Part 1: Model Building
1. Submit both this word and excel file
2. Keep two decimal places for your answer
Using the data Reynolds.xls. The variables are defined as:
Sales (Y) =number of electronic laboratory scales sold
Months (X) =the number of months the salesperson has been employed
1. Develop the scatter plot using Sales as y axis and Months as x axis, and can you see the curvature?
2. Using a simple linear regression model to develop an estimated regression equation to predict the Sales. What is the adjusted-R square?
3. Using a second-order regression model to develop an estimated regression equation to predict the Sales. What is the adjusted-R square? (Hint: second-order regression model should look like: y=b0+b1X+b2X2, and we learnt it in Chapter 16)
4. Compare the adjusted-R square from 2 and 3, which one is larger? Which model is better? (Hint: we learn this in Chapter 15)
5. Use 4 diagrams to test the 5 model assumptions for the second-order regression model. Do you think they are violated? (Hint: we learn this in week 12 computer skill class)
Months | Sales |
41 | 275 |
106 | 296 |
76 | 317 |
104 | 376 |
22 | 162 |
12 | 150 |
85 | 367 |
111 | 308 |
40 | 189 |
51 | 235 |
9 | 83 |
12 | 112 |
6 | 67 |
56 | 325 |
19 | 189 |
Part 1: Model Building 1. Submit both this word and excel file 2. Keep two decimal places for your answer Using the data Reynolds.xls. The variables are defined as: Sales (Y) =number of electronic lab...
Excel Problem 2 - Chapter 12: PART B: The following data give the selling price, square footage, and age of houses that have sold in a Bend, OR in the past 6 months (note that this is the same base data as Part A, above, with new variables added). Selling Price ($) Square Footage Age (Years) 84,000 1,670 30 79,000 1,339 25 91,500 1,712 30 120,000 1,840 40 127,500 2,300 18 132,500 2,234 30 145,000 2,311 19 164,000 2,377 7...