I need help answering the questions below. The table of information to use to answer these questions, is located below these questions.

1. Input variables into Excel and run Regression analysis from the Data tab.

1. List the following in determining best-fit model:

• Linear model between only x1-variable and y with correlation coefficient (r-squared) and SSE (Sum of Squares for Residual)
• Linear model between only x2-variable and y with correlation coefficient (r-squared) and SSE (Sum of Squares for Residual)
• Linear model between x1, x2 and y with correlation coefficient (r-squared) and SSE (Sum of Squares for Residual)
• Determine which model offers best fit and why (compare the Correlation coefficients and Sum of Squares of the residuals)

1. Using the best-fit model, list the following in determining significance:

• F-test: F-value and significance of linear model
• T-test for x1-variable: t-value and p-value for significance of variable
• T-test for x2-variable: t-value and p-value for significance of variable

Student GPA Program Return

1 3.78 1 1

2 2.38 0 1

3 1.30 0 0

4 2.19 1 0

5 3.22 1 1

6 2.68 1 1

98 2.57 1 1

99 1.70 1 1

100 3.85 1 1