# Consider the following data on newly hired entry-level employees in relation

November 24, 2016

2.(TCO B) Consider the following data on newly hired entry-level employees in relation to how many previous positions they have held and which part of the country they were born.

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0

1

2

3 or more

Total

East

3

5

2

1

11

Midwest

7

9

2

0

18

West

1

7

8

5

21

Total

11

21

12

6

50

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

b. is from the West and had three or more previous positions.

c. had only one previous position, given that the person is from the Midwest. (Points : 18)

7.(TCO D)An article in a trade journal reports that nationwide 28% of liquor purchases are made by women. If B & B Liquor’s proportion of sales to women is significantly different from the national norm, the owners are considering redesigning B & B’s advertising. A random sample of 100 customers is selected resulting in 24 women and 76 men.Does the sample data provide evidence to conclude that less than 28% of B&B’s customers are women (usinga= .01)? 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 non-rejection 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 this sample data provide evidence (witha= .01), that less than 28% of B & B’s customers are women? (Points : 24)

1.(TCO E) A used car dealer is interested in determining the relationship between car mileage (i.e., the odometer reading, Miles X1, in 1,000s of miles), gender of the previous owner (Gender, X2 where 0=female and 1=male), and the trade value of the car (Value, Y in \$100s). A random sample of 16 five-year-old cars of the same make, model, condition, and optional features is selected. The results are found below.

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Miles

Gender

Value

59

1

67

92

0

61

61

1

73

72

0

69

52

1

71

67

0

69

88

0

65

62

0

70

95

0

59

83

0

63

60

1

70

65

1

66

72

1

68

82

0

63

74

1

66

56

1

74

58

0

64

62

1

72

82

1

70

72

0

60

Correlations: Miles, Gender, Value

Miles Gender

Gender-0.519

0.019

Value-0.6970.638

0.0010.002

Cell Contents: Pearson correlation

P-Value

Regression Analysis: Value versus Miles, Gender

The regression equation is

77.6 – 0.172 Miles + 3.20 Gender.

Predictor Coef SE CoefT P

Constant 77.564 4.897 15.84 0.000

Miles-0.172030.06236-2.760.013

Gender3.1981.5372.080.053

S = 2.93645 R-Sq = 59.1% R-Sq(adj) = 54.2%

Analysis of Variance

Source DF SS MS F P

Regression 2 211.41 105.71 12.26 0.001

Residual Error17 146.598.62

Total19 358.00

Predicted Values for New Observations

New ObsFit SE Fit95% CI95% PI

1 68.7190.994 (66.622, 70.817) (62.179, 75.260)

Values of Predictors for New Observations

New Obs Miles Gender

170.01.00

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

b. Find and interpret the multiple index of determination (R-Sq).

c. Perform the multiple regressiont-testson1,2(use two tailed test with (a= .10). Interpret your results.

d. Predict the trade value for a single car that 70,000 miles on the odometer and was owned by a male. Use both a point estimate and the appropriate interval estimate.

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