**Wed, Oct 7**

Review:

- Multiple Regression
- Polynomial (Curve Fit) in Sheets or Excel [Crude Oil Prices]

Presentation:

- Regression Output Interpretation
- R-Squared
- Regression Equation Coefficients
- t-Stat and p-values for Independent Variables significance
- F statistic and p-value (Significance F) for Overall Model significance
- ANOVA table Sum of Squares values (SSR, SSE, SSyy)
- SSR = b1^2*SSxx
- SSE = Sum of Squares residuals
- SSyy = Sum of Squares of y

Activity:

- Read
**Demonstration Problem 13.1 on p. 528-529** - Use the Regression Summary Output table on p. 529 to answer these questions.
- What is the
**R-Squared**value? - How many
**observations**are in the data set being analyzed? - Name the variables and their corresponding
**coefficients**. - What are the
**t-stat**values for each independent variable? - What are the
**p-values**for each independent variable? - Which variable is the most significant?
- What is the
**F statistic**for the model? - What is the significance level of the F statistic?
- What is
**SSE**, the Sum of Squares Error? - What is
**SSyy**, the Sum of Squares for y? - What is
**SSR**, the Sum of Squares Regression?

- What is the

Assignment:

- Download Excel data provided as a companion to the textbook: black_7e_excel_database
- Complete the “Analyzing the Database”
**Problems 1-4**on**p. 549** - Don’t worry about the discussion questions.
- I only want you to produce the models specified and then answer the same “Activity” questions above for each resulting Regression Output.

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