Multiple Regression

Please Read the following and answer the questions at the end of the scenario.

What is your research question?  Is there a significant relationship between socioeconomic status, occupational prestige and owning or renting a home?

What is the null hypothesis for your question?  A person’s socioeconomic status has no significance to occupational prestige and owning or renting a home.

What research design would align with this question?  Non-experimental would be the research design I would use.  Comparative research would aide in determining the significance between the variables.

What dependent variable was used and how is it measured?  Socioeconomic status was the dependent variable.  The measure is socioeconomic index of the respondent and measured on an interval scale.

What independent variable is used and how is it measured?  The independent variables used are occupational prestige and does the respondent own or rent home.  The occupational prestige score reflects the occupational prestige of the respondent. The occupational prestige is measured on an interval scale while the respondent owning or renting is measured nominally.

What other variables were added to the multiple regression models as controls?  All requested variables were entered for the multiple regression model and none were removed.

Regression

Variables Entered/Removeda

Model

Variables Entered

Variables Removed

Method

1

DOES R OWN OR RENT HOME?, Rs

Occupational Prestige Score (2010)b

.

Enter

a. Dependent Variable: R’s socioeconomic index (2010)

b. All requested variables entered.

Model Summary:  The R square and adjusted r square is .701.  This means that 70% of the variability in a respondent’s socioeconomic status index is explained by the two independent variables which is occupational prestige and does respondent own or rent home.

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.837a

.701

.701

12.3547

a. Predictors: (Constant), DOES R OWN OR RENT HOME?, Rs occupational prestige score (2010)

ANOVA: The model is significant because it measures .000 which is well below the .05 conventional threshold meaning that the model does have statistical significance

ANOVAa

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

572398.452

2

286199.226

1875.020

.000b

Residual

244220.710

1600

152.638

Total

816619.161

1602

a. Dependent Variable: R’s socioeconomic index (2010)

b. Predictors: (Constant), DOES R OWN OR RENT HOME?, Rs occupational prestige score (2010)

Coefficients:  Under this analysis the constant is serving as a mathematical anchor where the regression line crosses the Y-axis.  This means that for every 1 unit increase for the occupational prestige, their socioeconomic status index value will change by 1.354 units controlling the respondent renting or owning home.  For every respondent renting or owning home the respondent’s socioeconomic status index will change by -3.268 units controlling for occupational prestige score.  .000 for both independent variables is below the .05 threshold therefore the null hypothesis is rejected meaning there is no relationship between the two independent variables and dependent variable.  Also, both are statistically significant predictors of the respondent’s socioeconomic status index.  The BETA which falls under the standardized coefficient is when one or more predictors’ variables are measured at different units of analysis than your other predictors (Laureate, 2016g).  So for every 1 unit increase for every 1 standard deviation, an increase in the respondent’s occupational prestige score along with the socioeconomic status index, the dependent variable, will change by .819 standard deviations controlling respondent’s owning or renting home.  The respondent’s occupational prestige score, owning or renting home are together significant predictors of socioeconomic status index.

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

-8.354

1.478

-5.653

.000

Rs occupational prestige score (2010)

1.354

.023

.819

58.604

.000

DOES R OWN OR RENT HOME?

-3.268

.611

-.075

-5.349

.000

a. Dependent Variable: R’s socioeconomic index (2010)

 

Respond to post and comment on the following:

1. Do you think the variables are appropriately used? Why or why not?
2. Does the addition of the control variables make sense to you? Why or why not?
3. Does the analysis answer the research question? Be sure and provide constructive and helpful comments for possible improvement.
4. If there was a significant effect, comments on the strength and its meaningfulness.
5. As a lay reader, were you able to understand the results and their implications? Why or why not?