Statistical Program for the Social Sciences

Module 5 Problem Set
Student’s Name
Institutional Affiliation
Module 5 Problem Set
BANK.SAV
1 Suppose you were interested in understanding how an employee’s demographic characteristics, beginning salary, and time at the bank and in the workforce were related to the current salary. Below were the scatterplots of Salberg, sex, time, age, edlevel, and work with salnow where;
* Salbeg stands for a beginning salary
* Sex for sex of an employee
* Time for job seniority
* Age for the age of an employee
* Edlevel for educational level
* Work for work experience
A scatterplot of Salberg with salnow
A scatterplot of sex with salnow
A scatterplot of time with salnow
A scatterplot of age with salnow
A scatterplot of edlevel with salnow
A scatterplot of work with salnow
2 The scatterplots prove the presence of positive and negative relationships between each selected variable and salnow. All relationships except sex and edlevel appeared linear. Only salbeg, time, and edlevel had positive relationships while age, sex, and work had negative relationships with salnow. Of strong relationships, time and age had the strongest ones, positive and negative, respectively.
3 There were significant correlations with salnow noted on 5 variables. These were; salbeg (r = 0.88, p <0.05), sex (r =-0.45, p <0.001), age (r = -0.146, p <0.001), edlevel (r = 0.661, p <0.001), and work (r = -0.097, p <0.05). The largest correlation in absolute value with salnow was 0.88 by salbeg. Only time had an insignificant correlation with salnow (r = 0.084, p <0.001). The correlation values matched the scatterplots findings on positive and negative relationships between each selected variable with salnow.
Correlations



Current salary

Beginning salary


Pearson Correlation

.880**



Sig. (2-tailed)

.000



N

474

Sex of employee


Pearson Correlation

-.450**



Sig. (2-tailed)

.000



N

474

Job seniority


Pearson Correlation

.084



Sig. (2-tailed)

.067



N

474

Age of employee


Pearson Correlation

-.146**



Sig. (2-tailed)

.001



N

474

Current salary


Pearson Correlation

1



Sig. (2-tailed)




N

474

Educational level


Pearson Correlation

.661**



Sig. (2-tailed)

.000



N

474

Work experience


Pearson Correlation

-.097*



Sig. (2-tailed)

.034



N

474

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

*. Correlation is significant at the 0.05 level (2-tailed).

CENSUS.SAV
1 First, a scatterplot of educ with income06 was plotted and a fit line superimposed.
A scatterplot of educ with income06
The relationship seemed linear and positive. That is, an increase in educ would result to an increase in income06. Later a linear ...