Inference for Categorical Data Chi-SquareCh.11. Facts about Chi-Square ► Takes only positive values and the graph is skewed to the right ► Test Statistic.

Slides:



Advertisements
Similar presentations
Chapter 11 Other Chi-Squared Tests
Advertisements

Chi-square test Chi-square test or  2 test. Chi-square test countsUsed to test the counts of categorical data ThreeThree types –Goodness of fit (univariate)
Chi-Squared Hypothesis Testing Using One-Way and Two-Way Frequency Tables of Categorical Variables.
The Analysis of Categorical Data and Goodness of Fit Tests
Inference about the Difference Between the
Statistical Inference for Frequency Data Chapter 16.
Chapter 13: Inference for Distributions of Categorical Data
© 2010 Pearson Prentice Hall. All rights reserved The Chi-Square Test of Homogeneity.
© 2010 Pearson Prentice Hall. All rights reserved The Chi-Square Test of Independence.
CHAPTER 11 Inference for Distributions of Categorical Data
PY 427 Statistics 1Fall 2006 Kin Ching Kong, Ph.D Lecture 12 Chicago School of Professional Psychology.
HAWKES LEARNING SYSTEMS math courseware specialists Copyright © 2010 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Chapter 12 Additional.
Chapter 26: Comparing Counts. To analyze categorical data, we construct two-way tables and examine the counts of percents of the explanatory and response.
Cross-Tabulations.
Presentation 12 Chi-Square test.
Chapter 13 Chi-Square Tests. The chi-square test for Goodness of Fit allows us to determine whether a specified population distribution seems valid. The.
Business Statistics, A First Course (4e) © 2006 Prentice-Hall, Inc. Chap 11-1 Chapter 11 Chi-Square Tests Business Statistics, A First Course 4 th Edition.
Chapter 26: Comparing Counts AP Statistics. Comparing Counts In this chapter, we will be performing hypothesis tests on categorical data In previous chapters,
A random sample of 300 doctoral degree
Copyright © 2013 Pearson Education, Inc. All rights reserved Chapter 10 Inferring Population Means.
 2 test for independence Used with categorical, bivariate data from ONE sample Used to see if the two categorical variables are associated (dependent)
Chapter 11: Applications of Chi-Square. Chapter Goals Investigate two tests: multinomial experiment, and the contingency table. Compare experimental results.
Chapter 11 Chi-Square Procedures 11.3 Chi-Square Test for Independence; Homogeneity of Proportions.
AP Statistics Chapter 26 Notes
Chi-square test or c2 test
Chapter 26 Chi-Square Testing
A)For small degrees of freedom, the curve displays right-skewness. b) As the degrees of freedom increase, the curve approaches a normal curve. c)  2 is.
Chi-Square Procedures Chi-Square Test for Goodness of Fit, Independence of Variables, and Homogeneity of Proportions.
Other Chi-Square Tests
Chi-Square Distributions. Recap Analyze data and test hypothesis Type of test depends on: Data available Question we need to answer What do we use to.
+ Chi Square Test Homogeneity or Independence( Association)
BPS - 5th Ed. Chapter 221 Two Categorical Variables: The Chi-Square Test.
Chapter 14: Chi-Square Procedures – Test for Goodness of Fit.
Warm up On slide.
Other Chi-Square Tests
Chapter 13 Inference for Tables: Chi-Square Procedures AP Statistics 13 – Chi-Square Tests.
Copyright © 2010 Pearson Education, Inc. Slide
Inference for Distributions of Categorical Variables (C26 BVD)
© Copyright McGraw-Hill CHAPTER 11 Other Chi-Square Tests.
Test of Independence Lecture 43 Section 14.5 Mon, Apr 23, 2007.
Chapter Outline Goodness of Fit test Test of Independence.
1 Chapter 10. Section 10.1 and 10.2 Triola, Elementary Statistics, Eighth Edition. Copyright Addison Wesley Longman M ARIO F. T RIOLA E IGHTH E DITION.
11.2 Tests Using Contingency Tables When data can be tabulated in table form in terms of frequencies, several types of hypotheses can be tested by using.
Inferences Concerning Variances
Chapter 15 The Chi-Square Statistic: Tests for Goodness of Fit and Independence PowerPoint Lecture Slides Essentials of Statistics for the Behavioral.
Chapter 12 The Analysis of Categorical Data and Goodness of Fit Tests.
Chapter 13- Inference For Tables: Chi-square Procedures Section Test for goodness of fit Section Inference for Two-Way tables Presented By:
Lecture PowerPoint Slides Basic Practice of Statistics 7 th Edition.
CHAPTER INTRODUCTORY CHI-SQUARE TEST Objectives:- Concerning with the methods of analyzing the categorical data In chi-square test, there are 3 methods.
1 1 Slide © 2008 Thomson South-Western. All Rights Reserved Chapter 12 Tests of Goodness of Fit and Independence n Goodness of Fit Test: A Multinomial.
+ Section 11.1 Chi-Square Goodness-of-Fit Tests. + Introduction In the previous chapter, we discussed inference procedures for comparing the proportion.
11.1 Chi-Square Tests for Goodness of Fit Objectives SWBAT: STATE appropriate hypotheses and COMPUTE expected counts for a chi- square test for goodness.
Chapter 11: Categorical Data n Chi-square goodness of fit test allows us to examine a single distribution of a categorical variable in a population. n.
Class Seven Turn In: Chapter 18: 32, 34, 36 Chapter 19: 26, 34, 44 Quiz 3 For Class Eight: Chapter 20: 18, 20, 24 Chapter 22: 34, 36 Read Chapters 23 &
AP Statistics Chapter 13 Section 1. 2 kinds of Chi – Squared tests 1.Chi-square goodness of fit – extends inference on proportions to more than 2 proportions.
The Chi-Square Distribution  Chi-square tests for ….. goodness of fit, and independence 1.
Chapter 12 Lesson 12.2b Comparing Two Populations or Treatments 12.2: Test for Homogeneity and Independence in a Two-way Table.
Test of Goodness of Fit Lecture 41 Section 14.1 – 14.3 Wed, Nov 14, 2007.
Warm up On slide.
Chi-Square hypothesis testing
Chi-square test or c2 test
5.1 INTRODUCTORY CHI-SQUARE TEST
Lecture 18 Section 8.3 Objectives: Chi-squared distributions
AP Stats Check In Where we’ve been… Chapter 7…Chapter 8…
Chapter 11: Inference for Distributions of Categorical Data
Lecture 38 Section 14.5 Mon, Dec 4, 2006
Lecture 43 Sections 14.4 – 14.5 Mon, Nov 26, 2007
Chapter 13: Inference for Distributions of Categorical Data
Inference for Two Way Tables
Lecture 46 Section 14.5 Wed, Apr 13, 2005
Presentation transcript:

Inference for Categorical Data Chi-SquareCh.11

Facts about Chi-Square ► Takes only positive values and the graph is skewed to the right ► Test Statistic ( on AP sheet) ► Conditions: Expected cells are at least 5 and observations are based on a random sample.

3 types ► Goodness of Fit Test ► Test of Independence ► Homogeneity

Goodness of Fit Test ► Is used to determine how well a set of observed values matches a set of expected values.

Goodness of Fit Test ► 1 Categorical Variable ► 1 Population ► df=n-1 (n is the number of categories) ► Expected counts is equal to proportion of sample size ► Large Test statistic means more evidence against the null hypothesis

Chi-Square Goodness of Fit Test (Example from 5 Book pg 279) ► The following are the approximate percentages for the different blood types: A: 40 % B:11% AB: 4% O: 45% A random sample of 1000 black Americans yielded the following blood type data: A- 270, B-200, AB- 40 and O Does this sample provide evidence that the distribution of blood types among black Americans differs from that of white Americans or could the sample values simply be due to sampling variation? One categorical variable- blood type One population- black Americans

Example Continue ► We need to compare the observed values in the sample with the expected values we would get if the sample of black Americans really had the same distribution of blood types as white Americans. Blood Type Observe d Values Expected Values A270.40(1000) =400 B AB4040 O490450

Another example (yellow workbook pg 145) ► A Philadelphia newspaper report claims that 24.1 % of 18-to 24-year-olds who attend a local college are from Delaware, 15.4% are from New Jersey, 50.7% are from Pennsylvania, and the remaining 9.8% are from other states in the region. Suppose that a random sample (size 150) of 18-to-24 year olds is taken at the college and the number from each state/region is recorded.

Continue ► Suppose that a random sample (size 150) of 18-to-24 year olds is taken at the college and the number from each state/region is recorded. The following is our observed values StateNumber of Students Delaware30 New Jersey39 Pennsylvania71 Other10

Continue ► Do these data provide evidence at the α=.05 level that the newspaper report is correct? ► (Answer in workbook pg )

Test of Independence ► 1 Population ► 2 Categorical Variables ► df=( r-1)(c-1) Use matrix ► Null hypothesis: Two variables are independent in the population (not related) ► Alternate hypothesis: They are not independent in the population ( are related)

Example of Test of Independence (5 Book pg 284) ► A random sample of 400 residents of large western city are polled to determine their attitudes concerning the affirmative action admissions policy of the local university. The residents are classified according to ethnicity ( white, black, Asian) and whether or not they favor the affirmative action policy. The results are presented in the following table.

Attitude Toward Affirmative Action Favor Do Not Favor Total White Black Asian Total

Attitude towards Affirmative Action ► We are interested in whether or not, in this population of 400 citizens, ethnicity and attitude towards affirmative action are related ( we have 1 population and two categorical variables)

Another Example Test of Indep. (yellow workbook pg 150) ► A Survey was taken to determine if there is a relationship between students having computers in their homes and in their school divisions (elementary, middle, secondary). A random sample of size 250 produced the following results:

Continue- Computer in Home DivisionYesNo Elementary1461 Middle5025 Secondary8614

► Is there evidence that school division and having a home computer are independent? ► Use a.05 level of significance.

Test of Homogeneity of Proportion or Populations ► 1 Categorical Variable and 2 or more populations ► Degrees of freedom: (r-1)(c-1) same as independent test. ► Null Hypothesis: p1=p2…. ► Alternate Hypothesis: p1 does not equal p2…

Example of Homogeneity (5 Book pg 288) ► We have a random sample of 20 males from the population of males in the school and another independent, random sample of 16 females from the population of females in the school. Within each sample we classify the students as Democrat, Republican, and Independent. The results are presented in the following table.

Continue DemocratRepublican Indepen dent Total Male Female78116 Total

Continue ► We are asking if the proportions of Democrats, Republicans, and Independents are the same within the populations of Males and Females.

Another example: Test of Homogeneity (yellow wb pg 148) ► The table shows the number of Central High School students who passed the AP Calculus AB exam. Has the distribution of scores changed over the past 3 years? Give appropriate statistical evidence to support your answer.

ScoreYear 1Year 2Year

► Has there been a change in the distribution of passing grades on the AB Calculus exam over these three years?