9 May 2022

76

Estimating Models Using Dummy Variables

Format: APA

Academic level: High School

Paper type: Coursework

Words: 284

Pages: 1

Downloads: 0

For this research scenario, the independent variable is the Rs occupational standing score. For the independent variables, I used the age of respondents and highest completed school year, and an American citizenship categorized dummy variable as 1 (for yes), 2 (for no), and 0 (for otherwise). I intend to discover whether highest school year completed, the dummy variable and the age of the respondents are essential for determining Rs occupational standing score. In addition to that, what is the influence on Rs professional standing score with a unit increase in highest school year completed, American citizenship, and the respondent age?

Coefficients interpretation and significance

With the p-value lower than the (0.05) alpha, the coefficient of respondent age and highest school years completed. However, with the p-value more significant than the (0.05) alpha no and yes is not substantial. With a unit increase within the highest school years completed, is an increase of 2.324 units in Rs occupational standing score. With a unit increase within the respondent age, an increase of 0.112 units is experienced in Rs professional standing score. Rs occupational standing score is .335 units lower on an average for the American citizens compared to others. Moreover, the Rs professional standing score is 2.487 units more for American citizens on an average compared to others.

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Output

Correlations

 

Rs occupational prestige score (2010)

AGE OF RESPONDENT

HIGHEST YEAR OF SCHOOL COMPLETED

yes

no

Rs occupational prestige score (2010) Pearson Correlation

1

.126**

.514**

.028

-.077**

Sig. (2-tailed)  

.000

.000

.165

.000

N

2427

2421

2426

2427

2427

AGE OF RESPONDENT Pearson Correlation

.126**

1

-.014

.036

-.083**

Sig. (2-tailed)

.000

 

.479

.068

.000

N

2421

2529

2528

2529

2529

HIGHEST YEAR OF SCHOOL COMPLETED Pearson Correlation

.514**

-.014

1

.088**

-.201**

Sig. (2-tailed)

.000

.479

 

.000

.000

N

2426

2528

2537

2537

2537

yes Pearson Correlation

.028

.036

.088**

1

-.172**

Sig. (2-tailed)

.165

.068

.000

 

.000

N

2427

2529

2537

5054

5054

no Pearson Correlation

-.077**

-.083**

-.201**

-.172**

1

Sig. (2-tailed)

.000

.000

.000

.000

 
N

2427

2529

2537

5054

5054

**. at the 0.01 level, the correlation is significant (2-tailed).

Variables Entered/Removeda

Model

Variables Entered

Variables Removed

Method

1 no, AGE OF RESPONDENT, yes, HIGHEST YEAR OF SCHOOL COMPLETEDb

.

Enter
a. Dependent Variable: Rs occupational prestige score (2010)
b. All requested variables entered.

References

Frankfort-Nachmias, C., & Leon-Guerrero, A. (2015). Social statistics for a diverse society (7th ed.). Thousand Oaks, CA: Sage Publications.

Walden University Library. (n.d.). Course Guide and Assignment Help for RSCH 8210. Retrieved from http://academicguides.waldenu.edu/rsch8210

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Reference

StudyBounty. (2023, September 15). Estimating Models Using Dummy Variables.
https://studybounty.com/51570-estimating-models-using-dummy-variables-coursework

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