Loading... Please wait...

Price:

Page 1

Question 1. 1. (TCO A) An insurance company researcher conducted a survey on the

number of car thefts in a large city for a period of 20 days last summer. The results are as

follows.

52

58

75

59

62

77

56

59

51

66

55

68

50

53

67

65

69

57

73

72

a. Compute the mean, median, mode, and standard deviation, Q1, Q3, Min, and Max for

the above sample data on number of car thefts.

b. In the context of this situation, interpret the Median, Q1, and Q3. (Points : 33)

2. (TCO B) Consider the following data on newly hired employees in relation to which part

of the country they were born and their highest degree attained.

HS

BS

MS

PHD

Total

East

3

5

2

1

11

Midwest

7

9

2

0

18

South

5

8

6

2

21

West

1

7

8

6

22

16

29

18

9

72

Total

If you choose one person at random, then find the probability that the person

a. is from the Midwest.

b. is from the South and has a PHD.

c. is from the West, given that person only holds a MS degree. (Points : 18)

3. (TCO B) A source in the Internal Revenue Service has stated that historically 90% of

federal tax returns filed are free of arithmetic errors. A random sample of 25 returns are

selected and checked carefully for arithmetic errors. Assuming independence, find the

probability that

a. all 25 returns are free of arithmetic errors.

b. at most 23 returns are free of arithmetic errors.

c. more than 17 are free of arithmetic errors. (Points : 18)

4. (TCO B) At a local supermarket the monthly customer expenditure follows a normal

distribution with a mean of $495 and a standard deviation of $121.

a. Find the probability that the monthly customer expenditure is less than $300 for a

randomly selected customer.

b. Find the probability that the monthly customer expenditure is between $300 and $600

for a randomly selected customer.

c. The management of a supermarket wants to adopt a new promotional policy giving a free

gift to every customer who spends more than a certain amount per month at this

supermarket. Management plans to give free gifts to the top 8% of its customers (in terms of

their expenditures). How much must a customer spend in a month to qualify for the free

gift? (Points : 18)

5. (TCO C) DJ Car Rental wants to estimate the average number of miles traveled per day by

each of its cars rented in California. A random sample of 110 cars rented in California yields

the following results.

Sample Size = 110

Sample Mean = 85.5 mi

Sample Standard Deviation = 19.3 mi

a. Construct the 99% confidence interval for the average number of miles traveled per day

by each of its cars rented in California.

b. Interpret this interval.

c. How many cars should be sampled if we wish to construct a 99% confidence interval for

the average number of miles traveled per day that is accurate to within 2 mi? (Points : 18)

6. (TCO C) A marketing research firm wishes to estimate the percentage of homeowners

who are dissatisfied with their present homeowner’s insurance policy. A simple random

sample of 400 homeowners led to 80 who were dissatisfied with their homeowner’s

insurance policy.

a. Compute the 95% confidence interval for the population percentage of homeowners who

are dissatisfied with their present homeowner’s insurance policy.

b. Interpret this confidence interval.

c. How many homeowners should be sampled in order to be 95% confident of being within

2% of the population percentage of homeowners who are dissatisfied with their present

homeowner’s insurance policy? (Points : 18)

7. (TCO D) A contract dispute between the National Football League and the Player’s Association arose regarding

the retirement system. The NFL agreed to a settlement only if it could be shown convincingly that less than 60% of

the players retired with 5 years or less playing time in their careers. A random sample of 200 retired NFL players is

selected with 116 having played for 5 years or less. Does the sample data provide evidence to conclude that the

percentage of players retiring with 5 years or less of playing time is less than 60% (using = .01)?

a. Formulate the null and alternative hypotheses.

b. State the level of significance.

c. Find the critical value (or values), and clearly show the rejection and nonrejection regions.

d. Compute the test statistic.

e. Decide whether you can reject Ho and accept Ha or not.

f. Explain and interpret your conclusion in part e. What does this mean?

g. Determine the observed pvalue for the hypothesis test and interpret this value. What does this mean?

h. Does this sample data provide evidence (with = .01), that the percentage of players retiring with 5 years or less

of playing time is less than 60%? (Points : 24)

8. (TCO D) A restaurant franchise company has a policy of opening new restaurants only in

areas that have a mean household income in excess of $65,000. The company is currently

considering an area to open a new restaurant. A random sample of 144 households from

this area is selected yielding the following results.

Sample Size = 144

Sample Mean = $66,124

Sample Standard Deviation = $7,400

Does the sample data provide evidence to conclude that the population mean annual

household income is in excess of $65,000 (using = .05)? Use the hypothesis testing

procedure outlined below.

a. Formulate the null and alternative hypotheses.

b. State the level of significance.

c. Find the critical value (or values), and clearly show the rejection and nonrejection

regions.

d. Compute the test statistic.

e. Decide whether you can reject Ho and accept Ha or not.

f. Explain and interpret your conclusion in part e. What does this mean?

g. Determine the observed p-value for the hypothesis test and interpret this value. What

does this mean?

h. Does the sample data provide evidence to conclude that the population mean annual

household income is in excess of $65,000 (using = .05)? (Points : 24)

Page 2

Question 1. 1. (TCO E) The Central Company manufactures a certain item once a week in a batch production run.

The number of items produced in each run varies from week to week as demand fluctuates. The company is

interested in the relationship between the size of the production run (SIZE, X) and the number of personhours of

labor (LABOR, Y). A random sample of 13 production runs is selected, yielding the data below.

SIZE

LABOR

PREDICT

40

83

60

30

60

100

70

138

90

180

50

97

60

118

70

140

40

75

80

159

70

140

40

75

80

159

70

144

50

90

60

125

50

87

Correlations: SIZE, LABOR

Pearson correlation of SIZE and LABOR = 0.990

PValue = 0.000

Regression Analysis: EMP. versus FLIGHTS

The regression equation is

LABOR = 6.16 + 2.07 SIZE

Predictor Coef SE Coef T P

Constant 6.155 5.297 1.16 0.270

SIZE 2.07371 0.08717 23.79 0.000

S = 5.20753 RSq = 98.1% RSq(adj) = 97.9%

Analysis of Variance

Source DF SS MS F P

Regression 1 15349 15349 565.99 0.000

Residual Error 11 298 27

Total 12 15647

Predicted Values for New Observations

New Obs Fit SE Fit 95% CI 95% PI

1 118.27 1.45 (115.07, 121.46) (106.37, 130.17)

2 201.22 3.90 (192.64, 209.80) (186.90, 215.53)X

X denotes a point that is an extreme outlier in the predictors.

Values of Predictors for New Observations

New Obs SIZE

1 60

2 100

a. Analyze the above output to determine the regression equation.

b. Find and interpret β˖1in the context of this problem.

c. Find and interpret the coefficient of determination (rsquared).

d. Find and interpret coefficient of correlation.

e. Does the data provide significant evidence (= .05) that the size of the production run can be used to predict the

total labor hours? Test the utility of this model using a twotailed test. Find the observed pvalue and interpret.

f. Find the 95% confidence interval for the mean total labor hours for all occurrences of having production runs of

size 60. Interpret this interval.

g. Find the 95% prediction interval for the total labor hours for one occurrence of a production run of size 60.

Interpret this interval.

h. What can we say about the total labor hours when we had a production run of size 100? (Points : 48)

Page 3

1. (TCO E) At an auction, a national car rental agency sold 12 comparably equipped 3yearold Chevrolet Corsicas.

The data on mileage (X1), type of car (X2), and selling price (Y) are found below.

Y = PRICE ($)

X1= MILEAGE (miles)

X2= TYPE (dummy variable 0=sedan, 1=coupe)

The data is given below (in MINITAB).

PRICE

Mileage

Type

PredMile

PredType

7000

60000

0

54000

0

8500

52000

0

54000

1

7000

62000

0

8900

48000

0

7600

55000

0

7200

60000

1

8500

50000

1

7800

53000

1

7200

58000

1

9000

48000

1

7200

60000

1

7700

55000

0

Correlations: PRICE, Mileage, Type

PRICE Mileage

Mileage 0.970

0.000

Type 0.023 0.053

0.942 0.871

Cell Contents: Pearson correlation

PValue

Regression Analysis: PRICE versus Mileage, Type

The regression equation is

PRICE = 15841 0.146 Mileage 39 Type.

Predictor Coef SE Coef T P

Constant 15840.9 671.4 23.59 0.000

Mileage 0.14562 0.01205 12.09 0.000

Type 39.5 114.1 0.35 0.737

S = 197.278 RSq = 94.2% RSq(adj) = 92.9%

Analysis of Variance

Source DF SS MS F P

Regression 2 5689732 2844866 73.10 0.000

Residual Error 9 350268 38919

Total 11 6040000

Predicted Values for New Observations

New Obs Fit SE Fit 95% CI 95% PI

1 7977.5 82.1 (7791.7, 8163.3) (7494.1, 8460.9)

2 7938.0 81.2 (7754.4, 8121.6) (7455.4, 8420.6)

Values of Predictors for New Observations

New Obs Mileage Type

1 54000 0.00

2 54000 1.00

a. Analyze the above output to determine the multiple regression equation.

b. Find and interpret the multiple index of determination (RSq).

c. Perform the ttests on β˖1, β˖2 (use two tailed test with (= .05). Interpret your results.

d. Predict the price for an individual Chevy Corsica with mileage of 54,000 miles and with type being sedan. Use

both a point estimate and the appropriate interval estimate. (Points : 31)