WILLING TO NEGOTIATE !! HELLO, THESE ASSIGNMENTS ARE FOR A QUANTITATE METHODS CLASS!! (QMB3600) THERE IS AN EXCEL WORKSHEET WHERE YOU PLUG IN THE NUMERS FROM THE WORD HOMEWORK ASSIGNMENTS AND THEN A
Homework 5
1) Thirteen student were admitted to the undergraduate business program at Whatsamatta University 2 years ago. The following table indicates what their grade-point average was after 2 years at the University. Also listed is their SAT score that they scored when they were in high school (maximum score is 2400).
Student | SAT Score | GPA | Student | SAT Score | GPA |
1263 | 2.90 | 1443 | 2.53 | ||
1131 | 2.93 | 2187 | 3.22 | ||
1755 | 3.00 | 1503 | 1.99 | ||
2070 | 3.45 | 1839 | 2.75 | ||
1824 | 3.66 | 2127 | 3.90 | ||
1170 | 2.88 | 1098 | 1.60 | ||
1245 | 2.15 |
a) Using the SAT score to predict their GPA is there a meaningful relationship between the SAT score and their GPA? How do you know?
b) If a student has a SAT score of 1200, what do you think their GPA will be in two years?
c) If a student has a SAT score of 2400, what do you think their GPA will be in two years?
2) The following data gives the selling price, square footage, number of bedrooms, and the age of a house in years. These houses have been sold in a specific neighborhood over the last six months.
Selling Price ($) | Square Footage | Bedrooms | 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 | ||
155,000 | 2,736 | 10 | |
168,000 | 2,500 | ||
172,500 | 2,500 | ||
174,500 | 2,479 | ||
175,000 | 2,400 | ||
177,500 | 3,124 | ||
184,000 | 2,500 | ||
195,500 | 4,062 | 10 | |
195,000 | 2,854 |
a) Using square footage develop a model to predict the selling price of the house. How well does the model fit the data? What percentage of the selling price is explained by the model?
b) Using the number of bedrooms develop a model to predict the selling price of the house. How well does the model fit the data? What percentage of the selling price is explained by the model?
c) Using the age of the house develop a model to predict the selling price of the house. How well does the model fit the data? What percentage of the selling price is explained by the model?
d) Which of the models estimated in parts a – d best fits the data? Why did you select that model?
3) The total expenses of a hospital is determined by many different factors but two of these factors are the number of beds and the number of patients that are admitted to the hospital. Data was collected on 14 hospitals and is listed in the table.
Hospital | Number of beds | Admissions (1,000s) | Total expenses ($1,000,000 |
215 | 77 | 57 | |
336 | 160 | 127 | |
520 | 230 | 157 | |
135 | 43 | 24 | |
35 | 14 | ||
210 | 155 | 93 | |
140 | 53 | 45 | |
90 | |||
410 | 159 | 99 | |
10 | 50 | 18 | 12 |
11 | 65 | 16 | 11 |
12 | 42 | 29 | 15 |
13 | 110 | 28 | 21 |
14 | 305 | 98 | 63 |
a) Develop a model using the number of beds to predict the total expenses of a hospital. How well does the model fit the data?
b) Develop a model using the number of admissions to predict the total expenses of a hospital. How well does the model fit the data?
c) Develop a model using the number of beds and admissions to predict the total expenses of a hospital. How well does the model fit the data?
d) Do you think that both variables (number of beds and admissions) should be included in our prediction model? Why or Why not?
4) A sample of 20 automobiles was taken and the miles per gallon (MPG), horsepower, and total weight were recorded. Develop a regression model to predict MPG based on weight and horsepower.
MPG | Horsepower | Weight (lbs) |
44 | 67 | 1,844 |
44 | 50 | 1,998 |
40 | 62 | 1,752 |
37 | 96 | 1,980 |
37 | 66 | 1,797 |
34 | 63 | 2,199 |
35 | 90 | 2,404 |
32 | 99 | 2,611 |
30 | 63 | 3,236 |
28 | 91 | 2,606 |
26 | 94 | 2,580 |
26 | 88 | 2,507 |
25 | 124 | 2,922 |
22 | 97 | 2,434 |
20 | 114 | 3,248 |
21 | 102 | 2,812 |
18 | 114 | 3,382 |
18 | 142 | 3,197 |
16 | 153 | 4,380 |
16 | 139 | 4,036 |
a) Develop a regression model using weight and horsepower to predict the MPG. How well does the data fit the model?
b) Let us suppose that your automobile has 83 horsepower and a weight of 2,381 pounds. What is your expected MPG?