Using the appropriate model, sample size n, and output:
1. Report SSE, s², and s as shown on the output. Calculate s² from SSE and other numbers.
2. Report the total variation, unexplained variation, and explained variation as shown on the output.

3. Report R² and R̅² as shown on the output. Interpret R² and R̅². Show how  R̅² has been calculated from R² and other numbers.
4. Calculate the F(model) statistic by using the explained and unexplained variations (as shown on the output) and other relevant quantities. Find F(model) on the output to check your answer (within rounding).
5. Use the F(model) statistic and the appropriate critical value to test the significance of the linear regression model under consideration by setting α equal to .05.
6. Use the F(model) statistic and the appropriate critical value to test the significance of the linear regression model under consideration by setting α equal to .01.
7. Find the p-value related to F(model) on the output. Using the p-value, test the significance of the linear regression model by setting α = .10, .05, .01, and .001. What do you conclude?

Model: y = β₀ + β₁x₁ + β₂x₂ + β₃x₃ + ϵ. Sample size: n =16.

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Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total 0.9981 0.9961 0.9952 387.1598 16 df 3 12 15 SS 462327889.4 1798712.2 464126601.6 MS 154109296.5 149892.7 F 1028.1309 Significance F 9.92E-15