DS 212 Regression Analysis Extra Credit Assignment
1. Download the data set “SIMPLE_REGRESSION_SALARY_VS_YEARS_EMPLOYED_DATA.xlsx” from
iLearn.
2. Make a scatterplot, add the regression equation and the R-squared value to the plot. Treat “Years
Employed” as a predictor variable (independent variable) and “Salary” as a variable being
predicted (dependent variable.)
3. Use MS Excel or any other statistical software you are familiar with to obtain the regression output
that includes the regression statistics, ANOVA, and summary of the coefficients of the regression
model. Answer the following questions:
a) Report a linear correlation coefficient and comment on the form, strength, and direction of
association.
b) Report the least-squares regression model. Clearly identify the values of slope and the yintercept and their meaning. Be specific.
c) Demonstrate how you use your regression model to predict a salary for somebody with 2
years of employment with the company. If possible report the residual.
d) Report SSE. What does this value mean?
e) Report the standard error of estimate. Explain the meaning of this value. Be specific.
f) Report the coefficient of determination (R-squared). Explain its meaning. Be specific.
g) Test the claim that the salary increases with the years of employment. State the hypotheses,
a value of the test statistics, and the p-value of the test. Use a 5% level of significance.
h) Test the overall significance of the model. Use a 5% level of significance.
4. You will submit this assignment on iLearn. The instructions and the due date will be provided
shortly. This optional assignment is worth up to 3% of extra credit added to your total score.
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