Task B: Multiple regression (18%)

In a follow-up study, the researchers decided to investigate the factors that affect the number of years participants in their random sample of Australian adult workers are employed at a company. The researchers included the following predictors in their model: work satisfaction, years of tertiary education and sex. Using the,https://www.dropbox.com/s/cvuawpxos8fn8p6/Assignment%202%20-%20Workbook%201%20Data%20File.sav?dl=0run a multiple regression to address this scenario and answer the following questions:

• From the raw correlations table, which of the predictors were significantly related to the dependent variable? Quote relevant statistics.
• Give the regression equation for the number of years spent working for a company (to two decimal places).
• Use the regression equation to predict the number of years spent working for a company for a male who has a work satisfaction score of 40 and 4 years of tertiary education.
• Interpret the partial regression coefficient for work satisfaction.
• What was the most important predictor in this regression? Quote relevant statistics.
• When all of the predictors are taken into account, what predictors contributed significantly to the multiple regression? Quote relevant statistics.
• Is the value of Multiple R significant? What does this tell us? Quote relevant statistics.
• How much of the variation in the number of years spent working for a companycan be explained by this linear model?

In addition, consider the following notes:

• Note 1: Assume all assumptions have been met.
• N