What df1 for the interaction between gender and age is:1. 12. 23. 34. 5 **Between-Subjects Factors**This table presents the categorical variables included in the analysis. - **Gender:** - Value Label 0: Female (N = 365) - Value Label 1: Male (N = 122)- **Age in Years:** - Value Label 1: 18-42 years (N = 219) - Value Label 2: 43-67 years (N = 124) - Value Label 3: 68-89 years (N = 143) - Value Label 92: 92 years (N = 1)**Tests of Between-Subjects Effects**This section summarizes the results of the analysis of variance (ANOVA) testing different effects on the dependent variable, Stroop Test.- **Corrected Model:** - Type III Sum of Squares: 8424.288 - Degrees of Freedom (df): 6 - Mean Square: 1404.048 - F-value: 31.273 - Significance (Sig.): <.001 - **Intercept:** - Type III Sum of Squares: 5094.582 - df: 1 - Mean Square: 5094.582 - F-value: 113.475 - Sig.: <.001 - **Gender1 (Main Effect of Gender):** - Type III Sum of Squares: 304.358 - df: 1 - Mean Square: 304.358 - F-value: 6.779 - Sig.: .010- **Age1 (Main Effect of Age):** - Type III Sum of Squares: 7571.542 - df: 3 - Mean Square: 2523.847 - F-value: 56.215 - Sig.: <.001- **Gender1 * Age1 (Interaction Effect):** - Type III Sum of Squares: 554.294 - df: 2 - Mean Square: 277.147 - F-value: 6.173 - Sig.: .002- **Error:** - Type III Sum of Squares: 21550.175 - df: 480 - Mean Square: 44.896- **Total:**

From the given output, the df for interaction between gender and age is 2.

Answered: What df1 for the interaction between…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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You are testing the claim that the proportion of men who own cats is larger than the proportion of women who own cats.You sample 150 men, and 80% own cats.You sample 190 women, and 55% own cats.Find p¯ (p-bar), as a decimal, rounded to two decimal places.
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Use the following information to answer the next two exercises. A new AIDS prevention drug was tried on a group of 224 HIV positive patients. Forty-five patients developed AIDS after four years. In a control group of 224 HIV positive patients, 68 developed AIDS after four years. We want to test whether the method of treatment reduces the proportion of patients that develop AIDS after four years or if the proportions of the treated group and the untreated group stay the same. Using HA: P₁ P2 <0 as the alternative hypothesis, an alpha level of P1 0.01, and the p-value you found in the previous problem, form a α - conclusion. If the drug made no difference, there was only a 1.6% chance of finding the sample proportions we did. While this is very unlikely, the high medical standards when working with humans generally requires less than 1%, so the evidence was not statistically significant enough to determine that the drug works. If the drug made no difference, there was only a 0.8% chance…
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