Listed below is the table of data. Below the table is the information that I need to find.

weekly gross revenue television advertising newspaper advertising

96 5.0 1.5

90 2.0 2.0

95 4.0 1.5

92 2.5 2.5

95 3.0 3.3

94 3.5 2.3

94 2.5 4.2

94 3.0 2.5

1. Input variables into Excel and run Regression analysis from the Data tab.
2. 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)

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

Regression Output:

• List Variables
• Show Regression Output page

Linear Models:

• List three equations each with their r-squared and SSE values
• Compare r-squared and SSE values to determine which equation offers the best linear model

Significance Tests: For the best linear model state the following:

• F-test: value and state significance
• T-test: value and p-value and state significance for first variable.
• T-test: value and p-value and state significance for second variable.