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hw4a1 - H β =0 vs H A β ≠0 based on the 0.05...

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STA 6126 – Homework Project #5 Fall 2010 – Due 12/5/11 Download the cotton price/acreage dataset. The variables are given in the description file. Let Y be the amount of acreage of cotton planted in the year. Let X be the adjusted combined price of cotton and cottonseed in the previous year (last variable in data file). Complete the following parts: Briefly describe the parameter β in the regression model Y = α + β X + ε Obtain a plot of Y versus X including the fitted regression equation. Write out the fitted equation: bX a Y + = ^ Give the estimate of the conditional standard deviation: 2 2 ^ ^ - - = n Y Y σ Give the correlation coefficient: ( 29 ( 29 ( 29 ( 29 - - - - = 2 2 Y Y X X Y Y X X r Give the coefficient of determination: TSS SSE TSS r - = 2
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Conduct the t-test to test H 0 : β =0 vs H A : β ≠0 based on the 0.05 significance level. Obtain a 95% confidence interval for β Give the Analysis of Variance Table. Conduct the F-test to test
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Unformatted text preview: H : β =0 vs H A : β ≠0 based on the 0.05 significance level. • Conduct the t-test to test H : ρ =0 vs H A : ρ ≠0 based on the 0.05 significance level. SPSS Instructions: • Import dataset into SPSS • Using Variable View, Name the relevant variables (e.g. acres, price) • Make sure both variables are SCALE in the last column • Return to Data View and Select: • GRAPHS (To obtain Plot with Fitted Equation) • INTERACTIVE (This may not be available on newer versions) • SCATTERPLOT • Move acres to vertical (up/down) axis • Move price to horizontal (right/left) axis • Click on Fit tab • Select Regression as Method • ANALYZE (To fit Model) • REGRESSION • LINEAR • Identify acres as Dependent Variable • Identify price as Independent Variable • Under STATISTICS, select Confidence Intervals...
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