Introduction to Statistics and Data Analysis
5th Edition
ISBN: 9781305750999
Author: Peck Olson Devore
Publisher: CENGAGE C
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Chapter 15.4, Problem 33E
To determine
Explain the reason that the individual effect of factor A or factor B is not interpretable when there is an AB interaction present.
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1. is the factor interaction significant? explain
A researcher wants to see if gender and / or income affects the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affects the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. Below is the data set followed by the results:
A researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help.
The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help.
He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis.
What do the results of this study mean to you?
Chapter 15 Solutions
Introduction to Statistics and Data Analysis
Ch. 15.1 - Give as much information as you can about the...Ch. 15.1 - Prob. 2ECh. 15.1 - Employees of a state university system can choose...Ch. 15.1 - The accompanying summary statistics for a measure...Ch. 15.1 - The authors of the paper Age and Violent Content...Ch. 15.1 - The paper referenced in the previous exercise also...Ch. 15.1 - The Paper Womens and Mens Eating Behavior...Ch. 15.1 - Can use of an online plagiarism-detection system...Ch. 15.1 - The experiment described in Example 15.4 also gave...Ch. 15.1 - Prob. 10E
Ch. 15.1 - Prob. 11ECh. 15.1 - Prob. 12ECh. 15.1 - In an experiment to investigate the performance of...Ch. 15.2 - Leaf surface area is an important variable in...Ch. 15.2 - Prob. 15ECh. 15.2 - Prob. 16ECh. 15.2 - Prob. 17ECh. 15.2 - The paper referenced in Exercise 15.5 described an...Ch. 15.2 - Prob. 19ECh. 15.2 - The accompanying data resulted from a flammability...Ch. 15.2 - Do lizards play a role in spreading plant seeds?...Ch. 15.2 - Samples of six different brands of diet or...Ch. 15.3 - A particular county employs three assessors who...Ch. 15.3 - The accompanying display is a partially completed...Ch. 15.3 - With the use of biofuels increasing, investigators...Ch. 15.3 - Prob. 26ECh. 15.3 - Prob. 27ECh. 15.3 - Prob. 28ECh. 15.4 - Prob. 29ECh. 15.4 - The paper Feedback Enhances the Positive Effects...Ch. 15.4 - The following graphs appear in the paper Which...Ch. 15.4 - The behavior of undergraduate students when...Ch. 15.4 - Prob. 33ECh. 15.4 - The following partially completed ANOVA table...Ch. 15.4 - Prob. 35ECh. 15.4 - Prob. 36ECh. 15.4 - Prob. 37ECh. 15 - Suppose that a random sample or size n = 5 was...Ch. 15 - Parents are frequently concerned when their child...Ch. 15 - Prob. 40CRCh. 15 - Consider the accompanying data on plant growth...Ch. 15 - Prob. 42CRCh. 15 - Prob. 43CRCh. 15 - Prob. 44CRCh. 15 - Prob. 45CRCh. 15 - Prob. 46CRCh. 15 - Prob. 47CRCh. 15 - Prob. 48CRCh. 15 - Prob. 49CR
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- Explain the differences between Gaussian elimination and Gauss-Jordan elimination.arrow_forwardA researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. What is the null hypothesis?arrow_forwardA researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. Is there significance for either gender or income?arrow_forward
- A researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. What is one research hypothesis (there are three possible hypotheses here – name them all if you can.arrow_forwardA researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. what is the significance of the interaction of gender and income?arrow_forwardA researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. What is one research hypothesis (there are three possible hypotheses here name them all if you can but naming at least one is required)?arrow_forward
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