Question 1
Below you are given the examination scores of 20 students (data set also provided in accompanying MS Excel file).
52
|
99
|
92
|
86
|
84
|
63
|
72
|
76
|
95
|
88
|
92
|
58
|
65
|
79
|
80
|
90
|
75
|
74
|
56
|
99
|
a. Construct a frequency distribution, cumulative frequency distribution, relative frequency distribution, cumulative relative frequency distribution and percent frequency distribution for the data set using a class width of 10.
b. Construct a histogram showing the percent frequency distribution of the examination scores. Comment on the shape of the distribution.
Question 2
Shown below is a portion of a computer output for a regression analysis relating supply (Y in thousands of units) and unit price (X in thousands of dollars).
ANOVA
|
|
|
|
df
|
SS
|
Regression
|
1
|
354.689
|
Residual
|
39
|
7035.262
|
|
Coefficients
|
Standard Error
|
Intercept
|
54.076
|
2.358
|
X
|
0.029
|
0.021
|
a. What has been the sample size for this problem?
b. Determine whether or not supply and unit price are related. Use α = 0.05.
c. Compute the coefficient of determination and fully interpret its meaning. Be very specific.
d. Compute the coefficient of correlation and explain the relationship between supply and unit price.
e. Predict the supply (in units) when the unit price is $50,000.
Question 3
Allied Corporation wants to increase the productivity of its line workers. Four different programs have been suggested to help increase productivity. Twenty employees, making up a sample, have been randomly assigned to one of the four programs and their output for a day's work has been recorded. You are given the results below (data set also provided in accompanying MS Excel file).
Program A
|
Program B
|
Program C
|
Program D
|
150
|
150
|
185
|
175
|
130
|
120
|
220
|
150
|
120
|
135
|
190
|
120
|
180
|
160
|
180
|
130
|
145
|
110
|
175
|
175
|
a. Construct an ANOVA table.
b. As the statistical consultant to Allied, what would you advise them? Use a .05 level of significance.
Question 4
A company has recorded data on the weekly sales for its product (y), the unit price of the competitor's product (x1), and advertising expenditures (x2). The data resulting from a random sample of 7 weeks follows. Use Excel's Regression Tool to answer the following questions (data set also provided in accompanying MS Excel file).
Week
|
Price
|
Advertising
|
Sales
|
1
|
.33
|
5
|
20
|
2
|
.25
|
2
|
14
|
3
|
.44
|
7
|
22
|
4
|
.40
|
9
|
21
|
5
|
.35
|
4
|
16
|
6
|
.39
|
8
|
19
|
7
|
.29
|
9
|
15
|
a. What is the estimated regression equation? Show the regression output.
b. Determine whether the model is significant overall. Use α = 0.10.
c. Determine if competitor's price and advertising is individually significantly related to sales. Use α = 0.10.
d. Based on your answer to part (c), drop any insignificant independent variable(s) and re-estimate the model. What is the new estimated regression equation?
e. Interpret the slope coefficient(s) of the model from part (d).