A company that has distribution rights to home video sales of previously released movies would like to estimate the number of units that it can be expected to Sell. Data are available for 29 movies that indicate the box office gross (in millions of dollars) and the number of units sold (in thousands) of home videos. alpha=.01
x=Box Office Gross (millions) 1.10, 1.13, 1.18, 1.25, 1.44, 1.53, 1.53, 1.69, 1.74, 1.77, 2.42, 5.34, 5.70, 6.43, 8.59, 9.36, 9.89, 12.66, 15.35, 17.55, 17.91, 18.25, 23.13, 27.62, 37.09, 40.73, 46.62, 54.70, 58.51
y-Home videos sold (thousands) 57.18, 26.17, 92.79, 61.60, 46.50,85.06, 103.52, 30.88, 49.29, 24.14, 115.31, 87.04, 128.45, 126.64, 107.28, 190.80, 121.57, 183.30, 204.72, 112.47, 162.95, 109.20, 280.79, 229.51, 277.68, 226.73, 218.64, 286.31, 254.58
Format report as follows and label each section as instructed:
1. Label: Problem Definition
2. Label: Scatterplot-Scatterplot with description of relationship between x and y, positive or negative? neither?
3. Label:Correlation Coefficient-Hypothesis test of correlation coefficient for Home Video Units sold and Box office gross-use 6 step process.
4. Label:Regression Equation (show only the equation, not the entire table or output) Define regression coefficients b0 and b1
5. Label: Significance Testing (Regression Coefficient)-T-test for significance of regression coefficient. Use six step process. In interpretation step discuss average amount of change in y for one unit change in x.
6. Label:Significance Testing (ANOVA) F-test to test R-Sqd - Use 6 step process and in interpretation step discuss percentage of variability in y describeed by x.
7. Label:Satisfying regression assumptions-Include plots with descriptions in report: NP Plot for residuals-address assumptions; Residuals vs. Fits-description addressing assumptions; Residuals and x variable-graph with description addressing assumptions
8. Label:Confidence Interval for Regression Coefficient-Develop confidence interval for regression coefficient and interpret-Calculations to be done by hand and typed neatly into report. Discuss whether 0 lies in interval and interpret interval using partial regression terminology.
9. Label:Prediction and Confidence interval for fit value of y - develop prediction interval and confidence interval for y for the value of x you select. Interpret both intervals as they relate to y.