Stats Practice Questions

Question 1: The human resource manager of a telemarketing firm is concerned about the rapid turnover of the

firm’s telemarketers, as many of them do not work for long before quitting. There is a high cost associated with

hiring and training new workers and so the manager decided to investigate the factors that influenced his

workers to quit. He reviewed the work history of a random sample of workers who have quit in the last year and

recorded the number of weeks on the job before quitting and the age of each worker when originally hired. An

Excel analysis was carried out and the Excel output is shown below.

ANOVA

Regression

Residual

Total

Intercept

Age

df

1

78

79

SS

59.51650857

256.4334914

315.95

Coefficients

30.63307456

-0.116916823

Standard Error

1.044141582

0.027478837

MS

F

Significance F

59.51650857 18.10328145 5.76741E-05

3.287608864

t Stat

P-value

29.33804678 6.84876E-44

-4.25479511 5.76741E-05

Lower 95%

28.55434839

-0.171622984

Upper 95%

32.71180074

-0.06221066

(a) Comment on the scatterplot in Figure 1 below, which is for the analysis given above.

Figure 1: Number of Weeks Employed against Age When Originally

Hired

Number of Weeks Employed

32

30

28

26

24

22

20

15

25

35

45

55

Age (years)

(b)

(c)

(d)

(e)

(f)

(g)

a.

What is the dependent variable and what is the independent variable?

Write down the equation of the fitted regression line in standard form.

Use the Excel analysis to test whether there is a negative linear relationship between the age of the workers

when originally hired and the number of weeks they stay with the firm. Use = 0. 01.

Write down a 95% confidence interval for the slope of the fitted regression line. Interpret this interval.

A 40 year old employee worked for 21 weeks. What is the residual for this value?

Comment on the scatterplot in Figure 2 below, which is for the analysis given above. What can you

conclude about the validity of the test in part (c)?

1

Figure 2: Residuals against Predicted Values

6

Residuals

4

2

0

-2

-4

-6

24

25

26

27

28

29

Predicted Values

Question 2: An office manager believes that the amount of time spent by office workers reading and deleting

spam email exceeds 25 minutes per day. A random sample of 18 workers was selected and the amount of time

each spent reading and deleting spam email was measured. The following times (in minutes) were recorded:

35 48 29 44 17 21 32 28 34 23 13 9 11 30 42 37 43 48

Can the office manager conclude that the average time spent reading and deleting spam email is more than 25

minutes? Use = 0.05.

Question 3: A large production facility uses two machines to produce a key part for its main product.

Sometimes the key part is defective. Inspectors randomly sampled 35 of the key parts from each machine. Of

those produced by machine A, 5 were defective. Of those produced by machine B, 7 were defective. Can the

production facility conclude that the proportion of defective parts produced by the two machines is different?

Use = 0.05.

Question 4: At a particular university, administrators believe that the proportion of students preferring to take

classes at night exceeds 0.30. To test this, a simple random sample of 200 students is selected and 66 indicate

that they prefer night classes.

(a) Can it be concluded that the administrators’ belief is correct? Test using a significance level of 10%. What

is the p-value for the test statistic?

(b) What is the p-value for the test in (a)?

Question 5: The supermarket is concerned by complaints by some customers that in the 12 items or less queue

some customers have more than 12 items. The supermarket decided to investigate this issue. One morning they

watched the first 50 customers and counted the number of items in their baskets.

(a) Assume that the supermarket improved their sampling techniques and from a simple random sample found

that 6 out of 50 customers exceeded the item limit in the 12 items or less…