
Data Driven pretest 2
Quiz
•
Mathematics
•
Professional Development
•
Practice Problem
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Medium
Elizabeth McDowell
Used 1+ times
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25 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
The number of customers that an automobile service shop receives on any given day is normally distributed within a mean of 75 and a standard deviation of 25. On a given day, 125 oil changes are performed.
What is the probability on a given day of 125 or fewer oil changes performed?
67%
68.5%
97.7%
99%
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
A nonprofit organization ran an email campaign with three different messages to solicit additional donations.
What should the nonprofit organization use to determine if the average donation differs for the different messages?
T-test
Mean
ANOVA
Median
3.
MULTIPLE SELECT QUESTION
45 sec • 1 pt
A manager of a call center is in charge of creating a staffing plan. The number of calls received per day is normally distributed.
Which two statistics would be needed to estimate the number of calls that would be received 95% of the time?
Choose 2 answers.
Standard deviation
Mean
Median
Interquartile range
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
A hospital gathers the blood pressure reading of a sample of patients. They find that the mean, median, and mode of this data set are all nearly equal and that 50% of the blood pressure readings are less that the mean and 50% and greater than the mean.
Which histogram would correctly graph this data set?
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
The following is a graph of a normally distributed data set with a mean of 10 and a standard deviation of 2:
68.2%
95.4%
99.6%
100%
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
A manager uses a linear regression to examine how the store's retail sales are predicted by advertising expenditures.
Which type of variable do retail sales represent in this regression?
Independent variable
Dependent variable
Control variable
Predictor variable
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
An analyst used multiple linear regression to explore how Store A's sales (y) are predicted by Store A's advertising expenditure dollars (variable x1) and the advertising expenditure dollars of Store A's competitor (variable x2).
The estimated regression is y=532+80.5x1 - 35.6x2.
How much sales would be predicted if x1 is $1,000 and x2 is also $1,000?
$45,432
$116,632
$44,900
$44,367
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