The GoodnessofFit Test


 Kerrie Lane
 2 years ago
 Views:
Transcription
1 on the Lecture 49 Section 14.3 HampdenSydney College Tue, Apr 21, 2009
2 Outline 1 on the 2 3 on the 4 5
3 Hypotheses on the (Steps 1 and 2) (1) H 0 : H 1 : H 0 is false. (2) α = p 1 = 0.24 p 2 = 0.20 p 3 = 0.16 p 4 = 0.14 p 5 = 0.13 p 6 = 0.13.
4 Hypotheses on the (Step 3) (3) χ 2 = (O E) 2. E all cells (4) χ 2 =
5 Degrees of Freedom on the Definition (χ 2 degrees of freedom) In a goodnessoffit test, the number of degrees of freedom is one less than the number of cells. χ 2 distribution has an associated degrees of freedom, just like the t distribution. Each χ 2 distribution has a slightly different shape, depending on the number of degrees of freedom. For example, we let χ 2 5 denote the chisquare statistic with 5 degrees of freedom.
6 Degrees of Freedom on the Graph of χ
7 Degrees of Freedom on the Graph of χ
8 Degrees of Freedom on the Graph of χ
9 Degrees of Freedom on the Graph of χ
10 Degrees of Freedom on the Graph of χ
11 Degrees of Freedom on the Graph of χ
12 Degrees of Freedom on the Graph of χ
13 Degrees of Freedom on the Graph of χ
14 Degrees of Freedom on the Graph of χ
15 Degrees of Freedom on the Graph of χ
16 Degrees of Freedom on the Graphs of χ 2 1, χ2 2,..., χ
17 Properties of χ 2 on the chisquare distribution with df degrees of freedom has the following properties. χ 2 0. It is unimodal. It is skewed right (not symmetric!) µ χ 2 = df. σ χ 2 = 2df. If df is large, then χ 2 df is approximately normal with mean df and standard deviation 2df.
18 vs. Normal on the graph of χ 2 8 vs. N(8, 4)
19 vs. Normal on the graph of χ 2 32 vs. N(32, 8)
20 vs. Normal on the graph of χ vs. N(128, 16)
21 vs. Normal on the graph of χ vs. N(512, 32)
22  Probabilities on the Chisquare Probabilities Press 2nd DISTR. Select χ 2 cdf. Enter the lower endpoint, the upper endpoint, and the degrees of freedom. Press ENTER. probability appears in the display.
23  Probabilities on the Practice Find P(χ 2 3 > 6) with df = 3. Find P(20 < χ 2 25 < 30) with df = 25. Find P(χ 2 6 < 10) with df = 6. Find the probability that χ is within one standard deviation of its mean.
24 on the In our example, we found χ 2 = re are 6 categories (colors), so there are 5 degrees of freedom.
25 on the (Steps 5, 6, and 7) (5) pvalue = χ 2 cdf(9.7581,e99,5) = (6) Accept H 0. (7) colors fit the distribution given by the Mars Candy Company.
26 on the ( ) (1) H 0 : p 1 = 0.24, p 2 = 0.20, p 3 = 0.16, p 4 = 0.14, p 5 = 0.13, p 6 = 0.13 H 1 : H 0 is false. (2) α = (O E) 2 E. Color Blue Orange Green Yellow Brown Red (3) χ 2 = all cells (4) Observed (Expected) (27.36) (22.80) (18.24) (15.96) (14.82) (14.82) χ 2 = (5) pvalue = χ 2 cdf(9.7581,e99,5) = (6) Accept H 0. (7) color distribution in plain M&Ms is what the Mars Candy Company advertises it is.
27 on the on the Be careful when using the! re is a function called χ 2 , but it does not perform the goodnessoffit test. Some TI84s have a GOF function. GOF function does perform the goodnessoffit test.
28 on the on the fit test Put the observed counts in list L 1. Put the hypothetical proportions in list L 2. Multiply L 2 by the sample size and store as L 2. se are the expected counts. Calculate (L 1 L 2 ) 2 /L 2. Go to LIST > MATH and select sum (item #5). Enter Ans and press ENTER. value of χ 2 appears. n use χ 2 cdf to find the pvalue.
29  Male vs. Female Births on the ( fit test) Suppose we observe 1000 births and find that 520 are male and 480 are female. Does this indicate that male births and female births are not equally likely?
30  Male vs. Female Births on the ( fit test) (1) Let p 1 = proportion of male births. Let p 2 = proportion of female births. H 0 : p 1 = 0.50, p 2 = 0.50 H 1 : H 0 is not true. (2) α = (3) test statistic is χ 2 = all cells (O E) 2. E
31  Male vs. Female Births on the ( fit test) (4) We have the table Calculate Male Female Observed (Expected) (500) (500) χ 2 = ( ) = = 1.6 ( )2 500
32  Male vs. Female Births on the ( fit test) (5) pvalue is pvalue = χ 2 cdf(1.6,e99,1) = (6) Accept H 0. (7) proportion of male births is 50%.
33  Male vs. Female Births on the Perform the above test as a twotailed oneproportion z test. That is, let the alternative hypothesis be What is the pvalue? H 1 : p 1 p 2. What is the value of the test statistic z? Square that number. What do you get? See Univariate Relationships.
34 on the Homework Read Sections , pages Let s Do It! 14.2, Exercises 611, 14, 15, page 935.
Lecture 42 Section 14.3. Tue, Apr 8, 2008
the Lecture 42 Section 14.3 HampdenSydney 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 informationThe GoodnessofFit Test
The GoodnessofFit Test Lecture 49 Section 14.3 Robb T. Koether HampdenSydney College Tue, Apr 24, 2012 Robb T. Koether (HampdenSydney College) The GoodnessofFit Test Tue, Apr 24, 2012 1 / 15 Outline
More informationHypothesis Testing for a Proportion
Math 122 Intro to Stats Chapter 6 Semester II, 201516 Inference for Categorical Data Hypothesis Testing for a Proportion In a survey, 1864 out of 2246 randomly selected adults said texting while driving
More informationCalculating PValues. Parkland College. Isela Guerra Parkland College. Recommended Citation
Parkland College A with Honors Projects Honors Program 2014 Calculating PValues Isela Guerra Parkland College Recommended Citation Guerra, Isela, "Calculating PValues" (2014). A with Honors Projects.
More informationUnit 29 ChiSquare GoodnessofFit Test
Unit 29 ChiSquare GoodnessofFit Test Objectives: To perform the chisquare hypothesis test concerning proportions corresponding to more than two categories of a qualitative variable To perform the Bonferroni
More informationChapter 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 informationIs it statistically significant? The chisquare test
UAS Conference Series 2013/14 Is it statistically significant? The chisquare test Dr Gosia Turner Student Data Management and Analysis 14 September 2010 Page 1 Why chisquare? Tests whether two categorical
More informationMATH 10: Elementary Statistics and Probability Chapter 11: The ChiSquare Distribution
MATH 10: Elementary Statistics and Probability Chapter 11: The ChiSquare Distribution Tony Pourmohamad Department of Mathematics De Anza College Spring 2015 Objectives By the end of this set of slides,
More informationLecture 8. Confidence intervals and the central limit theorem
Lecture 8. Confidence intervals and the central limit theorem Mathematical Statistics and Discrete Mathematics November 25th, 2015 1 / 15 Central limit theorem Let X 1, X 2,... X n be a random sample of
More informationClass 19: Two Way Tables, Conditional Distributions, ChiSquare (Text: Sections 2.5; 9.1)
Spring 204 Class 9: Two Way Tables, Conditional Distributions, ChiSquare (Text: Sections 2.5; 9.) Big Picture: More than Two Samples In Chapter 7: We looked at quantitative variables and compared the
More informationChiSquare Test. Contingency Tables. Contingency Tables. ChiSquare Test for Independence. ChiSquare Tests for GoodnessofFit
ChiSquare Tests 15 Chapter ChiSquare Test for Independence ChiSquare Tests for Goodness Uniform Goodness Poisson Goodness Goodness Test ECDF Tests (Optional) McGrawHill/Irwin Copyright 2009 by The
More informationChi Square for Contingency Tables
2 x 2 Case Chi Square for Contingency Tables A test for p 1 = p 2 We have learned a confidence interval for p 1 p 2, the difference in the population proportions. We want a hypothesis testing procedure
More informationTI89, TI92, Voyage 200 List Editor Basics
TI89, TI92, Voyage 200 List Editor Basics What follows is a brief description of how to enter, retrieve, and manipulate data in the List Editor of the TI89, TI92, and Voyage 200. (The instructions
More information1. 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 informationNovember 08, 2010. 155S8.6_3 Testing a Claim About a Standard Deviation or Variance
Chapter 8 Hypothesis Testing 8 1 Review and Preview 8 2 Basics of Hypothesis Testing 8 3 Testing a Claim about a Proportion 8 4 Testing a Claim About a Mean: σ Known 8 5 Testing a Claim About a Mean: σ
More informationChapter 8 Introduction to Hypothesis Testing
Chapter 8 Student Lecture Notes 81 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 informationNull 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 informationChi Square Goodness of Fit & Twoway Tables (Create) MATH NSPIRED
Overview In this activity, you will look at a setting that involves categorical data and determine which is the appropriate chisquare test to use. You will input data into a list or matrix and conduct
More information12.5: CHISQUARE GOODNESS OF FIT TESTS
125: ChiSquare Goodness of Fit Tests CD121 125: CHISQUARE GOODNESS OF FIT TESTS In this section, the χ 2 distribution is used for testing the goodness of fit of a set of data to a specific probability
More informationChapter 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 information1. 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 1propZint 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 informationBiotechnology Explorer
Biotechnology Explorer C. elegans Behavior Kit Chi Square Analysis Supplement explorer.biorad.com Catalog #1665120EDU This kit contains temperaturesensitive reagents. Open immediately and see individual
More informationCHAPTER 11 CHISQUARE: NONPARAMETRIC COMPARISONS OF FREQUENCY
CHAPTER 11 CHISQUARE: NONPARAMETRIC COMPARISONS OF FREQUENCY The hypothesis testing statistics detailed thus far in this text have all been designed to allow comparison of the means of two or more samples
More informationBasic Statistics Self Assessment Test
Basic Statistics Self Assessment Test Professor Douglas H. Jones PAGE 1 A sodadispensing machine fills 12ounce cans of soda using a normal distribution with a mean of 12.1 ounces and a standard deviation
More informationChapter 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 information13.2 The Chi Square Test for Homogeneity of Populations The setting: Used to compare distribution of proportions in two or more populations.
13.2 The Chi Square Test for Homogeneity of Populations The setting: Used to compare distribution of proportions in two or more populations. Data is organized in a two way table Explanatory variable (Treatments)
More information7 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 information3.4 Statistical inference for 2 populations based on two samples
3.4 Statistical inference for 2 populations based on two samples Tests for a difference between two population means The first sample will be denoted as X 1, X 2,..., X m. The second sample will be denoted
More informationSampling 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 informationAn Introduction to Statistics Course (ECOE 1302) Spring Semester 2011 Chapter 10 TWOSAMPLE 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 TWOSAMPLE TESTS Practice
More informationIntroduction to Hypothesis Testing. Point estimation and confidence intervals are useful statistical inference procedures.
Introduction to Hypothesis Testing Point estimation and confidence intervals are useful statistical inference procedures. Another type of inference is used frequently used concerns tests of hypotheses.
More informationSolutions to Homework 10 Statistics 302 Professor Larget
s to Homework 10 Statistics 302 Professor Larget Textbook Exercises 7.14 RockPaperScissors (Graded for Accurateness) In Data 6.1 on page 367 we see a table, reproduced in the table below that shows the
More informationThis can dilute the significance of a departure from the null hypothesis. We can focus the test on departures of a particular form.
OneDegreeofFreedom Tests Test for group occasion interactions has (number of groups 1) number of occasions 1) degrees of freedom. This can dilute the significance of a departure from the null hypothesis.
More informationFinal 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 information9.1 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 informationMind on Statistics. Chapter 15
Mind on Statistics Chapter 15 Section 15.1 1. A student survey was done to study the relationship between class standing (freshman, sophomore, junior, or senior) and major subject (English, Biology, French,
More informationSection 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 informationHow 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 informationChapter 11. Chapter 11 Overview. Chapter 11 Objectives 11/24/2015. Other ChiSquare Tests
11/4/015 Chapter 11 Overview Chapter 11 Introduction 111 Test for Goodness of Fit 11 Tests Using Contingency Tables Other ChiSquare Tests McGrawHill, Bluman, 7th ed., Chapter 11 1 Bluman, Chapter 11
More informationHYPOTHESIS 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 informationCATEGORICAL DATA ChiSquare Tests for Univariate Data
CATEGORICAL DATA ChiSquare Tests For Univariate Data 1 CATEGORICAL DATA ChiSquare Tests for Univariate Data Recall that a categorical variable is one in which the possible values are categories or groupings.
More informationThe ChiSquare Test. STAT E50 Introduction to Statistics
STAT 50 Introduction to Statistics The ChiSquare Test The Chisquare test is a nonparametric test that is used to compare experimental results with theoretical models. That is, we will be comparing observed
More informationChapter 8 Hypothesis Testing Chapter 8 Hypothesis Testing 81 Overview 82 Basics of Hypothesis Testing
Chapter 8 Hypothesis Testing 1 Chapter 8 Hypothesis Testing 81 Overview 82 Basics of Hypothesis Testing 83 Testing a Claim About a Proportion 85 Testing a Claim About a Mean: s Not Known 86 Testing
More informationDifference 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 informationIndependent t Test (Comparing Two Means)
Independent t Test (Comparing Two Means) The objectives of this lesson are to learn: the definition/purpose of independent ttest when to use the independent ttest the use of SPSS to complete an independent
More informationUnit 31 A Hypothesis Test about Correlation and Slope in a Simple Linear Regression
Unit 31 A Hypothesis Test about Correlation and Slope in a Simple Linear Regression Objectives: To perform a hypothesis test concerning the slope of a least squares line To recognize that testing for a
More information1. Comparing Two Means: Dependent Samples
1. Comparing Two Means: ependent Samples In the preceding lectures we've considered how to test a difference of two means for independent samples. Now we look at how to do the same thing with dependent
More informationDistribution is a χ 2 value on the χ 2 axis that is the vertical boundary separating the area in one tail of the graph from the remaining area.
Section 8 4B Finding Critical Values for a Chi Square Distribution The entire area that is to be used in the tail(s) denoted by. The entire area denoted by can placed in the left tail and produce a Critical
More information93.4 Likelihood ratio test. NeymanPearson lemma
93.4 Likelihood ratio test NeymanPearson lemma 91 Hypothesis Testing 91.1 Statistical Hypotheses Statistical hypothesis testing and confidence interval estimation of parameters are the fundamental
More informationSolutions to Homework 6 Statistics 302 Professor Larget
s to Homework 6 Statistics 302 Professor Larget Textbook Exercises 5.29 (Graded for Completeness) What Proportion Have College Degrees? According to the US Census Bureau, about 27.5% of US adults over
More informationLecture 13  χ 2 Tests
Lecture 13  χ 2 Tests Statistics 102 Colin Rundel March 6, 2013 Weldon s dice Weldon s dice Walter Frank Raphael Weldon (18601906), was an English evolutionary biologist and a founder of biometry. He
More informationVariables Control Charts
MINITAB ASSISTANT WHITE PAPER This paper explains the research conducted by Minitab statisticians to develop the methods and data checks used in the Assistant in Minitab 17 Statistical Software. Variables
More informationANOVA  Analysis of Variance
ANOVA  Analysis of Variance ANOVA  Analysis of Variance Extends independentsamples t test Compares the means of groups of independent observations Don t be fooled by the name. ANOVA does not compare
More informationCHISQUARE: TESTING FOR GOODNESS OF FIT
CHISQUARE: TESTING FOR GOODNESS OF FIT In the previous chapter we discussed procedures for fitting a hypothesized function to a set of experimental data points. Such procedures involve minimizing a quantity
More informationGeneral Procedure for Hypothesis Test. Five types of statistical analysis. 1. Formulate H 1 and H 0. General Procedure for Hypothesis Test
Five types of statistical analysis General Procedure for Hypothesis Test Descriptive Inferential Differences Associative Predictive What are the characteristics of the respondents? What are the characteristics
More informationExperimental Design. Power and Sample Size Determination. Proportions. Proportions. Confidence Interval for p. The Binomial Test
Experimental Design Power and Sample Size Determination Bret Hanlon and Bret Larget Department of Statistics University of Wisconsin Madison November 3 8, 2011 To this point in the semester, we have largely
More informationSimple Linear Regression Inference
Simple Linear Regression Inference 1 Inference requirements The Normality assumption of the stochastic term e is needed for inference even if it is not a OLS requirement. Therefore we have: Interpretation
More informationStatistics 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 informationName: (b) Find the minimum sample size you should use in order for your estimate to be within 0.03 of p when the confidence level is 95%.
Chapter 78 Exam Name: Answer the questions in the spaces provided. If you run out of room, show your work on a separate paper clearly numbered and attached to this exam. Please indicate which program
More informationChiSquare vs. z Section 25.9
ChiSquare vs. z Section 25.9 Lecture 49 Robb T. Koether HampdenSydney College Wed, Apr 20, 2016 Robb T. Koether (HampdenSydney College) ChiSquare vs. zsection 25.9 Wed, Apr 20, 2016 1 / 11 Outline
More informationBA 275 Review Problems  Week 5 (10/23/0610/27/06) CD Lessons: 48, 49, 50, 51, 52 Textbook: pp. 380394
BA 275 Review Problems  Week 5 (10/23/0610/27/06) CD Lessons: 48, 49, 50, 51, 52 Textbook: pp. 380394 1. Does vigorous exercise affect concentration? In general, the time needed for people to complete
More informationstatistics Chisquare tests and nonparametric Summary sheet from last time: Hypothesis testing Summary sheet from last time: Confidence intervals
Summary sheet from last time: Confidence intervals Confidence intervals take on the usual form: parameter = statistic ± t crit SE(statistic) parameter SE a s e sqrt(1/n + m x 2 /ss xx ) b s e /sqrt(ss
More informationZtable pvalues: use choice 2: normalcdf(
Pvalues 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 informationMATH 10: Elementary Statistics and Probability Chapter 7: The Central Limit Theorem
MATH 10: Elementary Statistics and Probability Chapter 7: The Central Limit Theorem Tony Pourmohamad Department of Mathematics De Anza College Spring 2015 Objectives By the end of this set of slides, you
More informationNUMB3RS Activity: Candy Pieces. Episode: End of Watch
Teacher Page 1 NUMB3RS Activity: Candy Pieces Topic: Chisquare test for goodnessoffit Grade Level: 1112 Objective: Use a chisquare test to determine if there is a significant difference between the
More informationChapter 8: Hypothesis Testing for One Population Mean, Variance, and Proportion
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
More informationStats Review Chapters 910
Stats Review Chapters 910 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 informationChapter 3 RANDOM VARIATE GENERATION
Chapter 3 RANDOM VARIATE GENERATION In order to do a Monte Carlo simulation either by hand or by computer, techniques must be developed for generating values of random variables having known distributions.
More informationAP STATISTICS (WarmUp Exercises)
AP STATISTICS (WarmUp Exercises) 1. Describe the distribution of ages in a city: 2. Graph a box plot on your calculator for the following test scores: {90, 80, 96, 54, 80, 95, 100, 75, 87, 62, 65, 85,
More informationLAB 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 informationCHAPTER 11. GOODNESS OF FIT AND CONTINGENCY TABLES
CHAPTER 11. GOODNESS OF FIT AND CONTINGENCY TABLES The chisquare distribution was discussed in Chapter 4. We now turn to some applications of this distribution. As previously discussed, chisquare is
More informationMath 10 MPS Homework 6 Answers to additional problems
Math 1 MPS Homework 6 Answers to additional problems 1. What are the two types of hypotheses used in a hypothesis test? How are they related? Ho: Null Hypotheses A statement about a population parameter
More informationHypothesis 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 informationChapter 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 informationIntroduction to Hypothesis Testing. Hypothesis Testing. Step 1: State the Hypotheses
Introduction to Hypothesis Testing 1 Hypothesis Testing A hypothesis test is a statistical procedure that uses sample data to evaluate a hypothesis about a population Hypothesis is stated in terms of the
More information4) The goodness of fit test is always a one tail test with the rejection region in the upper tail. Answer: TRUE
Business Statistics, 9e (Groebner/Shannon/Fry) Chapter 13 Goodness of Fit Tests and Contingency Analysis 1) A goodness of fit test can be used to determine whether a set of sample data comes from a specific
More informationChisquare test Fisher s Exact test
Lesson 1 Chisquare test Fisher s Exact test McNemar s Test Lesson 1 Overview Lesson 11 covered two inference methods for categorical data from groups Confidence Intervals for the difference of two proportions
More informationHYPOTHESIS 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 informationHypoTesting. 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 informationNonParametric Tests (I)
Lecture 5: NonParametric Tests (I) KimHuat LIM lim@stats.ox.ac.uk http://www.stats.ox.ac.uk/~lim/teaching.html Slide 1 5.1 Outline (i) Overview of DistributionFree Tests (ii) Median Test for Two Independent
More informationBivariate Statistics Session 2: Measuring Associations ChiSquare Test
Bivariate Statistics Session 2: Measuring Associations ChiSquare Test Features Of The ChiSquare Statistic The chisquare test is nonparametric. That is, it makes no assumptions about the distribution
More informationLecture 13 More on hypothesis testing
Lecture 13 More on hypothesis testing Thais Paiva STA 111  Summer 2013 Term II July 22, 2013 1 / 27 Thais Paiva STA 111  Summer 2013 Term II Lecture 13, 07/22/2013 Lecture Plan 1 Type I and type II error
More information4. Sum the results of the calculation described in step 3 for all classes of progeny
F09 Biol 322 chi square notes 1. Before proceeding with the chi square calculation, clearly state the genetic hypothesis concerning the data. This hypothesis is an interpretation of the data that gives
More informationBasic concepts and introduction to statistical inference
Basic concepts and introduction to statistical inference Anna Helga Jonsdottir Gunnar Stefansson Sigrun Helga Lund University of Iceland (UI) Basic concepts 1 / 19 A review of concepts Basic concepts Confidence
More informationE205 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 informationBowerman, O'Connell, Aitken Schermer, & Adcock, Business Statistics in Practice, Canadian edition
Bowerman, O'Connell, Aitken Schermer, & Adcock, Business Statistics in Practice, Canadian edition Online Learning Centre Technology StepbyStep  Excel Microsoft Excel is a spreadsheet software application
More informationNormality Testing in Excel
Normality Testing in Excel By Mark Harmon Copyright 2011 Mark Harmon No part of this publication may be reproduced or distributed without the express permission of the author. mark@excelmasterseries.com
More informationChapter Five: Paired Samples Methods 1/38
Chapter Five: Paired Samples Methods 1/38 5.1 Introduction 2/38 Introduction Paired data arise with some frequency in a variety of research contexts. Patients might have a particular type of laser surgery
More informationChiSquare Tests and the FDistribution. Goodness of Fit Multinomial Experiments. Chapter 10
Chapter 0 ChiSquare Tests and the FDistribution 0 Goodness of Fit Multinomial xperiments A multinomial experiment is a probability experiment consisting of a fixed number of trials in which there are
More informationLecture 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 informationStats 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 informationIntroduction to Hypothesis Testing. Copyright 2014 Pearson Education, Inc. 91
Introduction to Hypothesis Testing 91 Learning Outcomes Outcome 1. Formulate null and alternative hypotheses for applications involving a single population mean or proportion. Outcome 2. Know what Type
More informationTwoSample TTests Assuming Equal Variance (Enter Means)
Chapter 4 TwoSample TTests Assuming Equal Variance (Enter Means) Introduction This procedure provides sample size and power calculations for one or twosided twosample ttests when the variances of
More informationModule 9: Nonparametric Tests. The Applied Research Center
Module 9: Nonparametric Tests The Applied Research Center Module 9 Overview } Nonparametric Tests } Parametric vs. Nonparametric Tests } Restrictions of Nonparametric Tests } OneSample ChiSquare Test
More informationINTERPRETING THE ONEWAY ANALYSIS OF VARIANCE (ANOVA)
INTERPRETING THE ONEWAY ANALYSIS OF VARIANCE (ANOVA) As with other parametric statistics, we begin the oneway ANOVA with a test of the underlying assumptions. Our first assumption is the assumption of
More informationHypothesis 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 information1 Nonparametric Statistics
1 Nonparametric Statistics When finding confidence intervals or conducting tests so far, we always described the population with a model, which includes a set of parameters. Then we could make decisions
More information9.1 Hypothesis Testing
9.1 Hypothesis Testing Define: 1. Null Hypothesis 2. Alternative Hypothesis Null Hypothesis: H 0, statement that the population proportion, or population mean is EQUAL TO a number population proportion
More informationChapter 7 Part 2. Hypothesis testing Power
Chapter 7 Part 2 Hypothesis testing Power November 6, 2008 All of the normal curves in this handout are sampling distributions Goal: To understand the process of hypothesis testing and the relationship
More informationTImath.com. F Distributions. Statistics
F Distributions ID: 9780 Time required 30 minutes Activity Overview In this activity, students study the characteristics of the F distribution and discuss why the distribution is not symmetric (skewed
More information