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July 21, 2017UncategorizedBy classhelp24@gmail.com [email if you need fresh paper done]

Can i get the answer of this one. This one is business statistics but, I don’t know exactly how to i resolve it.

1. In discussing how its customers use online services, a bank manager noted ?there
seems to be a strong correlation between the use of the online bill paying feature and
gender.? Comment on this statement.
2. For each of the following scenarios indicate which is the predictor variable and which
is the response variable.
a. A study examined consumption levels of oil and carbon dioxide emissions for a sample
of counties.
b. Data were collected on job performance rating and hours of training for a sample of
employees at a telecommunications repair facility.
c. Salary data as well as years of managerial experience were collected for a sample of
executives in the high tech industry.
3. The following scatterplot shows monthly sales figures (in units) and number of
months of experience on the job for a sample of 19 salespeople.
Scatterplot of Sales vs Experience
80

70

60

50

40

30
0

20

40

60

80

100

Experience

a. Describe the association between monthly sales and level of experience.
b. Do these data satisfy the conditions for computing a correlation coefficient? Explain.
c. Estimate the correlation.

.

4. Shown below is a correlation table showing correlation coefficients between stock
price, earnings per share (EPS), and price/earnings (P/E) ratio for a sample of 19 publicly
traded companies.
Correlations: Stock Price, EPS, PE
Stock Price

EPS

0.875
0.323

-0.111

EPS
PE

a. What is the correlation between stock price and EPS? Interpret.
b. What is the correlation between stock price and PE? Interpret.
c. What is the correlation between EPS and PE? Interpret.
Use the following to answer questions 5 – 8.
To determine whether the cash bonus paid by a company is related to annual pay, data
were gathered for 10 account executives at Johnson Financial Group who received cash
bonuses in 2007. The data, scatterplot, and summary statistics are shown below.
ANNUAL PAY
$ 70609
$ 58487
$ 104561
$ 43922
$ 82613
$ 116250
$ 76751
$ 68513
$ 137000
$ 94469

CASH BONUS
$ 11225
$ 6238
$ 14194
$ 4188
$ 11863
$ 13671
$ 7758
$ 20760
$ 55000
$ 34368

Mean
Standard Deviation

$ 85318
$ 28077

$ 17927
$ 15618

Correlation

0.735

.

Scatterplot of Cash Bonus vs Pay
60000
50000

40000
30000

20000
10000
0
50000

75000

100000
Pay

125000

150000

5. Comment on whether each of the following conditions for correlation / linear
regression is met.
a. Quantitative variable condition.
b. Linearity condition.
c. Outlier condition.
6. Estimate the linear regression model that relates the response variable (cash bonus)
to the predictor variable (annual pay).
a. Find the slope of the regression line.
b. Find the intercept of the regression line.
c. Write the equation of the linear model.
7. Find the value of R2. Interpret its meaning in this context.
8. Using the estimated regression equation,
a. Estimate the cash bonus for an executive at Johnson Financial earning $82, 613 a year.
b. What is the residual for this estimate? What does it mean?

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