SPSS was used to analyze the data from the 2014 General Social Survey data set which reveals both hours watching TV and time spent on the internet during the week affect your socioeconomic status.
The Model Summary of the Multiple Linear Regression tests reveals that 40% of socioeconomic statuses are explained by the two independent variables; hours spent watching TV and time spent on the internet. The ANOVA test has a significance of .000, below the .05 alpha level indicating the rejection of the null that there is no relationship between variables.
Nonetheless, analyzing the unstandardized coefficients reveals for every unit increase of hours per day watching TV, SES will decrease by 1.668 units. For every unit increase in internet hours per week, SES will increase by .130 units. The significance of each independent variable is statistically significant at the .01 alpha level and are statistically significant predictors of SES. Thus, in laymen terms, the more you watch TV, the less money you will make and the more time you spend on the internet, the more money you will make. However, there are multiple influences that affect hours spent on the internet, some beneficial to income, some not.