Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics S eventh Edition By Brase and Brase Prepared by: Lynn Smith.

Slides:



Advertisements
Similar presentations
CHI-SQUARE(X2) DISTRIBUTION
Advertisements

15- 1 Chapter Fifteen McGraw-Hill/Irwin © 2005 The McGraw-Hill Companies, Inc., All Rights Reserved.
Chi Square Example A researcher wants to determine if there is a relationship between gender and the type of training received. The gender question is.
The Chi-Square Test for Association
Hypothesis Testing IV Chi Square.
Statistical Inference for Frequency Data Chapter 16.
Chapter 13: The Chi-Square Test
© 2010 Pearson Prentice Hall. All rights reserved The Chi-Square Test of Independence.
PSY 340 Statistics for the Social Sciences Chi-Squared Test of Independence Statistics for the Social Sciences Psychology 340 Spring 2010.
Irwin/McGraw-Hill © The McGraw-Hill Companies, Inc., 2000 LIND MASON MARCHAL 1-1 Chapter Thirteen Nonparametric Methods: Chi-Square Applications GOALS.
Ch 15 - Chi-square Nonparametric Methods: Chi-Square Applications
Chi-Square and F Distributions Chapter 11 Understandable Statistics Ninth Edition By Brase and Brase Prepared by Yixun Shi Bloomsburg University of Pennsylvania.
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.
Cross Tabulation and Chi-Square Testing. Cross-Tabulation While a frequency distribution describes one variable at a time, a cross-tabulation describes.
Copyright © Cengage Learning. All rights reserved. 11 Applications of Chi-Square.
The table shows a random sample of 100 hikers and the area of hiking preferred. Are hiking area preference and gender independent? Hiking Preference Area.
HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Section 10.7.
Chi-Square as a Statistical Test Chi-square test: an inferential statistics technique designed to test for significant relationships between two variables.
Chapter 9: Non-parametric Tests n Parametric vs Non-parametric n Chi-Square –1 way –2 way.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics S eventh Edition By Brase and Brase Prepared by: Lynn Smith.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics S eventh Edition By Brase and Brase Prepared by: Lynn Smith.
Chi-Square X 2. Parking lot exercise Graph the distribution of car values for each parking lot Fill in the frequency and percentage tables.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics S eventh Edition By Brase and Brase Prepared by: Lynn Smith.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics S eventh Edition By Brase and Brase Prepared by: Lynn Smith.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics S eventh Edition By Brase and Brase Prepared by: Lynn Smith.
Business Statistics: A First Course, 5e © 2009 Prentice-Hall, Inc. Chap 11-1 Chapter 11 Chi-Square Tests Business Statistics: A First Course Fifth Edition.
Section 10.2 Independence. Section 10.2 Objectives Use a chi-square distribution to test whether two variables are independent Use a contingency table.
© Copyright McGraw-Hill CHAPTER 11 Other Chi-Square Tests.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics Seventh Edition By Brase and Brase Prepared by: Lynn Smith.
Chapter Outline Goodness of Fit test Test of Independence.
The table shows a random sample of 100 hikers and the area of hiking preferred. Are hiking area preference and gender independent? Hiking Preference Area.
Chapter 11: Chi-Square  Chi-Square as a Statistical Test  Statistical Independence  Hypothesis Testing with Chi-Square The Assumptions Stating the Research.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics S eventh Edition By Brase and Brase Prepared by: Lynn Smith.
July, 2000Guang Jin Statistics in Applied Science and Technology Chapter 12. The Chi-Square Test.
Copyright © Cengage Learning. All rights reserved. Chi-Square and F Distributions 10.
Section 12.2: Tests for Homogeneity and Independence in a Two-Way Table.
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 11 Analyzing the Association Between Categorical Variables Section 11.2 Testing Categorical.
Sec 8.5 Test for a Variance or a Standard Deviation Bluman, Chapter 81.
Chapter 11: Additional Topics Using Inferences 11.1 – Chi-Square: Tests of Independence 11.2 – Chi-Square: Goodness of Fit 11.3 – Testing a Single Variance.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics Seventh Edition By Brase and Brase Prepared by: Lynn Smith.
Understanding Basic Statistics Fourth Edition By Brase and Brase Prepared by: Lynn Smith Gloucester County College Chapter Nine Hypothesis Testing.
Chapter Fifteen Chi-Square and Other Nonparametric Procedures.
Chapter 14 – 1 Chi-Square Chi-Square as a Statistical Test Statistical Independence Hypothesis Testing with Chi-Square The Assumptions Stating the Research.
Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.
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.
Chapter 10 Section 5 Chi-squared Test for a Variance or Standard Deviation.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 The P Value The P value is the smallest level of significance for which the observed.
Statistics 300: Elementary Statistics Section 11-3.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics S eventh Edition By Brase and Brase Prepared by: Lynn Smith.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics Seventh Edition By Brase and Brase Prepared by: Lynn Smith.
Section 10.2 Objectives Use a contingency table to find expected frequencies Use a chi-square distribution to test whether two variables are independent.
Statistics for Psychology CHAPTER SIXTH EDITION Statistics for Psychology, Sixth Edition Arthur Aron | Elliot J. Coups | Elaine N. Aron Copyright © 2013.
Chi Square Chi square is employed to test the difference between an actual sample and another hypothetical or previously established distribution such.
Test of independence: Contingency Table
Chi-Square hypothesis testing
10 Chapter Chi-Square Tests and the F-Distribution Chapter 10
Chapter Fifteen McGraw-Hill/Irwin
Community &family medicine
Qualitative data – tests of association
1) A bicycle safety organization claims that fatal bicycle accidents are uniformly distributed throughout the week. The table shows the day of the week.
Consider this table: The Χ2 Test of Independence
Chi-Square and F Distributions
Chapter 10 Analyzing the Association Between Categorical Variables
CHI SQUARE TEST OF INDEPENDENCE
HYPOTHESIS TESTS ABOUT THE MEAN AND PROPORTION
Analyzing the Association Between Categorical Variables
Copyright © Cengage Learning. All rights reserved.
Chapter Outline Goodness of Fit test Test of Independence.
Quadrat sampling & the Chi-squared test
Quadrat sampling & the Chi-squared test
Presentation transcript:

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics S eventh Edition By Brase and Brase Prepared by: Lynn Smith Gloucester County College Chapter Eleven Part 1 (Section 11.1) Chi-Square and F Distributions

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 2 The Chi-Square Distribution The  2 Distribution is not symmetrical and depends on the number of degrees of freedom.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 3  is the Greek Letter Chi.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 4 The  2 Distribution for d.f. = n

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 5 The  2 Distribution for d.f. = n d.f. = 3

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 6 The  2 Distribution for d.f. = n d.f. = 3 d.f. = 5

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 7 The mode or high point occurs over n – 2 for n  n d.f. = 10 d.f. = 3 d.f. = 5

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 8 As the degrees of freedom increase, the graphs looks more bell-like and symmetric n d.f. = 3 d.f. = 10 d.f. = 5

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 9 Use Table 7 in Appendix II to find Critical Values of  2 Distributions

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 10 Area in the Right Tail of the Distribution =   22

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 11 Use Table 7 (with d.f. = 8) to find the area to the right of  2 =  =

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 12 Chi Square: Tests of Independence To test the independence of two factors, use a contingency table.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 13 Contingency Table

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 14 Shaded boxes (called “cells”) will contain frequencies.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 15 Horizontal lines of cells are called rows.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 16 Vertical lines of cells are called columns.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 17 The size of a table is given as row X column.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 18 This is a 3 X 3 contingency table.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 19 This is a 3 X 2 contingency table.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 20 This is a 2 X 3 contingency table.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 21 When giving the size of a contingency table, Always give the number of rows first.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 22 Suppose we wish to determine (at 5% level of significance) if the time it takes to complete a given task is independent of gender.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 23 Number and gender of individuals who completed a task in the times indicated.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 24 To test the null hypothesis that gender and the time it takes to complete the task are independent: H 0 :Variables are independent. H 1 :Variables are not independent. Use the null hypothesis to determine the expected frequency of each cell.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 25 Expected Frequency

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 26 Finding the Expected Frequencies E = (Row total)(Column total) Sample size Sample size

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 27 Finding the Expected Frequencies E = (Row total)(Column total) sample size Sample size

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 28 Finding the Expected Frequencies E = (Row total)(Column total) sample size

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 29 Finding the Expected Frequencies E = (Row total)(Column total) sample size

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 30 Finding the Expected Frequencies E = (Row total)(Column total) sample size

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 31 Finding the Expected Frequencies E = (Row total)(Column total) sample size

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 32 Finding the Expected Frequencies E = (Row total)(Column total) sample size

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 33 The actual frequency which occurred is called the observed frequency, O.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 34 The Sample Statistic  2 Chi square is a measure of the sum of the differences between observed frequency O and expected frequency E in each cell.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 35 Difference Between Observed and Expected Frequencies

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 36 The Sum of the (O – E) Column Will Equal Zero.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 37 To calculate Chi Square, we use the values (O – E) 2 /E To reflect the magnitude of the differences between the observed and expected frequencies. To reflect the fact that the small difference between the observed and expected frequencies is more important when the expected frequency is small.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 38 Computing  2

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 39 Degrees of Freedom d.f. = (R – 1)(C – 1) R = number of cell rows C = number of cell columns

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 40 For our example: R = 2, C = 3 d.f. = (2 – 1)(3 – 1) = 2

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 41 Using d.f. = 2 and  = 0.05, find the critical value of  2 from Table 7.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 42 If the sample statistic is larger than the critical value, reject the null hypothesis of independence. In our example, the sample statistic  2 = The critical value = 5.99.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 43 Conclusion Reject the null hypothesis of independence. We conclude that the time it takes to complete the task is not independent of gender.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 44 P Value Approach In our example, the sample statistic  2 = For d.f. = 2, the sample statistic  2 = falls between 9.21 and (the critical values for  =.010 and.005 respectively). We conclude that < P < We would reject H 0 for any   P. We, therefore reject H 0 for  = 0.05.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 45 In order to safely use the critical values of  2 from Table 7, we must assure that all expected frequencies are greater than or equal to five. If this condition is not met, the sample size should be increased.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 46 Using Chi-Square Distribution to Test the Independence of Two Variables Set up the hypotheses H 0 :The variables are independent. H 1 :The variables are not independent. Compute the expected frequency for each cell in the contingency table.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 47 Using Chi-Square Distribution to Test the Independence of Two Variables Compute the statistic  2 for the sample.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 48 Using Chi-Square Distribution to Test the Independence of Two Variables Find the critical value   2 in Table 7. Use the level of significance  and degrees of freedom: d.f. = (R – 1)(C – 1) where R and C are the numbers of rows and columns of cells. The critical region = all values of  2 to the right of the critical value   2.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 49 Using Chi-Square Distribution to Test the Independence of Two Variables Compare the sample statistic  2 with the critical value   2. If the sample statistic is larger than the critical value, reject the null hypothesis of independence. Otherwise, do not reject the null hypothesis.