I need help with these questions 1. do the covariates and factors interact?2. can you conclude a homogeneity of regression slopes?3. can you conclude homogeneity of variance? **Tests of Between-Subjects Effects****Dependent Variable:** rincom2| Source | Type III Sum of Squares | df | Mean Square | F | Sig. ||-------------------|-------------------------|-----|-------------|---------|-------|| Corrected Model | 2344.328\(^a\) | 5 | 468.866 | 32.346 | .000 || Intercept | 78765.010 | 1 | 78765.010 | 5433.786| .000 || sex | 733.137 | 1 | 733.137 | 50.577 | .000 || degree | 1598.765 | 4 | 399.691 | 27.574 | .000 || Error | 9856.886 | 680 | 14.495 | | || Total | 150407.000 | 686 | | | || Corrected Total | 12201.214 | 685 | | | |**Explanation:**This table presents a statistical analysis of the effects of different factors (such as sex and degree) on a dependent variable, `rincom2`. The analysis uses an ANOVA (Analysis of Variance) approach.- **Corrected Model**: This row summarizes the overall effect of the independent variables. The sum of squares is 2344.328 with 5 degrees of freedom, leading to a mean square of 468.866 and an F-value of 32.346, which is statistically significant at the .000 level. - **Intercept**: This measures the mean effect across all factors, with a very large sum of squares (78765.010) and is also significant.- **sex**: The effect of sex on the dependent variable is statistically significant, with a sum of squares of 733.137 and an F-value of 50.577.- **degree**: The degrees have a significant impact as well, with a sum of squares of 1598.765 and an F-value of 27.574.- **Error**: Represents the variation within groups, with a sum square of 9856.886 and 680 degrees of freedom, indicating the unexpl

Answered: I need help with these questions 1.…

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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Question

I need help with these questions

1. do the covariates and factors interact?

2. can you conclude a homogeneity of regression slopes?

3. can you conclude homogeneity of variance?

**Tests of Between-Subjects Effects**

**Dependent Variable:** rincom2

| Source | Type III Sum of Squares | df | Mean Square | F | Sig. |
|-------------------|-------------------------|-----|-------------|---------|-------|
| Corrected Model | 2344.328\(^a\) | 5 | 468.866 | 32.346 | .000 |
| Intercept | 78765.010 | 1 | 78765.010 | 5433.786| .000 |
| sex | 733.137 | 1 | 733.137 | 50.577 | .000 |
| degree | 1598.765 | 4 | 399.691 | 27.574 | .000 |
| Error | 9856.886 | 680 | 14.495 | | |
| Total | 150407.000 | 686 | | | |
| Corrected Total | 12201.214 | 685 | | | |

**Explanation:**

This table presents a statistical analysis of the effects of different factors (such as sex and degree) on a dependent variable, `rincom2`. The analysis uses an ANOVA (Analysis of Variance) approach.

- **Corrected Model**: This row summarizes the overall effect of the independent variables. The sum of squares is 2344.328 with 5 degrees of freedom, leading to a mean square of 468.866 and an F-value of 32.346, which is statistically significant at the .000 level.

- **Intercept**: This measures the mean effect across all factors, with a very large sum of squares (78765.010) and is also significant.

- **sex**: The effect of sex on the dependent variable is statistically significant, with a sum of squares of 733.137 and an F-value of 50.577.

- **degree**: The degrees have a significant impact as well, with a sum of squares of 1598.765 and an F-value of 27.574.

- **Error**: Represents the variation within groups, with a sum square of 9856.886 and 680 degrees of freedom, indicating the unexpl

Definition Definition Measure of how two random variables change together. Covariance indicates the joint variability or the directional relationship between two variables. When two variables change in the same direction (i.e., if they either increase or decrease together), they have a positive covariance. When the change is in opposite directions (i.e., if one increases and the other decreases), the two variables have a a negative covariance.

Expert Solution

Step 1: Overview

Given is an ANOVA table for the regression of rincom2 on sex and degree. From the output, it is evident that all the p-values (Sig.) are 0. It means that:

Overall model is significant in predicting rincom2 from the given factors.
Sex has significant effect on rincom2 or the value of rincom2 is significantly different b/w males and females.
Degree has significant effect on rincom2 or the value of rincom2 is significant for different level of degree.