Question
Find and interpret the coefficient of determination for the regression of DVD system sales on price, using the following data.$$\begin{array}{rrrrrrrrr}\hline \text { Sales } & 420 & 380 & 350 & 400 & 440 & 380 & 450 & 420 \\\hline \text { Price } & 98 & 194 & 244 & 207 & 89 & 261 & 149 & 198 \\\hline\end{array}$$
Step 1
- Mean of Sales, \(\bar{y}\) = \(\frac{420 + 380 + 350 + 400 + 440 + 380 + 450 + 420}{8} = \frac{3240}{8} = 405\) - Mean of Price, \(\bar{x}\) = \(\frac{98 + 194 + 244 + 207 + 89 + 261 + 149 + 198}{8} = \frac{1440}{8} = 180\) Show more…
Show all steps
Your feedback will help us improve your experience
James Kiss and 85 other educators are ready to help you.
Ask a new question
Labs
Want to see this concept in action?
Explore this concept interactively to see how it behaves as you change inputs.
Key Concepts
Recommended Videos
Regression and Correlation Work Sheet 1. Mumbai Electronics is planning is planning to expand its marketing region from Jamaica to Barbados. In order to predict to predict its sales in Barbados, the company has asked you to develop a linear regression of DVD system sales on price, using the following data supplied by the marketing department: Price 98 194 231 207 89 255 149 195 Sales 418 384 343 407 432 386 444 427 a. Estimate the regression model b. Calculate and interpret the coefficient of determination.
Interpreting the Coefficient of Determination. We the value of the linear correlation coefficient $r$ to find the coefficient of determination and the percentage of the total variation that can be explained by the linear relationship between the two variables from the Appendix B data sets. $r=0.744(x=\text { movie budget, } y=$ movie gross)
Correlation and Regression
Variation and Prediction Intervals
Use the results from Problem 27 in Section 4.1 and Problem 19 in Section 4.2 to: (a) Compute the coefficient of determination, $R^{2}$. (b) Construct a residual plot to verify the requirements of the least-squares regression model. (c) Interpret the coefficient of determination and comment on the adequacy of the linear model.
Describing the Relation between Two Variables
Diagnostics on the Least-Squares Regression Line
Transcript
Watch the video solution with this free unlock.
EMAIL
PASSWORD