EBK BUSINESS STATISTICS
7th Edition
ISBN: 9780134462783
Author: STEPHAN
Publisher: PEARSON CUSTOM PUB.(CONSIGNMENT)
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4. Describe whether each of the following scenarios would result in qualitative or quantitative data:
a. Time needed to finish a project by a technician
b. Number of days of stay in a hospital by a patient after bypass surgery
c. Average number of cars passing through a toll booth each day
d. Types of beverages served by a restaurant
e. Size of a rod used in a project
f. Condition of a home for sale (excellent, good, fair, bad)
g. Heights of basketball players
h. Dose of medication prescribed by a physician to his/her patients
i. Recorded temperatures of a tourist place during the month of January
j. Ages of persons waiting in a physician's office
k. Speed of a vehicle crossing George Washington Bridge in New York
1. Amount of interest reported in a tax return
m. Sizes of cars available at a rental company (full, medium, compact, small)
n. Manufacturers of cars parked in a parking lot
5. Referring to Problem 4, classify the data in each case as nominal, ordinal, interval, or ratio.
A media company is in the process of deciding whether to purchase a maintenance contract for a new piece of camera equipment or pay for the maintenance themselves. Managers feel that cost
required to maintain the equipment should be related to the amount of time it is used, and they collected the following data on hours used (per week) and yearly maintenance costs (in dollars).
Hours Used per Week
9 =
12
10
19
27
31
17
23
31
40
37
Maintenance Cost per Year
1750
2250
2950
3650
4750
3000
3200
3850
5100
4050
(a) Develop the estimated regression equation that could be used to predict the yearly maintenance costs (in dollars) given the weekly usage (in hours). (Round your numerical values to two
decimal places.)
2. A real estate expert wanted to find the relationship between the sale price of houses
and various characteristics of the houses. He collected data on five variables,
recorded in the table, for 12 houses that were sold recently. The five variables are:
Sale price of a house in thousands of dollars.
Size of the lot in acres.
Price:
Lot Size:
Living Area: Living area in square feet.
Age:
Type of house: town house (T) or Villa (V)
Age of a house in years.
Price
Lot Size
Living
Area
Age
Туре
of
house
255
1.4
2500
8
T
178
0.9
2250
12
T
T.
T.
T.
263
1.8
2900
5
0.7
2.6
127
1800
24
305
3200
10
164
1.2
2400
18
245
2.1
2700
T
V
146
1.1
2050
28
287
2.8
2850
13
V
189
1.6
2600
9
211
1.7
2300
8
V
123
0.5
1700
11
V
a) Find the regression equation for the town house
b) Find the regression equation for the Villa
c) What is the price of a town house with a lot size of 1.3, living area
of 1800, and is 7 years old?
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