A GEICO Direct magazine had an interesting article concerning the percentage of teenage motor vehicle deaths and the time of day. The following percentages.

Slides:



Advertisements
Similar presentations
Chi Squared Tests Hypothesis Tests for Linear Regression
Advertisements

Four girls soccer teams took a random sample of players regarding the number of goals scored per game. The results are below. Use a significance level.
Chapter 12 Goodness-of-Fit Tests and Contingency Analysis
A GEICO Direct magazine had an interesting article concerning the percentage of teenage motor vehicle deaths and the time of day. The following percentages.
Chapter 10 Chi-Square Tests and the F- Distribution 1 Larson/Farber 4th ed.
© 2010 Pearson Prentice Hall. All rights reserved Hypothesis Testing Using a Single Sample.
© 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.
Hypothesis Testing Steps of a Statistical Significance Test. 1. Assumptions Type of data, form of population, method of sampling, sample size.
Ch 15 - Chi-square Nonparametric Methods: Chi-Square Applications
11-2 Goodness-of-Fit In this section, we consider sample data consisting of observed frequency counts arranged in a single row or column (called a one-way.
The Kruskal-Wallis Test The Kruskal-Wallis test is a nonparametric test that can be used to determine whether three or more independent samples were.
Chi-square Goodness of Fit Test
Goodness of Fit Test for Proportions of Multinomial Population Chi-square distribution Hypotheses test/Goodness of fit test.
The Chi-Square Test Used when both outcome and exposure variables are binary (dichotomous) or even multichotomous Allows the researcher to calculate a.
The Chi-square Statistic. Goodness of fit 0 This test is used to decide whether there is any difference between the observed (experimental) value and.
Sections 8-1 and 8-2 Review and Preview and Basics of Hypothesis Testing.
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.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics S eventh Edition By Brase and Brase Prepared by: Lynn Smith.
1 Tests with two+ groups We have examined tests of means for a single group, and for a difference if we have a matched sample (as in husbands and wives)
EDRS 6208 Analysis and Interpretation of Data Non Parametric Tests
Overview Basics of Hypothesis Testing
1 Desipramine is an antidepressant affecting the brain chemicals that may become unbalanced and cause depression. It was tested for recovery from cocaine.
Section 10.1 Goodness of Fit. Section 10.1 Objectives Use the chi-square distribution to test whether a frequency distribution fits a claimed distribution.
Copyright © 2010, 2007, 2004 Pearson Education, Inc Chapter 11 Goodness of Fit Test (section 11.2)
Hypothesis Testing for Variance and Standard Deviation
Two Variable Statistics
Copyright © 2010, 2007, 2004 Pearson Education, Inc. 1.. Section 11-2 Goodness of Fit.
Chapter 9: Non-parametric Tests n Parametric vs Non-parametric n Chi-Square –1 way –2 way.
Chi-square test or c2 test
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics S eventh Edition By Brase and Brase Prepared by: Lynn Smith.
10.1: Multinomial Experiments Multinomial experiment A probability experiment consisting of a fixed number of trials in which there are more than two possible.
Copyright © 2010, 2007, 2004 Pearson Education, Inc Chapter 12 Analysis of Variance 12.2 One-Way ANOVA.
Chapter 11 Inference for Tables: Chi-Square Procedures 11.1 Target Goal:I can compute expected counts, conditional distributions, and contributions to.
Chi-Square Procedures Chi-Square Test for Goodness of Fit, Independence of Variables, and Homogeneity of Proportions.
The average work week for employees in an internet start up company is believed to be about 65 hours. A newly hired marketing employee hopes that it is.
Chi-Square Test.
Testing Hypothesis That Data Fit a Given Probability Distribution Problem: We have a sample of size n. Determine if the data fits a probability distribution.
Chapter 10 Chi-Square Tests and the F-Distribution
GOODNESS OF FIT Larson/Farber 4th ed 1 Section 10.1.
1 Chi-squared Test (1) H 0 : population follows distribution Divide the observations into k bins O i = observed frequency in i-th bin E i = expected frequency.
Section 10.2 Independence. Section 10.2 Objectives Use a chi-square distribution to test whether two variables are independent Use a contingency table.
Inference for Distributions of Categorical Variables (C26 BVD)
© Copyright McGraw-Hill CHAPTER 11 Other Chi-Square Tests.
Kruskal-Wallis H TestThe Kruskal-Wallis H Test is a nonparametric procedure that can be used to compare more than two populations in a completely randomized.
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.
A course is designed to increase mathematical comprehension. In order to evaluate the effectiveness of the course, students are given a test before and.
1 Hypothesis Testing Goodness-of-fit & Independence Chi-Squared Tests.
© Copyright McGraw-Hill 2004
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 11 Analyzing the Association Between Categorical Variables Section 11.2 Testing Categorical.
7.5 Hypothesis Testing for Variance and Standard Deviation Key Concepts: –The Chi-Square Distribution –Critical Values and Rejection Regions –Chi-Square.
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.
Statistics 300: Elementary Statistics Section 11-2.
Statistical Inference Drawing conclusions (“to infer”) about a population based upon data from a sample. Drawing conclusions (“to infer”) about a population.
Chapter 13- Inference For Tables: Chi-square Procedures Section Test for goodness of fit Section Inference for Two-Way tables Presented By:
Section 8-6 Testing a Claim about a Standard Deviation or Variance.
Chapter 14 – 1 Chi-Square Chi-Square as a Statistical Test Statistical Independence Hypothesis Testing with Chi-Square The Assumptions Stating the Research.
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.
11.2 – Chi-Square: Goodness of Fit. "Does the current distribution "fit" a past distribution?" H o : The percentage distribution for job incentives is.
Hypothesis Testing Steps for the Rejection Region Method State H 1 and State H 0 State the Test Statistic and its sampling distribution (normal or t) Determine.
Chapter 10 Section 5 Chi-squared Test for a Variance or Standard Deviation.
Chapter 18 Chi-Square Tests.  2 Distribution Let x 1, x 2,.. x n be a random sample from a normal distribution with  and  2, and let s 2 be the sample.
Statistics 300: Elementary Statistics Section 11-3.
Section 10.2 Objectives Use a contingency table to find expected frequencies Use a chi-square distribution to test whether two variables are independent.
CHI SQUARE DISTRIBUTION. The Chi-Square (  2 ) Distribution The chi-square distribution is the probability distribution of the sum of several independent,
Section 10.1 Goodness of Fit © 2012 Pearson Education, Inc. All rights reserved. 1 of 91.
Sun. Mon. Tues. Wed. Thurs. Fri. Sat.
Presentation transcript:

A GEICO Direct magazine had an interesting article concerning the percentage of teenage motor vehicle deaths and the time of day. The following percentages were given from a sample. Time % 12-3AM AM 8 6-9AM 8 9AM-noon 6 Noon-3PM PM PM 15 9PM-12AM 19

Is the percentage of teenage motor vehicle deaths the same for each time period? Conduct a hypothesis test at the 1% level. H o : The percent of teenage motor vehicle deaths is the same for each time period. H a : The percent of teenage motor vehicle deaths is not the same for each time period.

The table contains the observed (O) percentages. If the null hypothesis is true, the expected percentages (E) are 100% divided by 8 time periods or 12.5%. A Goodness-of-Fit Test is always right-tailed. The degrees of freedom (df) = n – 1 = 8 – 1 = 7

Distribution for the Test: Chi-Square Mean of the distribution = number of dfs = 7

Test statistic: 13.6 p-value: graph:

Decision: Do not reject the null hypothesis. Conclusion: We conclude that the percent of teenage motor vehicle deaths is the same for each time period.