I would like some assistance please. I am attempting to address the following questions:

2. Give each assumption and show it was met:

a.Durbin-Watson's (independence of error), what's the value and what does this mean?

b. The full ANOVA (was the test significant?)

c. VIF (to diagnose collinearity), what is the value and what does this mean?

d. Cooks distance (to test undue influence), what is the value and does this mean here?

e. Normal Distribution as per the histogram, explain what it means.

f.Heteroscedasticityand Linearity - thescatterplot,explain what both of these mean and how thescatterplotshows both.

3. Now, finish themultipleregression information:

a. The ANOVA hasalready been discussed, but re-mention to continue this analysis.

b. The R and R-squared and what they both mean.

c. The coefficient p-values and what this means and the overall coefficient equation.

4. Follow with abrief conclusion.

I'm struggling with my research question, is it fitting for this analysis? As well as having difficulity interpreting the coefficent's data in particular because I have not been confronted with a negative Beta in any of my analyses. However, is it correct to interpret this as If the beta coefficient is negative, the interpretation is that for every 1-unit increase in the predictor variable, the outcome variable willdecrease by the beta coefficient value?

Thanks in advance.

2. Give each assumption and show it was met: a. Durbin-Watson's (independence of error), what's the value and what does this mean? b. The full ANOVA (was the test significant?) c. VIF (to diagnose collinearity), what is the value and what does this mean? d. Cooks distance (to test undue influence), what is the value and does this mean here? e. Normal Distribution as per the histogram, explain what it means. f. Heteroscedasticity and Linearity - the scatterplot, explain what both of these mean and how the scatterplot shows both. 3. Now, finish the multiple regression information: a. The ANOVA has already been discussed, but re-mention to continue this analysis. b. The R and R-squared and what they both mean. c. The coefficient p-values and what this means and the overall coefficient equation. 4. Follow with a brief conclusion. RQ: Is there a significant difference in mean values between socioeconomic index, a higher level degree and occupational prestige score? Null Hypothesis: There is no significant difference in mean values between socioeconomic index, having a higher level degree and occupational prestige score. Alternative Hypothesis: There is a significant difference in mean values between socioeconomic index, having a higher level degree and occupational prestige score Coefficientsa Unstandardized Coefficients Std. B Error -14.631 2.016 1.260 .051 Standard ized Coefficie nts Model Beta t Sig. 1 (Constant) -7.256 .000 Rs occupational .724 24.688 .000 prestige score (2010) RS HIGHEST 3.446 .546 .185 6.307 .000 DEGREE a. Dependent Variable: R's socioeconomic index (2010) ANOVAa Sum of Mean Model Squares df Square F Sig. 1 Regressio 167504.6 2 83752.32 555.26 .000b n 52 6 0 Residual 72853.04 483 150.834 3 Total 240357.6 485 95 a. Dependent Variable: R's socioeconomic index (2010) b. Predictors: (Constant), RS HIGHEST DEGREE, Rs occupational prestige score (2010) Coefficientsa Unstandardized Coefficients Std. B Error -14.631 2.016 1.260 .051 Standard ized Coefficie nts Model Beta t Sig. 1 (Constant) -7.256 .000 Rs occupational .724 24.688 .000 prestige score (2010) RS HIGHEST 3.446 .546 .185 6.307 .000 DEGREE a. Dependent Variable: R's socioeconomic index (2010) Residuals Statisticsa Minimu m Maximu m Std. Mean Deviation N Predicted Value 8.982 99.989 46.606 18.5841 Std. Predicted -2.025 2.873 .000 1.000 Value Standard Error .578 1.786 .929 .262 of Predicted Value Adjusted 8.810 100.128 46.604 18.5844 Predicted Value Residual -36.0778 38.1547 .0000 12.2561 Std. Residual -2.938 3.107 .000 .998 Stud. Residual -2.952 3.116 .000 1.001 Deleted -36.4407 38.3914 .0013 12.3258 Residual Stud. Deleted -2.976 3.145 .000 1.003 Residual Mahal. Distance .078 9.261 1.996 1.781 Cook's Distance .000 .029 .002 .003 Centered .000 .019 .004 .004 Leverage Value a. Dependent Variable: R's socioeconomic index (2010) 486 486 486 486 486 486 486 486 486 486 486 486