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Suppose you ask the same question of four times as many people, but the proportions remain the same. The new results are shown in the 2 x 2 data matrix below: Observed Frequencies Color Preference Red Yellow Female 212 120 Male 80 188 The x2 test statistic for the chi-square test of independence would now be 68.64, and the phi-coefficient would be Thus, when we change the sample size without changing the proportions, the does not change, but the does.

Suppose you ask the same question of four times as many people, but the proportions remain the same. The new results are shown in the 2 x 2 data matrix below: Observed Frequencies Color Preference Red Yellow Female 212 120 Male 80 188 The x2 test statistic for the chi-square test of independence would now be 68.64, and the phi-coefficient would be Thus, when we change the sample size without changing the proportions, the does not change, but the does.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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For the blanks on this sentence: "The χ² test statistic for the chi-square test of independence would now be 68.64, and the phi-coefficient would be(blank1)    . Thus, when we change the sample size without changing the proportions, the (blank 2)    does not change, but the (blank 3)   does." 

Blank 2 options: "chi-square test statistic" or "significance of the association" or "strength of the association" 

Blank 3 options: "phi-coefficient" or significance of the association" or "strength of the association" 

Suppose you ask the same question of four times as many people, but the proportions remain the same. The new results are shown in the 2 x 2 data matrix below: Observed Frequencies Color Preference Red Yellow Female 212 120 Male 80 188 The x2 test statistic for the chi-square test of independence would now be 68.64, and the phi-coefficient would be Thus, when we change the sample size without changing the proportions, the does not change, but the does. Now, suppose you conduct a slightly different study. Instead of looking at the difference between the preferences of males and females for two colors, you classify your 250 respondents into four categories: male child, female child, male adult, and female adult. You also decide to look at differences in preferences for five (5) colors: red, yellow, green, blue, and purple. The x² test statistic for the chi-square test of independence is 99.45, and Cramer's V would be According to Cohen's guidelines, the value for the Cramer's V indicates effect.
Transcribed Image Text:Suppose you ask the same question of four times as many people, but the proportions remain the same. The new results are shown in the 2 x 2 data matrix below: Observed Frequencies Color Preference Red Yellow Female 212 120 Male 80 188 The x2 test statistic for the chi-square test of independence would now be 68.64, and the phi-coefficient would be Thus, when we change the sample size without changing the proportions, the does not change, but the does. Now, suppose you conduct a slightly different study. Instead of looking at the difference between the preferences of males and females for two colors, you classify your 250 respondents into four categories: male child, female child, male adult, and female adult. You also decide to look at differences in preferences for five (5) colors: red, yellow, green, blue, and purple. The x² test statistic for the chi-square test of independence is 99.45, and Cramer's V would be According to Cohen's guidelines, the value for the Cramer's V indicates effect.
Which of the following statements are correct about the phi-coefficient? Check all that apply. It is a measure of correlation between two dichotomous variables. It can be used as a measure of the strength of a relationship between two dichotomous variables. It is a measure of correlation between a dichotomous variable and a continuous variable. It can be used as a measure of the significance of a relationship between two dichotomous variables. Suppose you are looking at the relationship between gender and color preference. You wonder if there is a difference between the preferences of males and females for red and yellow. You conduct a quick survey asking different people which color they prefer. The results are shown in the 2 x 2 data matrix below: Observed Frequencies Color Preference Red Yellow Female 53 30 Male 20 47 The x2 test statistic for the chi-square test for independence is 17.16. The phi-coefficient is According to Cohen's guidelines, the value for the phi-coefficient indicates effect.
Transcribed Image Text:Which of the following statements are correct about the phi-coefficient? Check all that apply. It is a measure of correlation between two dichotomous variables. It can be used as a measure of the strength of a relationship between two dichotomous variables. It is a measure of correlation between a dichotomous variable and a continuous variable. It can be used as a measure of the significance of a relationship between two dichotomous variables. Suppose you are looking at the relationship between gender and color preference. You wonder if there is a difference between the preferences of males and females for red and yellow. You conduct a quick survey asking different people which color they prefer. The results are shown in the 2 x 2 data matrix below: Observed Frequencies Color Preference Red Yellow Female 53 30 Male 20 47 The x2 test statistic for the chi-square test for independence is 17.16. The phi-coefficient is According to Cohen's guidelines, the value for the phi-coefficient indicates effect.
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