For the points: X: 6 8 12 Y: 18 24 29 The estimated equation from a linear regression is: Yᵢ = 8.5 +1.75Xᵢ Using this information, write out your calculations (yes, I want you to do them by hand, just this once) for the following: A. Standard Error of the Estimate (SEE) B. Total Sum of Squares (TSS) C. Explained Sum of Squares (ESS) D. Residual Sum of Squares (RSS) E. Coefficient of Determination (R²) F. The Adjusted R² Please Use R to Answer the Following Questions
5. Bicyclists are crazy about weight. They will pay a lot of money to reduce the weight of their bike. A friend of mine who is a serious cyclist once told me that a serious cyclist would pay a price per gram to reduce the weight of their bike that was greater than the price of gold. There is data on bicycle saddles on the course web page giving the price of the saddle, the brand, the mass of the saddle in grams and the material from which the rails are made. A
. Use the bicycle seats data available on the D2L site to estimate a linear regression of the regular price of a bicycle seat on the weight of the seat. Briefly explain what the coefficient estimates mean. B. How does the explanatory power of the model change if Brand is added, if the materials from which the rails are made is added and if both are added? C. Brooks saddles are unusual and are generally favored by members of a group of extremist cyclists. How does the explanatory power of the model from part A change if Brooks saddles are excluded from the analysis?