the distribution that are pulling the mean away from the center of the distribution. This is a situation where outliers are influencing how the distribution is shaped. When a few high numbers pull the mean away from the center of the distribution, the tail of the distribtion pointing to the high numbers is stretched in a positive direction, hence, the distribution is positively skewed. Confident: 69/100 Mean, Median, and Mode (Define): 83 Mean, Median, and Mode in frequency distributions: 66 Time of problem: 0 minutes seconds 4. Which of the following words could legitimately fit into this sentence: "That simple frequency distribution has two, 13 and 18." means; medians; Correct Answer modes; all of the above. Modes is the correct answer. A distribution can have only one mean and only one median. Means and medians are computed values whereas the mode reflects the most frequently occurring value(s). In a simple frequency distribution (where scores are presented in an ascending or desending order accompanied by the number of occurrences for each score), the mode is the frequently appearing score or scores in the distribution. In a group frequency distribution, the mode is the midpoint of the interval that contains the most scores. Group frequency distributions can also be multimodal if more than one interval has the same high frequency count. Confident: 85/100 Mean, Median, and Mode (Define): 83 Mean, Median, and Mode in frequency distributions: 66 Time of problem: 0 minutes 6.77 seconds

4 5. The U.S. Department of Agriculture reported the total number of bushels harvested of corn, soy beans, wheat, rice, and oats. This is a frequency distribution of a Correct Answer nominal variable; ordinal variable; interval variable; ratio variable. Nominal variable is the correct response. The data in this question is nominal, that is categories are set up according to names like corn, wheat, soy beans, etc. There is no order to the variables, just simple categories and frequencies indicating the total number of bushels harvested in each category. A bar graph would be used to visually present this information. Histograms, frequency polygons, and line graphs are used when the underlying scale of measurement is continuous (interval or ratio). In this case, the underlying scale of measurement is nominal, so we want a presentation device that separates the different categories and that vehicle is the bar graph. The bar graph allows the reader to compare categories without regard to order. Confident: 100/100 Frequency graphs: 59 Time of problem: 0 minutes seconds 6. Which of the following is not used to present a frequency distribution? a bar graph; Correct Answer a scatterplot; a line graph; a histogram. Scatterplot is the correct response. A scatterplot shows the relationship between two quantitative variables, both measured on either an interval or ratio scale. The bar graph, histogram, and frequency polygon all indicate frequency values on the Y-axis and measurement on one variable represented on the X-axis. In a scatterplot, a point represents a the value on the Y variable that goes with the corresponding value on the

5 X variable. In a scatterplot, measurement for both the X and Y variables requires underlying scales of measurement that are continuous (interval or ratio). Confident: 90/100 Frequency graphs: 59 Time of problem: 0 minutes seconds 7. To present a frequency distribution of nominal data you should use a polygon; a histogram; a line graph; Correct Answer a bar graph. Bar graph is the correct response. With nominal data, the underlying scale of measurement is categorical, reflecting no specific order or equal distances between categories. Of the choices, only the bar graph makes sense for categorical data. The bars in a bar graph do not touch, emphasizing the separateness of the categories. Confident: 100/100 Frequency graphs: 59 Time of problem: 0 minutes seconds 8. In a set of scores that ranged from 11 to 50, an acceptable lowest class interval would be 11-13; 11-14; 9-12; Correct Answer is the correct answer. Remember:

6 a. the number of intervals should be between 10 and 20; b. the size for the class interval should be convenient; and c. each interval should begin with a value that is a multiple of the interval. Given the guidelines above, the range of values is 40 [(50-11)+1]. Dividing 40 by 10 (the recommended number of intervals) yields an interval width of 4. But, this interval width is not convenient because of midpoint problems. A better choice would be an interval width of 3 which would give us more than 10 intervals and a convenient width to work with when computing midpoints. This eliminates choices b and c. Given an interval width of 3, only the interval 9 to 11 begins with a multiple of 3. Confident: 26/100 Frequency Distributions: 67 Time of problem: 0 minutes seconds 9. In which situation would the mean be an appropriate measure of central tendency? Correct Answer Most of the scores are near the minimum, a few are in the middle range, and there are almost none near the maximum; We have frequency data on cows, horses, mules, and goats; You The data categories in the soil analysis are: 0-2 ppm, 3-5 ppm, 6-8 ppm, 9- Answered 11 ppm, and over 11 ppm; A few scores are at the minimum of the range, some scores are in the middle range, most scores are near the maximum; None of the above; The mean would be the appropriate measure of center for a, c, and d. If I'm looking for a single score to communicate how a group of individuals has performed, the mean is the best measure of central tendency when the measurement scale is continuous (interval or ratio) and the distribution of scores is reasonably symmetric. Because the mean is mathematically derived and represents the SX N, outliers in the data set can artificially raise or lower the mean by increasing or decreasing SX. Thus, in distributions that are skewed, the outlying data could render the mean too high or too low and make the median a more representative and informative measure of central tendency. When the distribution is symmetric (most of the scores are near the minimum, a few are in the middle range, and there are almost

7 none near the maximum) and the measurement scale is continuous, the mean is the most appropriate and most commonly used measure of central tendency. Stems b and c feature nominal data (mode only) and stem d describes a negatively skewed distribution in which case the median would be a better measure of central tendency than the mean. Confident: 68/100 Central tendency measures: statistics - parameters: 67 Mean, Median, and Mode (Define): 83 Time of problem: 0 minutes seconds 10. Following are final examination scores for 40 students in a basic statistics class. These scores were randomly selected from the records of all students who have taken the course over the past 10 years and have taken the standardized final examination a. Create a simple frequency distribution. b. Create grouped frequency distributions with interval widths of 3 and 5. Include columns for class intervals, exact limits, midpoints, f, cf, %, and c% in your tables. c. Draw histograms, keeping the same scale on the Y axis the same for each of the grouped frequency distributions. d. Draw a boxplot for this data using the five-number summary [X min,

8 X max, Q 3, Q 1, and the Median]. Note. You may eliminate this question as we have yet to cover boxplots. e. Comparing the two histograms, which do you think best represents the distribution and why? f. Using the group frequency distribution (i = 5), compute the percentiles for scores of 63 and 81. g. Using the group frequency distribution (i = 5), what score corresponds to the 15 th percentile? h. Compute the mean and standard deviation for this set of scores using both the deviation and raw score methods? Should you generate population parameters or sample statistics? Why? Note. Compute the mean but leave the standard deviation for later; we haven't covered it yet. i. From the grouped frequency distribution (i = 5), what are the values for the median and the mode? j. Given what you know about distributions and measures of center, what can you conclude about this data set? Your Answer: placeholder The full explanation for this question, along with tables, histograms, boxplot, summary statistics, and computations can be viewed and printed by clicking on the following link: a. The simple frequency distribution can be viewed on the linked page. In ascending order the data are: 58,60,61,63,63,65,65,68,68,70,72,72,73,74,75,75,75,76,76,79 80,80,80,81,82,82,82,82,82,84,84,86,86,88,89,89,90,91,94,96 b. Class Interval Exact Limits Midpoint f cf % c%

9 c. Class Interval Exact Limits Midpoint f cf % c% d. See linked page. e. See linked page.

10 f. In this distribution, scores range from 58 to 96, a distance of 39 score points. Generally, you are looking to create between 10 and 20 intervals. The interval width should be odd and it should make sense in terms of the distribution. The lower limit of the first interval should be a multiple of the interval width and include the lowest value in the distribution. Divide 39 by 10 and you get 3.9. The closest whole number value to 3.9 is 4.0, but this value is an even number which makes computation of the midpoint somewhat difficult. This leads us to considering interval widths of 3 and 5. A width of 3 yields 14 class intervals starting at and ending at A width of 5 yields 9 class intervals starting at and ending at Look over the histograms. With an interval width of 3, the distribution looks too flat, too sparse. There are not enough cases to adequately populate the 14 class intervals. An interval width of 5 on the other hand, leads to a much more cogent picture of the distribution, a slight negative skew, with bunching in the middle of the distribuiton. Moreover, an interval width of 5 makes sense, in that test scores naturally break at points of 90, 80, 70, 60, etc. g. Percentiles:

11 h. Percentile Rank: i. See linked page. The data is a random sample and will be used to describe the general characteristics of the population, all students who have taken the introductory statistics class over the past 10 years. Therefore, you should be computing sample statistics and using n-1 in the denominator of the standard deviation formula. j. In the grouped frequency distribution, the interval from 80 to 84 has the highest frequency (11), so the mode is the midpoint of that interval, 82. The median of the distribution is also in the interval from (79.5 to 84.5). The c% associated with the lower limit is 47.5 and with the upper limit is % (11 40) of the cases are in this interval. To compute the median, subtract 47.5 from 50 to get 2.5. Divide 2.5 by 27.5 to get.09. Multiply.09 times the interval width (5) to get.45 and add the.45 to 79.5 to get 79.95, the median.

12 Slight negative skew in the exam score distribution Scores bunched in the area Mean=77.4; Median= % of the students scored at or below 70 and 25% scored at or above 84. The score distribution might be interpreted to suggest that students were generally well prepared for the exam. The slight negative skew bunched in the 80% to 85% area indicates that the exam was challenging but fair. A shift in the distribution up would maybe indicate that the exam was too easy and a shift down, too hard. Overall, good scores were within the reach of most students in the class. Confident: 30/100 Central tendency measures: statistics - parameters: 67 Frequency Distributions: 67 Frequency graphs: 59 Graphs of distributions: 100 Mean, Median, and Mode (Define): 83 Mean, Median, and Mode in frequency distributions: 66 Skewness: 88 Time of problem: 0 minutes seconds 11. Your text noted which of the following as a characteristic of the mean? Correct Answer The sum of the results of squaring the difference between each score and the mean is a minimum; The sum of the results of squaring the difference between each score and the mean is zero; You Answered Both a and b; Neither a nor b. There are two important properties of the mean: 1. the mean is a balance point in a distribution, therefore, the sum of the deviations about the mean, S(X -`X), equals 0; and

13 2. if I square each of the deviation scores (to get rid of negative values), the sum of the squared deviation scores, S(X -`X) 2, is a minimum. The properties of the mean can be illustrated by the numbers 1, 3, and 5. The mean of these numbers is 3. If I create deviation scores for each value of X, I get (1-3) or -2; (3-3) or 0; and (5-3) or +2. Summing these deviation scores, I get ((-2) (+2))=0 (1 st property of the mean). If I square and sum each deviation, I get (-2) 2 + (0) 2 + (+2) 2 = 4+0+4=8. If I choose some other number for the mean, other than 3, say for instance 5, squaring and summing the deviations yields (1-5) 2 + (3-5) 2 + (5-5) 2 = = 20. Note that 8 is the lowest value that can be obtained when summing the squared deviations for the data values 1, 3, and 5. Try any other value. This is the second property of the mean. The second property of the mean is expressed in stem a and represents the correct answer to this question. Stem b cannot be correct because squaring the deviations and summing the values will yield 0 only when all scores in the distribution are the same. Confident: 14/100 Mean, Median, and Mode (Define): 83 Time of problem: 0 minutes seconds 12. The mean temperature for January was 30º. In February the mean was 25º and for March the mean was 35º. The overall mean for these months is 30º Correct Answer greater than 30º less than 30º Cannot be determined from the information presented. At first reading, this would appear to be a simple problem. Add and divide by 3 to get an average temperature of 30º. Certainly this would give you a rough estimate of the average temperature, but it would not be accurate estimate. This is a weighted mean problem because the three months are not equal in length. January and March have 31 days but February has only 28 days. This would mean that there are fewer days with the average temperature at 25º and more days with the average temperature at 35º. The weighting then would be on the above 30º side meaning that the average temperature over the three months would be slighly more than 30º.

14 Confident: 74/100 Weighted mean: 64 Time of problem: 0 minutes seconds 13. Two investigators tested their friends for memory span. The first tested five people and found a mean of 6.0. The second tested nine people and found a mean of 7.0. The overall mean for the data gathered is Correct Answer This is a weighted mean problem. One group has a mean of 6 based on 5 people and the other group has a mean of 7 based on 9 people. Because there are unequal numbers in the two groups, I need to proportionally weight the means. To determine the overall mean, you need to key in on the formula for the mean, SX N. For the first group, the SX is equal to 6*5 or 30. In the second group, SX is equal to 7*9 or 63. To find the combined mean, I would add the two SX terms, 30 and 63, and divide by the total number of people, 5+9. The result is or Help: Calculator Confident: 95/100 Weighted mean: 64 Time of problem: 2 minutes seconds 14. Describe the distinguishing characteristics of the histogram, line graph, and frequency polygon. Under what conditions would each be used? Correct answers: quantitative; two variables; line-curve Your Answer: placeholder (Incorrect) a. histogram

15 Graphing technique appropriate for quantitative data. Class intervals are represented on the X-axis, and the frequency of each class interval is represented by the height of the bar. Midpoints of the class intervals are plotted on the X-axis and the width of the bars extends to the exact limits for each class interval. The bars in a histogram, then, touch one another. Histograms tend to be easy to read and convey a sense for how scores in the distribution are gathered. b. line graph Line graphs picture the relationship between two variables. That is, for every value of X there is a corresponding value of Y. Line graphs are very useful for indicating trends, in fact, the most common use is probably with stock market data where transaction averages or stock values are plotted on the Y-axis and time (days, months, quarters, or years) is plotted on the X-axis. c. frequency polygon The frequency polygon is often referred to as a smooth-line curve and is a variation of the histogram. Midpoints of the class intervals on the X-axis are connected by straight lines. The frequency polygon allows researchers to easily compare, on one set of axes, distributions for two or more groups. Histograms comparing groups on the same axes are generally too cluttered. Like the histogram, frequency polygons represent frequencies for values of quantitative variables. Bar graphs, with spaces between bars, are used to display frequencies of the categories of a qualitative variable. Confident: 31/100 Frequency graphs: 59 Time of problem: 0 minutes seconds

16 15. The fact that the middle of a series of items is more difficult to learn that the beginning or the end is known as the series effect; middling effect; bimodal effect; Correct Answer serial position effect. Plotting this phenomenon, known as the serial-position effect, results in a good example of a line graph. In trying to learn a list of items, it tends to be the case that recall of the items is highest for those that occur at the beginning or at the end of the list. These effects are referred to as primacy and recency effects, respectively. That is, items that you reviewed most recently tend to have the highest recall followed by those at the beginning of the list that have been repeated most often in the study process. Items in the middle of the list are the ones that suffer in terms of memory and thus are the ones that need careful attention in the study process. Use of nmenonic devices can really improve interior recall, but the line curve is a good way to illustrate how the serial position effect impacts recall. Confident: 100/100 Frequency graphs: 59 Time of problem: 0 minutes seconds 16. Suppose a frequency distribution with a range of 0 to 100 was positively skewed. The greatest frequency of scores would be expected around Correct Answer 25; 50; 75; any of the above are possible for such a distribution; none of the above are reasonable for such a distribution.

17 Confident: 34/100 Graphs of distributions: 100 Mean, Median, and Mode in frequency distributions: 66 Time of problem: 0 minutes seconds 17. Identify the skew of the two distributions below. a. X f

18 b. X f Correct answers: negatively skewed; negatively skewed Your Answer: negatively skewed; negatively skewed (Incorrect) a. Even without sketching the first distribution, you should be able to see the strong negative skew. Negative skew is present when the tail of the distribution extends or points to the low numbers and that is exactly the case here. As scores on the X-axis go from 0 to 5 the frequencies move from 1 to 1 to 2 to 6 to 8 to 10. Eighteen of the 28 scores are 4's or 5's, that is, the scores tend to be bunched at the upper end of the distribution. This is characteristic of negatively skewed distributions. b. The second distribution is also negatively skewed, but not nearly as pronounced as the first. The tail points somewhat to the lower

19 numbers and bunches some at the higher numbers, but at the highest values, there is a dropoff in scoring and there are no real outlying scores on either end of the distribution. The distribution is not symmetric and it is negatively skewed, but the skew is slight. Confident: 80/100 Skewness: 88 Time of problem: 0 minutes seconds 18. The appropriate statistic for conveying the central tendency of a nominal variable is mean; median; Correct Answer mode; any of the above, but the mean is preferable; any of the above, but the median is preferable; any of the above, but the mode is preferable. The mode is the only appropriate measure of central tendency that can be used with nominal variables. Remember, nominal variables are represented by categories or names that have no inherent order to them. A bar graph is used to summarize the data and the bars are separated by space to indicate that their location along the X-axis is arbitrary. Means and medians, the other measures of central tendency, require that the measurement scale along the X-axis be at least ordered (mode + median) and at best interval or ratio (mode + median + mean). Confident: 22/100 Mean, Median, and Mode (Define): 83

20 Mean, Median, and Mode in frequency distributions: 66 Time of problem: 0 minutes seconds You answered 10 correct out of 15 computer graded questions. Add the number of the written answers (if any were given) that you believe you got correct to the total correct value to determine your score out of 18.

CHAPTER 3 CENTRAL TENDENCY ANALYSES

CHAPTER 3 CENTRAL TENDENCY ANALYSES CHAPTER 3 CENTRAL TENDENCY ANALYSES The next concept in the sequential statistical steps approach is calculating measures of central tendency. Measures of central tendency represent some of the most simple

More information

10-3 Measures of Central Tendency and Variation

10-3 Measures of Central Tendency and Variation 10-3 Measures of Central Tendency and Variation So far, we have discussed some graphical methods of data description. Now, we will investigate how statements of central tendency and variation can be used.

More information

Chapter 3: Central Tendency

Chapter 3: Central Tendency Chapter 3: Central Tendency Central Tendency In general terms, central tendency is a statistical measure that determines a single value that accurately describes the center of the distribution and represents

More information

A frequency distribution is a table used to describe a data set. A frequency table lists intervals or ranges of data values called data classes

A frequency distribution is a table used to describe a data set. A frequency table lists intervals or ranges of data values called data classes A frequency distribution is a table used to describe a data set. A frequency table lists intervals or ranges of data values called data classes together with the number of data values from the set that

More information

We will use the following data sets to illustrate measures of center. DATA SET 1 The following are test scores from a class of 20 students:

We will use the following data sets to illustrate measures of center. DATA SET 1 The following are test scores from a class of 20 students: MODE The mode of the sample is the value of the variable having the greatest frequency. Example: Obtain the mode for Data Set 1 77 For a grouped frequency distribution, the modal class is the class having

More information

Session 1.6 Measures of Central Tendency

Session 1.6 Measures of Central Tendency Session 1.6 Measures of Central Tendency Measures of location (Indices of central tendency) These indices locate the center of the frequency distribution curve. The mode, median, and mean are three indices

More information

Central Tendency. n Measures of Central Tendency: n Mean. n Median. n Mode

Central Tendency. n Measures of Central Tendency: n Mean. n Median. n Mode Central Tendency Central Tendency n A single summary score that best describes the central location of an entire distribution of scores. n Measures of Central Tendency: n Mean n The sum of all scores divided

More information

DESCRIPTIVE STATISTICS. The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses.

DESCRIPTIVE STATISTICS. The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses. DESCRIPTIVE STATISTICS The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses. DESCRIPTIVE VS. INFERENTIAL STATISTICS Descriptive To organize,

More information

Research Variables. Measurement. Scales of Measurement. Chapter 4: Data & the Nature of Measurement

Research Variables. Measurement. Scales of Measurement. Chapter 4: Data & the Nature of Measurement Chapter 4: Data & the Nature of Graziano, Raulin. Research Methods, a Process of Inquiry Presented by Dustin Adams Research Variables Variable Any characteristic that can take more than one form or value.

More information

Sampling, frequency distribution, graphs, measures of central tendency, measures of dispersion

Sampling, frequency distribution, graphs, measures of central tendency, measures of dispersion Statistics Basics Sampling, frequency distribution, graphs, measures of central tendency, measures of dispersion Part 1: Sampling, Frequency Distributions, and Graphs The method of collecting, organizing,

More information

Chapter 3: Data Description Numerical Methods

Chapter 3: Data Description Numerical Methods Chapter 3: Data Description Numerical Methods Learning Objectives Upon successful completion of Chapter 3, you will be able to: Summarize data using measures of central tendency, such as the mean, median,

More information

Content DESCRIPTIVE STATISTICS. Data & Statistic. Statistics. Example: DATA VS. STATISTIC VS. STATISTICS

Content DESCRIPTIVE STATISTICS. Data & Statistic. Statistics. Example: DATA VS. STATISTIC VS. STATISTICS Content DESCRIPTIVE STATISTICS Dr Najib Majdi bin Yaacob MD, MPH, DrPH (Epidemiology) USM Unit of Biostatistics & Research Methodology School of Medical Sciences Universiti Sains Malaysia. Introduction

More information

Chapter 2. Objectives. Tabulate Qualitative Data. Frequency Table. Descriptive Statistics: Organizing, Displaying and Summarizing Data.

Chapter 2. Objectives. Tabulate Qualitative Data. Frequency Table. Descriptive Statistics: Organizing, Displaying and Summarizing Data. Objectives Chapter Descriptive Statistics: Organizing, Displaying and Summarizing Data Student should be able to Organize data Tabulate data into frequency/relative frequency tables Display data graphically

More information

Univariate Descriptive Statistics

Univariate Descriptive Statistics Univariate Descriptive Statistics Displays: pie charts, bar graphs, box plots, histograms, density estimates, dot plots, stemleaf plots, tables, lists. Example: sea urchin sizes Boxplot Histogram Urchin

More information

Chapter 2 - Graphical Summaries of Data

Chapter 2 - Graphical Summaries of Data Chapter 2 - Graphical Summaries of Data Data recorded in the sequence in which they are collected and before they are processed or ranked are called raw data. Raw data is often difficult to make sense

More information

Descriptive Statistics and Measurement Scales

Descriptive Statistics and Measurement Scales Descriptive Statistics 1 Descriptive Statistics and Measurement Scales Descriptive statistics are used to describe the basic features of the data in a study. They provide simple summaries about the sample

More information

Describe what is meant by a placebo Contrast the double-blind procedure with the single-blind procedure Review the structure for organizing a memo

Describe what is meant by a placebo Contrast the double-blind procedure with the single-blind procedure Review the structure for organizing a memo Readings: Ha and Ha Textbook - Chapters 1 8 Appendix D & E (online) Plous - Chapters 10, 11, 12 and 14 Chapter 10: The Representativeness Heuristic Chapter 11: The Availability Heuristic Chapter 12: Probability

More information

Summarizing and Displaying Categorical Data

Summarizing and Displaying Categorical Data Summarizing and Displaying Categorical Data Categorical data can be summarized in a frequency distribution which counts the number of cases, or frequency, that fall into each category, or a relative frequency

More information

FREQUENCY AND PERCENTILES

FREQUENCY AND PERCENTILES FREQUENCY DISTRIBUTIONS AND PERCENTILES New Statistical Notation Frequency (f): the number of times a score occurs N: sample size Simple Frequency Distributions Raw Scores The scores that we have directly

More information

STATS8: Introduction to Biostatistics. Data Exploration. Babak Shahbaba Department of Statistics, UCI

STATS8: Introduction to Biostatistics. Data Exploration. Babak Shahbaba Department of Statistics, UCI STATS8: Introduction to Biostatistics Data Exploration Babak Shahbaba Department of Statistics, UCI Introduction After clearly defining the scientific problem, selecting a set of representative members

More information

Chapter 15 Multiple Choice Questions (The answers are provided after the last question.)

Chapter 15 Multiple Choice Questions (The answers are provided after the last question.) Chapter 15 Multiple Choice Questions (The answers are provided after the last question.) 1. What is the median of the following set of scores? 18, 6, 12, 10, 14? a. 10 b. 14 c. 18 d. 12 2. Approximately

More information

Descriptive Statistics. Frequency Distributions and Their Graphs 2.1. Frequency Distributions. Chapter 2

Descriptive Statistics. Frequency Distributions and Their Graphs 2.1. Frequency Distributions. Chapter 2 Chapter Descriptive Statistics.1 Frequency Distributions and Their Graphs Frequency Distributions A frequency distribution is a table that shows classes or intervals of data with a count of the number

More information

6.4 Normal Distribution

6.4 Normal Distribution Contents 6.4 Normal Distribution....................... 381 6.4.1 Characteristics of the Normal Distribution....... 381 6.4.2 The Standardized Normal Distribution......... 385 6.4.3 Meaning of Areas under

More information

1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number

1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number 1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number A. 3(x - x) B. x 3 x C. 3x - x D. x - 3x 2) Write the following as an algebraic expression

More information

1.5 NUMERICAL REPRESENTATION OF DATA (Sample Statistics)

1.5 NUMERICAL REPRESENTATION OF DATA (Sample Statistics) 1.5 NUMERICAL REPRESENTATION OF DATA (Sample Statistics) As well as displaying data graphically we will often wish to summarise it numerically particularly if we wish to compare two or more data sets.

More information

CHINHOYI UNIVERSITY OF TECHNOLOGY

CHINHOYI UNIVERSITY OF TECHNOLOGY CHINHOYI UNIVERSITY OF TECHNOLOGY SCHOOL OF NATURAL SCIENCES AND MATHEMATICS DEPARTMENT OF MATHEMATICS MEASURES OF CENTRAL TENDENCY AND DISPERSION INTRODUCTION From the previous unit, the Graphical displays

More information

13.2 Measures of Central Tendency

13.2 Measures of Central Tendency 13.2 Measures of Central Tendency Measures of Central Tendency For a given set of numbers, it may be desirable to have a single number to serve as a kind of representative value around which all the numbers

More information

Descriptive Statistics

Descriptive Statistics Y520 Robert S Michael Goal: Learn to calculate indicators and construct graphs that summarize and describe a large quantity of values. Using the textbook readings and other resources listed on the web

More information

AP * Statistics Review. Descriptive Statistics

AP * Statistics Review. Descriptive Statistics AP * Statistics Review Descriptive Statistics Teacher Packet Advanced Placement and AP are registered trademark of the College Entrance Examination Board. The College Board was not involved in the production

More information

Data Analysis: Describing Data - Descriptive Statistics

Data Analysis: Describing Data - Descriptive Statistics WHAT IT IS Return to Table of ontents Descriptive statistics include the numbers, tables, charts, and graphs used to describe, organize, summarize, and present raw data. Descriptive statistics are most

More information

GCSE HIGHER Statistics Key Facts

GCSE HIGHER Statistics Key Facts GCSE HIGHER Statistics Key Facts Collecting Data When writing questions for questionnaires, always ensure that: 1. the question is worded so that it will allow the recipient to give you the information

More information

Chapter 2: Exploring Data with Graphs and Numerical Summaries. Graphical Measures- Graphs are used to describe the shape of a data set.

Chapter 2: Exploring Data with Graphs and Numerical Summaries. Graphical Measures- Graphs are used to describe the shape of a data set. Page 1 of 16 Chapter 2: Exploring Data with Graphs and Numerical Summaries Graphical Measures- Graphs are used to describe the shape of a data set. Section 1: Types of Variables In general, variable can

More information

TYPES OF DATA TYPES OF VARIABLES

TYPES OF DATA TYPES OF VARIABLES TYPES OF DATA Univariate data Examines the distribution features of one variable. Bivariate data Explores the relationship between two variables. Univariate and bivariate analysis will be revised separately.

More information

F. Farrokhyar, MPhil, PhD, PDoc

F. Farrokhyar, MPhil, PhD, PDoc Learning objectives Descriptive Statistics F. Farrokhyar, MPhil, PhD, PDoc To recognize different types of variables To learn how to appropriately explore your data How to display data using graphs How

More information

Chapter 2 Summarizing and Graphing Data

Chapter 2 Summarizing and Graphing Data Chapter 2 Summarizing and Graphing Data 2-1 Review and Preview 2-2 Frequency Distributions 2-3 Histograms 2-4 Graphs that Enlighten and Graphs that Deceive Preview Characteristics of Data 1. Center: A

More information

Models for Discrete Variables

Models for Discrete Variables Probability Models for Discrete Variables Our study of probability begins much as any data analysis does: What is the distribution of the data? Histograms, boxplots, percentiles, means, standard deviations

More information

Lecture I. Definition 1. Statistics is the science of collecting, organizing, summarizing and analyzing the information in order to draw conclusions.

Lecture I. Definition 1. Statistics is the science of collecting, organizing, summarizing and analyzing the information in order to draw conclusions. Lecture 1 1 Lecture I Definition 1. Statistics is the science of collecting, organizing, summarizing and analyzing the information in order to draw conclusions. It is a process consisting of 3 parts. Lecture

More information

Graphing Data Presentation of Data in Visual Forms

Graphing Data Presentation of Data in Visual Forms Graphing Data Presentation of Data in Visual Forms Purpose of Graphing Data Audience Appeal Provides a visually appealing and succinct representation of data and summary statistics Provides a visually

More information

Table 2-1. Sucrose concentration (% fresh wt.) of 100 sugar beet roots. Beet No. % Sucrose. Beet No.

Table 2-1. Sucrose concentration (% fresh wt.) of 100 sugar beet roots. Beet No. % Sucrose. Beet No. Chapter 2. DATA EXPLORATION AND SUMMARIZATION 2.1 Frequency Distributions Commonly, people refer to a population as the number of individuals in a city or county, for example, all the people in California.

More information

( ) ( ) Central Tendency. Central Tendency

( ) ( ) Central Tendency. Central Tendency 1 Central Tendency CENTRAL TENDENCY: A statistical measure that identifies a single score that is most typical or representative of the entire group Usually, a value that reflects the middle of the distribution

More information

The right edge of the box is the third quartile, Q 3, which is the median of the data values above the median. Maximum Median

The right edge of the box is the third quartile, Q 3, which is the median of the data values above the median. Maximum Median CONDENSED LESSON 2.1 Box Plots In this lesson you will create and interpret box plots for sets of data use the interquartile range (IQR) to identify potential outliers and graph them on a modified box

More information

Chapter 7 What to do when you have the data

Chapter 7 What to do when you have the data Chapter 7 What to do when you have the data We saw in the previous chapters how to collect data. We will spend the rest of this course looking at how to analyse the data that we have collected. Stem and

More information

Chapter 3 Central Tendency

Chapter 3 Central Tendency Chapter 3 Central Tendency PowerPoint Lecture Slides Essentials of Statistics for the Behavioral Sciences Seventh Edition by Frederick J Gravetter and Larry B. Wallnau Learning Outcomes 1 2 3 4 5 6 Understand

More information

Unit 21 Student s t Distribution in Hypotheses Testing

Unit 21 Student s t Distribution in Hypotheses Testing Unit 21 Student s t Distribution in Hypotheses Testing Objectives: To understand the difference between the standard normal distribution and the Student's t distributions To understand the difference between

More information

In this chapter, you will learn to use descriptive statistics to organize, summarize, analyze, and interpret data for contract pricing.

In this chapter, you will learn to use descriptive statistics to organize, summarize, analyze, and interpret data for contract pricing. 3.0 - Chapter Introduction In this chapter, you will learn to use descriptive statistics to organize, summarize, analyze, and interpret data for contract pricing. Categories of Statistics. Statistics is

More information

Introduction to Descriptive Statistics

Introduction to Descriptive Statistics Mathematics Learning Centre Introduction to Descriptive Statistics Jackie Nicholas c 1999 University of Sydney Acknowledgements Parts of this booklet were previously published in a booklet of the same

More information

Exercise 1.12 (Pg. 22-23)

Exercise 1.12 (Pg. 22-23) Individuals: The objects that are described by a set of data. They may be people, animals, things, etc. (Also referred to as Cases or Records) Variables: The characteristics recorded about each individual.

More information

III. GRAPHICAL METHODS

III. GRAPHICAL METHODS Pie Charts and Bar Charts: III. GRAPHICAL METHODS Pie charts and bar charts are used for depicting frequencies or relative frequencies. We compare examples of each using the same data. Sources: AT&T (1961)

More information

Frequency Distributions

Frequency Distributions Descriptive Statistics Dr. Tom Pierce Department of Psychology Radford University Descriptive statistics comprise a collection of techniques for better understanding what the people in a group look like

More information

Chapter 1: Looking at Data Section 1.1: Displaying Distributions with Graphs

Chapter 1: Looking at Data Section 1.1: Displaying Distributions with Graphs Types of Variables Chapter 1: Looking at Data Section 1.1: Displaying Distributions with Graphs Quantitative (numerical)variables: take numerical values for which arithmetic operations make sense (addition/averaging)

More information

Statistics Revision Sheet Question 6 of Paper 2

Statistics Revision Sheet Question 6 of Paper 2 Statistics Revision Sheet Question 6 of Paper The Statistics question is concerned mainly with the following terms. The Mean and the Median and are two ways of measuring the average. sumof values no. of

More information

Statistical Foundations: Measures of Location and Central Tendency and Summation and Expectation

Statistical Foundations: Measures of Location and Central Tendency and Summation and Expectation Statistical Foundations: and Central Tendency and and Lecture 4 September 5, 2006 Psychology 790 Lecture #4-9/05/2006 Slide 1 of 26 Today s Lecture Today s Lecture Where this Fits central tendency/location

More information

MCQ S OF MEASURES OF CENTRAL TENDENCY

MCQ S OF MEASURES OF CENTRAL TENDENCY MCQ S OF MEASURES OF CENTRAL TENDENCY MCQ No 3.1 Any measure indicating the centre of a set of data, arranged in an increasing or decreasing order of magnitude, is called a measure of: (a) Skewness (b)

More information

Lesson 4 Measures of Central Tendency

Lesson 4 Measures of Central Tendency Outline Measures of a distribution s shape -modality and skewness -the normal distribution Measures of central tendency -mean, median, and mode Skewness and Central Tendency Lesson 4 Measures of Central

More information

Statistics Summary (prepared by Xuan (Tappy) He)

Statistics Summary (prepared by Xuan (Tappy) He) Statistics Summary (prepared by Xuan (Tappy) He) Statistics is the practice of collecting and analyzing data. The analysis of statistics is important for decision making in events where there are uncertainties.

More information

Data Mining Part 2. Data Understanding and Preparation 2.1 Data Understanding Spring 2010

Data Mining Part 2. Data Understanding and Preparation 2.1 Data Understanding Spring 2010 Data Mining Part 2. and Preparation 2.1 Spring 2010 Instructor: Dr. Masoud Yaghini Introduction Outline Introduction Measuring the Central Tendency Measuring the Dispersion of Data Graphic Displays References

More information

Graphical and Tabular. Summarization of Data OPRE 6301

Graphical and Tabular. Summarization of Data OPRE 6301 Graphical and Tabular Summarization of Data OPRE 6301 Introduction and Re-cap... Descriptive statistics involves arranging, summarizing, and presenting a set of data in such a way that useful information

More information

Measures of Central Tendency. There are different types of averages, each has its own advantages and disadvantages.

Measures of Central Tendency. There are different types of averages, each has its own advantages and disadvantages. Measures of Central Tendency According to Prof Bowley Measures of central tendency (averages) are statistical constants which enable us to comprehend in a single effort the significance of the whole. The

More information

Numerical Measures of Central Tendency

Numerical Measures of Central Tendency Numerical Measures of Central Tendency Often, it is useful to have special numbers which summarize characteristics of a data set These numbers are called descriptive statistics or summary statistics. A

More information

CHAPTER 1 The Item Characteristic Curve

CHAPTER 1 The Item Characteristic Curve CHAPTER 1 The Item Characteristic Curve Chapter 1: The Item Characteristic Curve 5 CHAPTER 1 The Item Characteristic Curve In many educational and psychological measurement situations, there is an underlying

More information

Introduction to Statistics for Computer Science Projects

Introduction to Statistics for Computer Science Projects Introduction Introduction to Statistics for Computer Science Projects Peter Coxhead Whole modules are devoted to statistics and related topics in many degree programmes, so in this short session all I

More information

Introductory Statistics Notes

Introductory Statistics Notes Introductory Statistics Notes Jamie DeCoster Department of Psychology University of Alabama 348 Gordon Palmer Hall Box 870348 Tuscaloosa, AL 35487-0348 Phone: (205) 348-4431 Fax: (205) 348-8648 August

More information

Exploratory data analysis (Chapter 2) Fall 2011

Exploratory data analysis (Chapter 2) Fall 2011 Exploratory data analysis (Chapter 2) Fall 2011 Data Examples Example 1: Survey Data 1 Data collected from a Stat 371 class in Fall 2005 2 They answered questions about their: gender, major, year in school,

More information

Numerical Summarization of Data OPRE 6301

Numerical Summarization of Data OPRE 6301 Numerical Summarization of Data OPRE 6301 Motivation... In the previous session, we used graphical techniques to describe data. For example: While this histogram provides useful insight, other interesting

More information

909 responses responded via telephone survey in U.S. Results were shown by political affiliations (show graph on the board)

909 responses responded via telephone survey in U.S. Results were shown by political affiliations (show graph on the board) 1 2-1 Overview Chapter 2: Learn the methods of organizing, summarizing, and graphing sets of data, ultimately, to understand the data characteristics: Center, Variation, Distribution, Outliers, Time. (Computer

More information

Summarizing Your Data

Summarizing Your Data Summarizing Your Data Key Info So now you have collected your raw data, and you have results from multiple trials of your experiment. How do you go from piles of raw data to summaries that can help you

More information

Chapter 2: Frequency Distributions and Graphs

Chapter 2: Frequency Distributions and Graphs Chapter 2: Frequency Distributions and Graphs Learning Objectives Upon completion of Chapter 2, you will be able to: Organize the data into a table or chart (called a frequency distribution) Construct

More information

Homework 8 Solutions

Homework 8 Solutions Homework 8 Solutions Chapter 5D Review Questions. 6. What is an exponential scale? When is an exponential scale useful? An exponential scale is one in which each unit corresponds to a power of. In general,

More information

CALCULATIONS & STATISTICS

CALCULATIONS & STATISTICS CALCULATIONS & STATISTICS CALCULATION OF SCORES Conversion of 1-5 scale to 0-100 scores When you look at your report, you will notice that the scores are reported on a 0-100 scale, even though respondents

More information

Frequency distributions, central tendency & variability. Displaying data

Frequency distributions, central tendency & variability. Displaying data Frequency distributions, central tendency & variability Displaying data Software SPSS Excel/Numbers/Google sheets Social Science Statistics website (socscistatistics.com) Creating and SPSS file Open the

More information

Statistical Concepts and Market Return

Statistical Concepts and Market Return Statistical Concepts and Market Return 2014 Level I Quantitative Methods IFT Notes for the CFA exam Contents 1. Introduction... 2 2. Some Fundamental Concepts... 2 3. Summarizing Data Using Frequency Distributions...

More information

Chapter 1: Exploring Data

Chapter 1: Exploring Data Chapter 1: Exploring Data Chapter 1 Review 1. As part of survey of college students a researcher is interested in the variable class standing. She records a 1 if the student is a freshman, a 2 if the student

More information

4. Describing Bivariate Data

4. Describing Bivariate Data 4. Describing Bivariate Data A. Introduction to Bivariate Data B. Values of the Pearson Correlation C. Properties of Pearson's r D. Computing Pearson's r E. Variance Sum Law II F. Exercises A dataset with

More information

Chapter 2 Statistical Foundations: Descriptive Statistics

Chapter 2 Statistical Foundations: Descriptive Statistics Chapter 2 Statistical Foundations: Descriptive Statistics 20 Chapter 2 Statistical Foundations: Descriptive Statistics Presented in this chapter is a discussion of the types of data and the use of frequency

More information

A Picture Really Is Worth a Thousand Words

A Picture Really Is Worth a Thousand Words 4 A Picture Really Is Worth a Thousand Words Difficulty Scale (pretty easy, but not a cinch) What you ll learn about in this chapter Why a picture is really worth a thousand words How to create a histogram

More information

Section 3.1 Measures of Central Tendency: Mode, Median, and Mean

Section 3.1 Measures of Central Tendency: Mode, Median, and Mean Section 3.1 Measures of Central Tendency: Mode, Median, and Mean One number can be used to describe the entire sample or population. Such a number is called an average. There are many ways to compute averages,

More information

STATISTICS FOR PSYCH MATH REVIEW GUIDE

STATISTICS FOR PSYCH MATH REVIEW GUIDE STATISTICS FOR PSYCH MATH REVIEW GUIDE ORDER OF OPERATIONS Although remembering the order of operations as BEDMAS may seem simple, it is definitely worth reviewing in a new context such as statistics formulae.

More information

Homework 3. Part 1. Name: Score: / null

Homework 3. Part 1. Name: Score: / null Name: Score: / Homework 3 Part 1 null 1 For the following sample of scores, the standard deviation is. Scores: 7, 2, 4, 6, 4, 7, 3, 7 Answer Key: 2 2 For any set of data, the sum of the deviation scores

More information

STA-201-TE. 5. Measures of relationship: correlation (5%) Correlation coefficient; Pearson r; correlation and causation; proportion of common variance

STA-201-TE. 5. Measures of relationship: correlation (5%) Correlation coefficient; Pearson r; correlation and causation; proportion of common variance Principles of Statistics STA-201-TE This TECEP is an introduction to descriptive and inferential statistics. Topics include: measures of central tendency, variability, correlation, regression, hypothesis

More information

Research Methods 1 Handouts, Graham Hole,COGS - version 1.0, September 2000: Page 1:

Research Methods 1 Handouts, Graham Hole,COGS - version 1.0, September 2000: Page 1: Research Methods 1 Handouts, Graham Hole,COGS - version 1.0, September 2000: Page 1: THE NORMAL CURVE AND "Z" SCORES: The Normal Curve: The "Normal" curve is a mathematical abstraction which conveniently

More information

Methods for Describing Data Sets

Methods for Describing Data Sets 1 Methods for Describing Data Sets.1 Describing Data Graphically In this section, we will work on organizing data into a special table called a frequency table. First, we will classify the data into categories.

More information

Introduction to Statistics for Psychology. Quantitative Methods for Human Sciences

Introduction to Statistics for Psychology. Quantitative Methods for Human Sciences Introduction to Statistics for Psychology and Quantitative Methods for Human Sciences Jonathan Marchini Course Information There is website devoted to the course at http://www.stats.ox.ac.uk/ marchini/phs.html

More information

MEASURES OF CENTRAL TENDENCY

MEASURES OF CENTRAL TENDENCY CHAPTER 5 MEASURES OF CENTRAL TENDENCY OBJECTIVES After completing this chapter, you should be able to define, discuss, and compute the most commonly encountered measures of central tendency the mean,

More information

! x sum of the entries

! x sum of the entries 3.1 Measures of Central Tendency (Page 1 of 16) 3.1 Measures of Central Tendency Mean, Median and Mode! x sum of the entries a. mean, x = = n number of entries Example 1 Find the mean of 26, 18, 12, 31,

More information

GCSE Statistics Revision notes

GCSE Statistics Revision notes GCSE Statistics Revision notes Collecting data Sample This is when data is collected from part of the population. There are different methods for sampling Random sampling, Stratified sampling, Systematic

More information

Measures of Center Section 3-2 Definitions Mean (Arithmetic Mean)

Measures of Center Section 3-2 Definitions Mean (Arithmetic Mean) Measures of Center Section 3-1 Mean (Arithmetic Mean) AVERAGE the number obtained by adding the values and dividing the total by the number of values 1 Mean as a Balance Point 3 Mean as a Balance Point

More information

Research Methods 1 Handouts, Graham Hole,COGS - version 1.0, September 2000: Page 1:

Research Methods 1 Handouts, Graham Hole,COGS - version 1.0, September 2000: Page 1: Research Methods 1 Handouts, Graham Hole,COGS - version 1.0, September 000: Page 1: DESCRIPTIVE STATISTICS - FREQUENCY DISTRIBUTIONS AND AVERAGES: Inferential and Descriptive Statistics: There are four

More information

Describing Data. We find the position of the central observation using the formula: position number =

Describing Data. We find the position of the central observation using the formula: position number = HOSP 1207 (Business Stats) Learning Centre Describing Data This worksheet focuses on describing data through measuring its central tendency and variability. These measurements will give us an idea of what

More information

2 Describing, Exploring, and

2 Describing, Exploring, and 2 Describing, Exploring, and Comparing Data This chapter introduces the graphical plotting and summary statistics capabilities of the TI- 83 Plus. First row keys like \ R (67$73/276 are used to obtain

More information

How to interpret scientific & statistical graphs

How to interpret scientific & statistical graphs How to interpret scientific & statistical graphs Theresa A Scott, MS Department of Biostatistics theresa.scott@vanderbilt.edu http://biostat.mc.vanderbilt.edu/theresascott 1 A brief introduction Graphics:

More information

x Measures of Central Tendency for Ungrouped Data Chapter 3 Numerical Descriptive Measures Example 3-1 Example 3-1: Solution

x Measures of Central Tendency for Ungrouped Data Chapter 3 Numerical Descriptive Measures Example 3-1 Example 3-1: Solution Chapter 3 umerical Descriptive Measures 3.1 Measures of Central Tendency for Ungrouped Data 3. Measures of Dispersion for Ungrouped Data 3.3 Mean, Variance, and Standard Deviation for Grouped Data 3.4

More information

Midterm Review Problems

Midterm Review Problems Midterm Review Problems October 19, 2013 1. Consider the following research title: Cooperation among nursery school children under two types of instruction. In this study, what is the independent variable?

More information

HISTOGRAMS, CUMULATIVE FREQUENCY AND BOX PLOTS

HISTOGRAMS, CUMULATIVE FREQUENCY AND BOX PLOTS Mathematics Revision Guides Histograms, Cumulative Frequency and Box Plots Page 1 of 25 M.K. HOME TUITION Mathematics Revision Guides Level: GCSE Higher Tier HISTOGRAMS, CUMULATIVE FREQUENCY AND BOX PLOTS

More information

Introduction; Descriptive & Univariate Statistics

Introduction; Descriptive & Univariate Statistics Introduction; Descriptive & Univariate Statistics I. KEY COCEPTS A. Population. Definitions:. The entire set of members in a group. EXAMPLES: All U.S. citizens; all otre Dame Students. 2. All values of

More information

Descriptive statistics Statistical inference statistical inference, statistical induction and inferential statistics

Descriptive statistics Statistical inference statistical inference, statistical induction and inferential statistics Descriptive statistics is the discipline of quantitatively describing the main features of a collection of data. Descriptive statistics are distinguished from inferential statistics (or inductive statistics),

More information

Descriptive Statistics. Purpose of descriptive statistics Frequency distributions Measures of central tendency Measures of dispersion

Descriptive Statistics. Purpose of descriptive statistics Frequency distributions Measures of central tendency Measures of dispersion Descriptive Statistics Purpose of descriptive statistics Frequency distributions Measures of central tendency Measures of dispersion Statistics as a Tool for LIS Research Importance of statistics in research

More information

EXAM #1 (Example) Instructor: Ela Jackiewicz. Relax and good luck!

EXAM #1 (Example) Instructor: Ela Jackiewicz. Relax and good luck! STP 231 EXAM #1 (Example) Instructor: Ela Jackiewicz Honor Statement: I have neither given nor received information regarding this exam, and I will not do so until all exams have been graded and returned.

More information

Inferential Statistics

Inferential Statistics Inferential Statistics Sampling and the normal distribution Z-scores Confidence levels and intervals Hypothesis testing Commonly used statistical methods Inferential Statistics Descriptive statistics are

More information

Center: Finding the Median. Median. Spread: Home on the Range. Center: Finding the Median (cont.)

Center: Finding the Median. Median. Spread: Home on the Range. Center: Finding the Median (cont.) Center: Finding the Median When we think of a typical value, we usually look for the center of the distribution. For a unimodal, symmetric distribution, it s easy to find the center it s just the center

More information

Mathematics. Probability and Statistics Curriculum Guide. Revised 2010

Mathematics. Probability and Statistics Curriculum Guide. Revised 2010 Mathematics Probability and Statistics Curriculum Guide Revised 2010 This page is intentionally left blank. Introduction The Mathematics Curriculum Guide serves as a guide for teachers when planning instruction

More information