Chi-Square Test for Qualitative Data

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Chi-Square Test for Qualitative Data"

Transcription

1 Chi-Square Test for Qualitative Data For qualitative data (measured on a nominal scale) * Observations MUST be independent - No more than one measurement per subject * Sample size must be large enough - Expected frequencies must be 5

2 Chi-square distribution Critical Values Table on page 537 in your book!

3 X rollercoaster right here in California

4 Goodness of Fit χ 1 variable H 0 : observed & expected frequencies do not differ Steps: Calculate expected frequencies Compute χ Compare to critical value df # categories - 1 (fo-fe) fe Observed frequency Expected frequency

5 Example: Goodness of Fit χ Married Single Separated Divorced Widowed Total Sample (N 100) f o expected freq. f e % Is the marital status of our sample representative of the population? Statistical Hypotheses: H 0 f o s (observed frequencies) conform to f e s (expected) H 1 the sample differs from the expected frequencies Decision rule: α.05; df 5-1 4; critical χ 9.49 Calculate test statistic: (*expected frequencies should not below 5 in any cell!) ( fo fe) χ fe (50 55) ( 1) (8 9) (18 10) ( 5) χ χ

6 Getting the Critical Value

7 Example: Goodness of Fit χ Observed statistical test value: χ (4) 8.81, p >.05 Make a decision & interpret - Retain H 0 because 8.81 < The sample does not significantly differ from the population, with regard to marital status

8 Another Example Rated G Rated PG-13 Rated NC17 Sample (N 4) f o expected freq. f e Is there an association between sexy advertising and buying more products? Statistical Hypotheses: H 0 there is no association between sexy advertising and purchases; H 1 there is an association between advertising and purchases Decision rule: α.05; df 3-1 ; critical χ 5.99 Calculate statistic: (remember: expected frequencies should not below 5 in any cell!) ( fo fe) χ fe (5 8) (5 8) (14 8) χ χ

9 Another Example Observed statistical test value: χ () 6.75, p <.05 Make a decision & interpret Reject H 0 because 6.75 > 5.99 Sex sells!

10 Practice! Goodness of Fit χ Lets say you roll a 6-sided dice 10 times. You would EXPECT that each side would come up 1/6 of the time (i.e., 0 times) f o Now your friend gets his own 6-sided dice and rolls it 10 times. You would have the same EXPECTED frequency here, right? f o Calculate a goodness of fit χ for both you and your friend, and determine whether one of you has a weighted dice, at α.05. Don t forget to calculate df to get the critical χ value! Is one of the dice suspect?

11 Your 10 Rolls Dice Obs. Exp. O-E (O-E) (O- E) E

12 Friend s 10 Rolls Dice Obs. Exp. O-E (O-E) (O- E) E

13 df & critical value l df #categories 1 5 l Critical χ 11.07

14 Practice: Goodness of Fit χ You: χ (O-E) E 1.4 NOT SIGNIFICANT Friend: χ (O-E) E 85 SIGNIFICANT Is your friend using a weighted dice?

15 χ Test for Independence Tests the association between categorical variables Do the frequencies you actually observe differ from the expected frequencies by more than chance alone? Statistical hypotheses: Steps: H 0 : the variables are independent (i.e. no association) H 1 : the variables are not independent Calculate expected frequency of each cell Compute χ Compare to critical value df (# rows 1) x (# columns 1) Observed frequency (fo-fe) fe Expected frequency

16 Example: χ Test for Independence Is there an association between gender and vegetarianism? Statistical Hypotheses: Vegetarian Non-Vegetarian Total: Male Female Total: H 0 : gender and food preference are independent H 1 : gender and food preference are associated/ not independent Decision rule: α.05 df (# rows 1) x (# columns 1) à (-1) x (-1) 1 Critical χ 3.841

17 Next step: calculate the expected frequency of each cell Vegetarian Non-Vegetarian Total: Male fe 70 x Female fe 130 x x Total: fe fe 130 x expected frequency of each cell row total x column total grand total

18 Now put it into the table Sample (N 00) Male Veg Male Non-Veg Female Veg Female Non-Veg f o expected freq. f e χ χ ( fo f fe (10 1) 1 e) (60 49) + 49 (50 39) + 39 (80 91) + 91 χ

19 Example: χ Test for Independence Observed statistical test value: χ (1) 1.66, p <.05 Make a decision & interpret Reject H 0 and accept H 1 because 1.66 > 3.84 Gender is related to food preference!

20 Practice! Is there an association between cat ownership (yes/no) and life success (yes/no)? You survey 100 people Successful Not Successful Total: Cat No Cat Total: 100 Don t forget to get your row and column totals And follow the steps of hypothesis testing: Statistical Hypothesis Decision Rule Calculate Test Statistic Make a Decision & Interpret

21 Successful Not Successful Total: Cat No Cat Total: Statistical Hypotheses: H 0 : cat ownership and life success are independent H 1 : cat ownership and life success are related Decision rule: α.05 df (# rows 1) x (# columns 1) à (-1) x (-1) 1 Critical χ 3.841

22 Successful Not Successful Total: Cat fe 75 x No Cat fe 5 x x Total: fe fe 5 x Sample (N 100) Cat, Success No cat, Success Cat, No success f o expected freq. f e No cat, No Success

23 Sample (N 100) Cat, Success No cat, Success Cat, No success f o expected freq. f e No cat, No Success χ ( fo fe) χ fe ( ) ( ) ( ) (10 6.5) χ

24 Observed statistical test value: χ (1) 4.00, p <.05 Make a decision & interpret Reject H 0 because 4.00 > 3.84 Cat ownership is related to life success!

Is it statistically significant? The chi-square test

Is it statistically significant? The chi-square test UAS Conference Series 2013/14 Is it statistically significant? The chi-square test Dr Gosia Turner Student Data Management and Analysis 14 September 2010 Page 1 Why chi-square? Tests whether two categorical

More information

Chi Square (χ 2 ) Statistical Instructions EXP 3082L Jay Gould s Elaboration on Christensen and Evans (1980)

Chi Square (χ 2 ) Statistical Instructions EXP 3082L Jay Gould s Elaboration on Christensen and Evans (1980) Chi Square (χ 2 ) Statistical Instructions EXP 3082L Jay Gould s Elaboration on Christensen and Evans (1980) For the Driver Behavior Study, the Chi Square Analysis II is the appropriate analysis below.

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

Having a coin come up heads or tails is a variable on a nominal scale. Heads is a different category from tails.

Having a coin come up heads or tails is a variable on a nominal scale. Heads is a different category from tails. Chi-square Goodness of Fit Test The chi-square test is designed to test differences whether one frequency is different from another frequency. The chi-square test is designed for use with data on a nominal

More information

11-2 Goodness of Fit Test

11-2 Goodness of Fit Test 11-2 Goodness of Fit Test In This section we consider sample data consisting of observed frequency counts arranged in a single row or column (called a one-way frequency table). We will use a hypothesis

More information

Module 9: Nonparametric Tests. The Applied Research Center

Module 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 } One-Sample Chi-Square Test

More information

Elementary Statistics

Elementary Statistics lementary Statistics Chap10 Dr. Ghamsary Page 1 lementary Statistics M. Ghamsary, Ph.D. Chapter 10 Chi-square Test for Goodness of fit and Contingency tables lementary Statistics Chap10 Dr. Ghamsary Page

More information

SCHOOL OF HEALTH AND HUMAN SCIENCES DON T FORGET TO RECODE YOUR MISSING VALUES

SCHOOL OF HEALTH AND HUMAN SCIENCES DON T FORGET TO RECODE YOUR MISSING VALUES SCHOOL OF HEALTH AND HUMAN SCIENCES Using SPSS Topics addressed today: 1. Differences between groups 2. Graphing Use the s4data.sav file for the first part of this session. DON T FORGET TO RECODE YOUR

More information

Comparing Multiple Proportions, Test of Independence and Goodness of Fit

Comparing Multiple Proportions, Test of Independence and Goodness of Fit Comparing Multiple Proportions, Test of Independence and Goodness of Fit Content Testing the Equality of Population Proportions for Three or More Populations Test of Independence Goodness of Fit Test 2

More information

Bivariate Statistics Session 2: Measuring Associations Chi-Square Test

Bivariate Statistics Session 2: Measuring Associations Chi-Square Test Bivariate Statistics Session 2: Measuring Associations Chi-Square Test Features Of The Chi-Square Statistic The chi-square test is non-parametric. That is, it makes no assumptions about the distribution

More information

TABLE OF CONTENTS. About Chi Squares... 1. What is a CHI SQUARE?... 1. Chi Squares... 1. Hypothesis Testing with Chi Squares... 2

TABLE OF CONTENTS. About Chi Squares... 1. What is a CHI SQUARE?... 1. Chi Squares... 1. Hypothesis Testing with Chi Squares... 2 About Chi Squares TABLE OF CONTENTS About Chi Squares... 1 What is a CHI SQUARE?... 1 Chi Squares... 1 Goodness of fit test (One-way χ 2 )... 1 Test of Independence (Two-way χ 2 )... 2 Hypothesis Testing

More information

Recommend Continued CPS Monitoring. 63 (a) 17 (b) 10 (c) 90. 35 (d) 20 (e) 25 (f) 80. Totals/Marginal 98 37 35 170

Recommend Continued CPS Monitoring. 63 (a) 17 (b) 10 (c) 90. 35 (d) 20 (e) 25 (f) 80. Totals/Marginal 98 37 35 170 Work Sheet 2: Calculating a Chi Square Table 1: Substance Abuse Level by ation Total/Marginal 63 (a) 17 (b) 10 (c) 90 35 (d) 20 (e) 25 (f) 80 Totals/Marginal 98 37 35 170 Step 1: Label Your Table. Label

More information

CHAPTER 11 CHI-SQUARE: NON-PARAMETRIC COMPARISONS OF FREQUENCY

CHAPTER 11 CHI-SQUARE: NON-PARAMETRIC COMPARISONS OF FREQUENCY CHAPTER 11 CHI-SQUARE: NON-PARAMETRIC 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 information

Chapter 11. Chapter 11 Overview. Chapter 11 Objectives 11/24/2015. Other Chi-Square Tests

Chapter 11. Chapter 11 Overview. Chapter 11 Objectives 11/24/2015. Other Chi-Square Tests 11/4/015 Chapter 11 Overview Chapter 11 Introduction 11-1 Test for Goodness of Fit 11- Tests Using Contingency Tables Other Chi-Square Tests McGraw-Hill, Bluman, 7th ed., Chapter 11 1 Bluman, Chapter 11

More information

Mind on Statistics. Chapter 15

Mind 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 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

3. Analysis of Qualitative Data

3. Analysis of Qualitative Data 3. Analysis of Qualitative Data Inferential Stats, CEC at RUPP Poch Bunnak, Ph.D. Content 1. Hypothesis tests about a population proportion: Binomial test 2. Chi-square testt for goodness offitfit 3. Chi-square

More information

2 Tests for Goodness of Fit:

2 Tests for Goodness of Fit: Tests for Goodness of Fit: General Notion: We often wish to know whether a particular distribution fits a general definition Example: To use t tests, we must suppose that the population is normally distributed

More information

Chi Square Goodness of Fit & Two-way Tables (Create) MATH NSPIRED

Chi Square Goodness of Fit & Two-way Tables (Create) MATH NSPIRED Overview In this activity, you will look at a setting that involves categorical data and determine which is the appropriate chi-square test to use. You will input data into a list or matrix and conduct

More information

Nonparametric Tests. Chi-Square Test for Independence

Nonparametric Tests. Chi-Square Test for Independence DDBA 8438: Nonparametric Statistics: The Chi-Square Test Video Podcast Transcript JENNIFER ANN MORROW: Welcome to "Nonparametric Statistics: The Chi-Square Test." My name is Dr. Jennifer Ann Morrow. In

More information

British Journal of Science 156 January 2012, Vol. 3 (1)

British Journal of Science 156 January 2012, Vol. 3 (1) British Journal of Science 156 Effect of Corporate Social Responsibility on the Society (Using Shell Petroleum Development Company as a Case study) Geraldine Nkechinyere Okeudo Department of Transport

More information

In comparison: Any performing arts event 42.4% 37.6% 0.8% 9.0% 9,000,000 9,100,000 83, %

In comparison: Any performing arts event 42.4% 37.6% 0.8% 9.0% 9,000,000 9,100,000 83, % Hill Strategies, detailed museum and art gallery tables, page 1 Museum and art gallery attendance in Canada - Detailed tables Prepared by Hill Strategies Most of the estimates in these tables are rounded

More information

Chapter 23. Two Categorical Variables: The Chi-Square Test

Chapter 23. Two Categorical Variables: The Chi-Square Test Chapter 23. Two Categorical Variables: The Chi-Square Test 1 Chapter 23. Two Categorical Variables: The Chi-Square Test Two-Way Tables Note. We quickly review two-way tables with an example. Example. Exercise

More information

CHAPTER IV FINDINGS AND CONCURRENT DISCUSSIONS

CHAPTER IV FINDINGS AND CONCURRENT DISCUSSIONS CHAPTER IV FINDINGS AND CONCURRENT DISCUSSIONS Hypothesis 1: People are resistant to the technological change in the security system of the organization. Hypothesis 2: information hacked and misused. Lack

More information

SPSS: Expected frequencies, chi-squared test. In-depth example: Age groups and radio choices. Dealing with small frequencies.

SPSS: Expected frequencies, chi-squared test. In-depth example: Age groups and radio choices. Dealing with small frequencies. SPSS: Expected frequencies, chi-squared test. In-depth example: Age groups and radio choices. Dealing with small frequencies. Quick Example: Handedness and Careers Last time we tested whether one nominal

More information

Binary Logistic Regression

Binary Logistic Regression Binary Logistic Regression Main Effects Model Logistic regression will accept quantitative, binary or categorical predictors and will code the latter two in various ways. Here s a simple model including

More information

Excel Charts & Graphs

Excel Charts & Graphs MAX 201 Spring 2008 Assignment #6: Charts & Graphs; Modifying Data Due at the beginning of class on March 18 th Introduction This assignment introduces the charting and graphing capabilities of SPSS and

More information

Running Descriptive Statistics: Sample and Population Values

Running Descriptive Statistics: Sample and Population Values Running Descriptive Statistics: Sample and Population Values Goal This exercise is an introduction to a few of the variables in the household- and person-level LIS data sets. The exercise concentrates

More information

Effect of Sales Promotion as a Tool on Organizational Performance (A case Study of Sunshine Plastic Company)

Effect of Sales Promotion as a Tool on Organizational Performance (A case Study of Sunshine Plastic Company) Journal of Emerging Trends in Economics and Sciences (JETEMS) 2 (1): 9-13 Scholarlink Research Institute Journals, 2011 (ISSN: 2141-7024) jetems.scholarlinkresearch.org Journal of Emerging Trends Economics

More information

Using Stata for Categorical Data Analysis

Using Stata for Categorical Data Analysis Using Stata for Categorical Data Analysis NOTE: These problems make extensive use of Nick Cox s tab_chi, which is actually a collection of routines, and Adrian Mander s ipf command. From within Stata,

More information

Terminology. 2 There is no mathematical difference between the errors, however. The bottom line is that we choose one type

Terminology. 2 There is no mathematical difference between the errors, however. The bottom line is that we choose one type Hypothesis Testing 10.2.1 Terminology The null hypothesis H 0 is a nothing hypothesis, whose interpretation could be that nothing has changed, there is no difference, there is nothing special taking place,

More information

Types of Data, Descriptive Statistics, and Statistical Tests for Nominal Data. Patrick F. Smith, Pharm.D. University at Buffalo Buffalo, New York

Types of Data, Descriptive Statistics, and Statistical Tests for Nominal Data. Patrick F. Smith, Pharm.D. University at Buffalo Buffalo, New York Types of Data, Descriptive Statistics, and Statistical Tests for Nominal Data Patrick F. Smith, Pharm.D. University at Buffalo Buffalo, New York . NONPARAMETRIC STATISTICS I. DEFINITIONS A. Parametric

More information

MULTIPLE REGRESSION EXAMPLE

MULTIPLE REGRESSION EXAMPLE MULTIPLE REGRESSION EXAMPLE For a sample of n = 166 college students, the following variables were measured: Y = height X 1 = mother s height ( momheight ) X 2 = father s height ( dadheight ) X 3 = 1 if

More information

Odds ratio, Odds ratio test for independence, chi-squared statistic.

Odds ratio, Odds ratio test for independence, chi-squared statistic. Odds ratio, Odds ratio test for independence, chi-squared statistic. Announcements: Assignment 5 is live on webpage. Due Wed Aug 1 at 4:30pm. (9 days, 1 hour, 58.5 minutes ) Final exam is Aug 9. Review

More information

SPSS for Exploratory Data Analysis Data used in this guide: studentp.sav (http://people.ysu.edu/~gchang/stat/studentp.sav)

SPSS for Exploratory Data Analysis Data used in this guide: studentp.sav (http://people.ysu.edu/~gchang/stat/studentp.sav) Data used in this guide: studentp.sav (http://people.ysu.edu/~gchang/stat/studentp.sav) Organize and Display One Quantitative Variable (Descriptive Statistics, Boxplot & Histogram) 1. Move the mouse pointer

More information

4. CHI-SQUARE: INTRODUCING THE GOODNESS OF FIT TEST AND THE TEST OF ASSOCIATION

4. CHI-SQUARE: INTRODUCING THE GOODNESS OF FIT TEST AND THE TEST OF ASSOCIATION 4. : INRODUCING HE GOODNESS OF FI ES AND HE ES OF ASSOCIAION Dr om Clark & Dr Liam Foster Department of Sociological Studies University of Sheffield CONENS 4. Chi-square *So now you should be able to undertake

More information

Row vs. Column Percents. tab PRAYER DEGREE, row col

Row vs. Column Percents. tab PRAYER DEGREE, row col Bivariate Analysis - Crosstabulation One of most basic research tools shows how x varies with respect to y Interpretation of table depends upon direction of percentaging example Row vs. Column Percents.

More information

Hypothesis Testing I

Hypothesis Testing I ypothesis Testing I The testing process:. Assumption about population(s) parameter(s) is made, called null hypothesis, denoted. 2. Then the alternative is chosen (often just a negation of the null hypothesis),

More information

Hypothesis Testing for a Proportion

Hypothesis Testing for a Proportion Math 122 Intro to Stats Chapter 6 Semester II, 2015-16 Inference for Categorical Data Hypothesis Testing for a Proportion In a survey, 1864 out of 2246 randomly selected adults said texting while driving

More information

Chi-square test Fisher s Exact test

Chi-square test Fisher s Exact test Lesson 1 Chi-square 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 information

First-year Statistics for Psychology Students Through Worked Examples

First-year Statistics for Psychology Students Through Worked Examples First-year Statistics for Psychology Students Through Worked Examples 1. THE CHI-SQUARE TEST A test of association between categorical variables by Charles McCreery, D.Phil Formerly Lecturer in Experimental

More information

Table 1: Profile of Consumer Particulars Classification Numbers Percentage Upto 20 25 41.67 Age. 21 to 40 18 30.00 Above 40 17 28.

Table 1: Profile of Consumer Particulars Classification Numbers Percentage Upto 20 25 41.67 Age. 21 to 40 18 30.00 Above 40 17 28. 2014; 1(7): 280-286 IJMRD 2014; 1(7): 280-286 www.allsubjectjournal.com Received: 04-12-2014 Accepted: 22-12-2014 e-issn: 2349-4182 p-issn: 2349-5979 V. Suganthi Assistant Professor, Department of Commerce,

More information

Parent Questionnaire. Q 1. Would you prefer to be interviewed in English or in French? English French

Parent Questionnaire. Q 1. Would you prefer to be interviewed in English or in French? English French Parent Questionnaire Q 1. Would you prefer to be interviewed in English or in French? English French Q 2. Including yourself, how many people live in your household? Q 3. How many of them are less than

More information

STATISTICS 8 CHAPTERS 1 TO 6, SAMPLE MULTIPLE CHOICE QUESTIONS

STATISTICS 8 CHAPTERS 1 TO 6, SAMPLE MULTIPLE CHOICE QUESTIONS STATISTICS 8 CHAPTERS 1 TO 6, SAMPLE MULTIPLE CHOICE QUESTIONS Correct answers are in bold italics.. This scenario applies to Questions 1 and 2: A study was done to compare the lung capacity of coal miners

More information

Testing Research and Statistical Hypotheses

Testing Research and Statistical Hypotheses Testing Research and Statistical Hypotheses Introduction In the last lab we analyzed metric artifact attributes such as thickness or width/thickness ratio. Those were continuous variables, which as you

More information

Parent Questionnaire. Q 1. Would you prefer to be interviewed in English or in French? English French

Parent Questionnaire. Q 1. Would you prefer to be interviewed in English or in French? English French Parent Questionnaire Q 1. Would you prefer to be interviewed in English or in French? English French Q 2. Including yourself, how many people live in your household? Q 3. How many of them are less than

More information

University of Colorado Campus Box 470 Boulder, CO 80309-0470 (303) 492-8230 Fax (303) 492-4916 http://www.colorado.edu/research/hughes

University of Colorado Campus Box 470 Boulder, CO 80309-0470 (303) 492-8230 Fax (303) 492-4916 http://www.colorado.edu/research/hughes Hughes Undergraduate Biological Science Education Initiative HHMI Tracking the Source of Disease: Koch s Postulates, Causality, and Contemporary Epidemiology Koch s Postulates In the late 1800 s, the German

More information

How to set the main menu of STATA to default factory settings standards

How to set the main menu of STATA to default factory settings standards University of Pretoria Data analysis for evaluation studies Examples in STATA version 11 List of data sets b1.dta (To be created by students in class) fp1.xls (To be provided to students) fp1.txt (To be

More information

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

The Chi-Square Test. STAT E-50 Introduction to Statistics

The Chi-Square Test. STAT E-50 Introduction to Statistics STAT -50 Introduction to Statistics The Chi-Square Test The Chi-square test is a nonparametric test that is used to compare experimental results with theoretical models. That is, we will be comparing observed

More information

IBM SPSS Statistics 20 Part 4: Chi-Square and ANOVA

IBM SPSS Statistics 20 Part 4: Chi-Square and ANOVA CALIFORNIA STATE UNIVERSITY, LOS ANGELES INFORMATION TECHNOLOGY SERVICES IBM SPSS Statistics 20 Part 4: Chi-Square and ANOVA Summer 2013, Version 2.0 Table of Contents Introduction...2 Downloading the

More information

Association Between Variables

Association Between Variables Contents 11 Association Between Variables 767 11.1 Introduction............................ 767 11.1.1 Measure of Association................. 768 11.1.2 Chapter Summary.................... 769 11.2 Chi

More information

Variables and Data A variable contains data about anything we measure. For example; age or gender of the participants or their score on a test.

Variables and Data A variable contains data about anything we measure. For example; age or gender of the participants or their score on a test. The Analysis of Research Data The design of any project will determine what sort of statistical tests you should perform on your data and how successful the data analysis will be. For example if you decide

More information

Mind on Statistics. Chapter 4

Mind on Statistics. Chapter 4 Mind on Statistics Chapter 4 Sections 4.1 Questions 1 to 4: The table below shows the counts by gender and highest degree attained for 498 respondents in the General Social Survey. Highest Degree Gender

More information

CATEGORICAL DATA Chi-Square Tests for Univariate Data

CATEGORICAL DATA Chi-Square Tests for Univariate Data CATEGORICAL DATA Chi-Square Tests For Univariate Data 1 CATEGORICAL DATA Chi-Square Tests for Univariate Data Recall that a categorical variable is one in which the possible values are categories or groupings.

More information

IBM SPSS Statistics for Beginners for Windows

IBM SPSS Statistics for Beginners for Windows ISS, NEWCASTLE UNIVERSITY IBM SPSS Statistics for Beginners for Windows A Training Manual for Beginners Dr. S. T. Kometa A Training Manual for Beginners Contents 1 Aims and Objectives... 3 1.1 Learning

More information

SUGI 29 Statistics and Data Analysis

SUGI 29 Statistics and Data Analysis Paper 194-29 Head of the CLASS: Impress your colleagues with a superior understanding of the CLASS statement in PROC LOGISTIC Michelle L. Pritchard and David J. Pasta Ovation Research Group, San Francisco,

More information

Business Statistics: Chapter 2: Data Quiz A

Business Statistics: Chapter 2: Data Quiz A CHAPTER 2 Quiz A Business Statistics, 2nd ed. 2-1 Business Statistics: Chapter 2: Data Quiz A Name 1. The mission of the Pew Internet & Life Project is to explore the impact of the Internet on families,

More information

AP: LAB 8: THE CHI-SQUARE TEST. Probability, Random Chance, and Genetics

AP: LAB 8: THE CHI-SQUARE TEST. Probability, Random Chance, and Genetics Ms. Foglia Date AP: LAB 8: THE CHI-SQUARE TEST Probability, Random Chance, and Genetics Why do we study random chance and probability at the beginning of a unit on genetics? Genetics is the study of inheritance,

More information

CHAPTER 11. GOODNESS OF FIT AND CONTINGENCY TABLES

CHAPTER 11. GOODNESS OF FIT AND CONTINGENCY TABLES CHAPTER 11. GOODNESS OF FIT AND CONTINGENCY TABLES The chi-square distribution was discussed in Chapter 4. We now turn to some applications of this distribution. As previously discussed, chi-square is

More information

Adverse Impact Ratio for Females (0/ 1) = 0 (5/ 17) = 0.2941 Adverse impact as defined by the 4/5ths rule was not found in the above data.

Adverse Impact Ratio for Females (0/ 1) = 0 (5/ 17) = 0.2941 Adverse impact as defined by the 4/5ths rule was not found in the above data. 1 of 9 12/8/2014 12:57 PM (an On-Line Internet based application) Instructions: Please fill out the information into the form below. Once you have entered your data below, you may select the types of analysis

More information

DEPARTMENT OF POLITICAL SCIENCE AND INTERNATIONAL RELATIONS. Posc/Uapp 816 CONTINGENCY TABLES

DEPARTMENT OF POLITICAL SCIENCE AND INTERNATIONAL RELATIONS. Posc/Uapp 816 CONTINGENCY TABLES DEPARTMENT OF POLITICAL SCIENCE AND INTERNATIONAL RELATIONS Posc/Uapp 816 CONTINGENCY TABLES I. AGENDA: A. Cross-classifications 1. Two-by-two and R by C tables 2. Statistical independence 3. The interpretation

More information

Additional sources Compilation of sources: http://lrs.ed.uiuc.edu/tseportal/datacollectionmethodologies/jin-tselink/tselink.htm

Additional sources Compilation of sources: http://lrs.ed.uiuc.edu/tseportal/datacollectionmethodologies/jin-tselink/tselink.htm Mgt 540 Research Methods Data Analysis 1 Additional sources Compilation of sources: http://lrs.ed.uiuc.edu/tseportal/datacollectionmethodologies/jin-tselink/tselink.htm http://web.utk.edu/~dap/random/order/start.htm

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

Chapter 13. Chi-Square. Crosstabs and Nonparametric Tests. Specifically, we demonstrate procedures for running two separate

Chapter 13. Chi-Square. Crosstabs and Nonparametric Tests. Specifically, we demonstrate procedures for running two separate 1 Chapter 13 Chi-Square This section covers the steps for running and interpreting chi-square analyses using the SPSS Crosstabs and Nonparametric Tests. Specifically, we demonstrate procedures for running

More information

Scientific Method. 2. Design Study. 1. Ask Question. Questionnaire. Descriptive Research Study. 6: Share Findings. 1: Ask Question.

Scientific Method. 2. Design Study. 1. Ask Question. Questionnaire. Descriptive Research Study. 6: Share Findings. 1: Ask Question. Descriptive Research Study Investigation of Positive and Negative Affect of UniJos PhD Students toward their PhD Research Project : Ask Question : Design Study Scientific Method 6: Share Findings. Reach

More information

LAB : THE CHI-SQUARE TEST. Probability, Random Chance, and Genetics

LAB : THE CHI-SQUARE TEST. Probability, Random Chance, and Genetics Period Date LAB : THE CHI-SQUARE TEST Probability, Random Chance, and Genetics Why do we study random chance and probability at the beginning of a unit on genetics? Genetics is the study of inheritance,

More information

Chi Square Distribution

Chi Square Distribution 17. Chi Square A. Chi Square Distribution B. One-Way Tables C. Contingency Tables D. Exercises Chi Square is a distribution that has proven to be particularly useful in statistics. The first section describes

More information

Writing Chapters 4 & 5 of the Thesis/Dissertation

Writing Chapters 4 & 5 of the Thesis/Dissertation Department of Graduate Education & Leadership LUNCH TIME SEMINAR Writing Chapters 4 & 5 of the Thesis/Dissertation March 26, 2014 Writing Chapters 4 & 5 of the Thesis/Dissertation Caddabra Bernard Research

More information

Guido s Guide to PROC FREQ A Tutorial for Beginners Using the SAS System Joseph J. Guido, University of Rochester Medical Center, Rochester, NY

Guido s Guide to PROC FREQ A Tutorial for Beginners Using the SAS System Joseph J. Guido, University of Rochester Medical Center, Rochester, NY Guido s Guide to PROC FREQ A Tutorial for Beginners Using the SAS System Joseph J. Guido, University of Rochester Medical Center, Rochester, NY ABSTRACT PROC FREQ is an essential procedure within BASE

More information

Solutions to Homework 10 Statistics 302 Professor Larget

Solutions to Homework 10 Statistics 302 Professor Larget s to Homework 10 Statistics 302 Professor Larget Textbook Exercises 7.14 Rock-Paper-Scissors (Graded for Accurateness) In Data 6.1 on page 367 we see a table, reproduced in the table below that shows the

More information

11. Chi Square. Go to Data/Weight Cases and select Freq as the weights. Select Analyze/Nonparametric Tests/Chi Square.

11. Chi Square. Go to Data/Weight Cases and select Freq as the weights. Select Analyze/Nonparametric Tests/Chi Square. 11. Chi Square Objectives Calculate goodness of fit Chi Square Calculate Chi Square for contingency tables Calculate effect size Save data entry time by weighting cases A Chi Square is used to analyze

More information

1. Comparing Two Means: Dependent Samples

1. 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 information

FREQ-OUT: An Applied Presentation of the Options and Output of the FREQ Procedure. Pamela Landsman MPH, Merck & Co., Inc, West Point, PA

FREQ-OUT: An Applied Presentation of the Options and Output of the FREQ Procedure. Pamela Landsman MPH, Merck & Co., Inc, West Point, PA FREQ-OUT: An Applied Presentation of the Options and Output of the FREQ Procedure Pamela Landsman MPH, Merck & Co., Inc, West Point, PA Abstract: Have you ever been told compare the rate of death by gender,

More information

COMPARISONS OF CUSTOMER LOYALTY: PUBLIC & PRIVATE INSURANCE COMPANIES.

COMPARISONS OF CUSTOMER LOYALTY: PUBLIC & PRIVATE INSURANCE COMPANIES. 277 CHAPTER VI COMPARISONS OF CUSTOMER LOYALTY: PUBLIC & PRIVATE INSURANCE COMPANIES. This chapter contains a full discussion of customer loyalty comparisons between private and public insurance companies

More information

A CNBC SPECIAL REPORT. THE AP-CNBC Poll. Conducted by GfK Roper Public Affairs & Media

A CNBC SPECIAL REPORT. THE AP-CNBC Poll. Conducted by GfK Roper Public Affairs & Media A CNBC SPECIAL REPORT THE AP-CNBC Poll Conducted by GfK Roper Public Affairs & Media Interview dates: April 7 12, 2010 Interviews: 1,001 adults Margin of error: +/- 4.3 percentage points at the 95% confidence

More information

Profiles and Data Analysis. 5.1 Introduction

Profiles and Data Analysis. 5.1 Introduction Profiles and Data Analysis PROFILES AND DATA ANALYSIS 5.1 Introduction The survey of consumers numbering 617, spread across the three geographical areas, of the state of Kerala, who have given information

More information

Chapter 5 Analysis of variance SPSS Analysis of variance

Chapter 5 Analysis of variance SPSS Analysis of variance Chapter 5 Analysis of variance SPSS Analysis of variance Data file used: gss.sav How to get there: Analyze Compare Means One-way ANOVA To test the null hypothesis that several population means are equal,

More information

2015 RCS FACT SHEET #5 GENDER AND MARITAL STATUS COMPARISONS AMONG WORKERS

2015 RCS FACT SHEET #5 GENDER AND MARITAL STATUS COMPARISONS AMONG WORKERS 2015 RCS FACT SHEET #5 GENDER AND MARITAL STATUS COMPARISONS AMONG WORKERS Are unmarried men and women equally likely to plan and save for? Do they have similar expectations about their needs in? And how

More information

Lesson 3: Calculating Conditional Probabilities and Evaluating Independence Using Two-Way Tables

Lesson 3: Calculating Conditional Probabilities and Evaluating Independence Using Two-Way Tables Calculating Conditional Probabilities and Evaluating Independence Using Two-Way Tables Classwork Example 1 Students at Rufus King High School were discussing some of the challenges of finding space for

More information

ehealth, Inc. National Consumer Survey of Individuals Looking for Private Health Insurance at ehealthinsurance Services

ehealth, Inc. National Consumer Survey of Individuals Looking for Private Health Insurance at ehealthinsurance Services ehealth, Inc. National Consumer Survey of Individuals Looking for Private Health Insurance at ehealthinsurance Services Methodology: ehealth, Inc. is the parent company of ehealthinsurance Services Inc.,

More information

WHOQOL-BREF. June 1997. U.S. Version. University of Washington Seattle, Washington United States of America

WHOQOL-BREF. June 1997. U.S. Version. University of Washington Seattle, Washington United States of America WHOQOL-BREF June 1997 U.S. Version University of Washington Seattle, Washington United States of America Emblem...Soul Catcher: a Northwest Coast Indian symbol of physical and mental well-being. Artist:

More information

Statistics. One-two sided test, Parametric and non-parametric test statistics: one group, two groups, and more than two groups samples

Statistics. One-two sided test, Parametric and non-parametric test statistics: one group, two groups, and more than two groups samples Statistics One-two sided test, Parametric and non-parametric test statistics: one group, two groups, and more than two groups samples February 3, 00 Jobayer Hossain, Ph.D. & Tim Bunnell, Ph.D. Nemours

More information

Statistics Notes Revision in Maths Week

Statistics Notes Revision in Maths Week Statistics Notes Revision in Maths Week 1 Section - Producing Data 1.1 Introduction Statistics is the science that studies the collection and interpretation of numerical data. Statistics divides the study

More information

ANOVA Analysis of Variance

ANOVA Analysis of Variance ANOVA Analysis of Variance What is ANOVA and why do we use it? Can test hypotheses about mean differences between more than 2 samples. Can also make inferences about the effects of several different IVs,

More information

Conditional Probability and General Multiplication Rule

Conditional Probability and General Multiplication Rule Conditional Probability and General Multiplication Rule Objectives: - Identify Independent and dependent events - Find Probability of independent events - Find Probability of dependent events - Find Conditional

More information

MULTIPLE REGRESSION WITH CATEGORICAL DATA

MULTIPLE REGRESSION WITH CATEGORICAL DATA DEPARTMENT OF POLITICAL SCIENCE AND INTERNATIONAL RELATIONS Posc/Uapp 86 MULTIPLE REGRESSION WITH CATEGORICAL DATA I. AGENDA: A. Multiple regression with categorical variables. Coding schemes. Interpreting

More information

The three statistics of interest comparing the exposed to the not exposed are:

The three statistics of interest comparing the exposed to the not exposed are: Review: Common notation for a x table: Not Exposed Exposed Disease a b a+b No Disease c d c+d a+c b+d N Warning: Rosner presents the transposed table so b and c have their meanings reversed in the text.

More information

Statistical Analysis The First Steps Jennifer L. Waller Medical College of Georgia, Augusta, Georgia

Statistical Analysis The First Steps Jennifer L. Waller Medical College of Georgia, Augusta, Georgia Statistical Analysis The First Steps Jennifer L. Waller Medical College of Georgia, Augusta, Georgia ABSTRACT For both statisticians and non-statisticians, knowing what data look like before more rigorous

More information

Simulating Chi-Square Test Using Excel

Simulating Chi-Square Test Using Excel Simulating Chi-Square Test Using Excel Leslie Chandrakantha John Jay College of Criminal Justice of CUNY Mathematics and Computer Science Department 524 West 59 th Street, New York, NY 10019 lchandra@jjay.cuny.edu

More information

Carolyn Anderson & Youngshil Paek (Slides created by Shuai Sam Wang) Department of Educational Psychology University of Illinois at Urbana-Champaign

Carolyn Anderson & Youngshil Paek (Slides created by Shuai Sam Wang) Department of Educational Psychology University of Illinois at Urbana-Champaign Carolyn Anderson & Youngshil Paek (Slides created by Shuai Sam Wang) Department of Educational Psychology University of Illinois at Urbana-Champaign Key Points 1. Data 2. Variable 3. Types of data 4. Define

More information

Math 58. Rumbos Fall 2008 1. Solutions to Review Problems for Exam 2

Math 58. Rumbos Fall 2008 1. Solutions to Review Problems for Exam 2 Math 58. Rumbos Fall 2008 1 Solutions to Review Problems for Exam 2 1. For each of the following scenarios, determine whether the binomial distribution is the appropriate distribution for the random variable

More information

BUY HERE PAY HERE BUYER STUDY

BUY HERE PAY HERE BUYER STUDY BUY HERE PAY HERE BUYER STUDY ABOUT THE STUDY In October 2010 and January 2011, the National Alliance of Buy Here, Pay Here Dealers (NABD) and AutoTrader.com teamed up for a groundbreaking study to define

More information

Demographic and Socioeconomic Conditions

Demographic and Socioeconomic Conditions Demographic and Socioeconomic Conditions Population Growth over Time and Projected Population Size by Race/Ethnicity 1990 1990 2000 2000 2010 2010 2050, Projected 2050, Projected Santa Clara County 1,497,577

More information

Estover Surgery New Patient Questionnaire

Estover Surgery New Patient Questionnaire Date of Completion: Personal Details Title: Mr Mrs Miss Ms Dr Other (please circle) Name: Date of Birth: Mobile Number: Home Telephone Number: Work Telephone Number: Contact Email Address: Marital Status:

More information

Topic 8. Chi Square Tests

Topic 8. Chi Square Tests BE540W Chi Square Tests Page 1 of 5 Topic 8 Chi Square Tests Topics 1. Introduction to Contingency Tables. Introduction to the Contingency Table Hypothesis Test of No Association.. 3. The Chi Square Test

More information

Data Types. 1. Continuous 2. Discrete quantitative 3. Ordinal 4. Nominal. Figure 1

Data Types. 1. Continuous 2. Discrete quantitative 3. Ordinal 4. Nominal. Figure 1 Data Types By Tanya Hoskin, a statistician in the Mayo Clinic Department of Health Sciences Research who provides consultations through the Mayo Clinic CTSA BERD Resource. Don t let the title scare you.

More information

Crosstabulation & Chi Square

Crosstabulation & Chi Square Crosstabulation & Chi Square Robert S Michael Chi-square as an Index of Association After examining the distribution of each of the variables, the researcher s next task is to look for relationships among

More information

This chapter discusses some of the basic concepts in inferential statistics.

This chapter discusses some of the basic concepts in inferential statistics. Research Skills for Psychology Majors: Everything You Need to Know to Get Started Inferential Statistics: Basic Concepts This chapter discusses some of the basic concepts in inferential statistics. Details

More information