A few years ago I was asked to help a company estimate its shipping costs. The company is in the business of providing authentic rebuilt parts for classic cars. They get orders from all around the world for both small and large parts. The company needed a method to estimate the shipping costs for the ordered parts instead of telling customers "TBD" (To Be Determined), which was becoming less and less acceptable given the wide variation in shipping costs due to the size of the part and the shipping destination.

Assume that you can appropriately use simple linear regression for this case. Using the data, run the regression models identified below and submit a single PDF file which includes the following components:

A) Model A: Run the regression model with only theShipping Weightas the explanatory variable and theShipping Chargeas the dependent variable. Include the Excel output of your model (all three tables in the Summary Output of regression analysis) and label it as Model A.

b) Model B: Run the regression model with only theMerchandise Totalas the explanatory variable and theShipping Chargeas the dependent variable. Include the Excel output of your model (all three tables in the Summary Output of regression analysis) and label it as Model B.

c) Analyze and compare the two models. Is one model better than the other? Why? Explain your answer fully by analyzing the standard deviation of the prediction errors and any other relevant model statistics.

use Excel to solve the problem

https://docs.google.com/spreadsheets/d/1_N532wEmqG3iGd0mFy4TLn_xgiPJrkNKq1MOxL09ONw/edit#gid=1732237501