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Chapter 11: Section Exercises #3, 4, 6, 14 , 16 NO P-Values are necessary for these problems 11.

Chapter 11: Section Exercises #3, 4, 6, 14 , 16
NO P-Values are necessary for these problems
11.3 Semester GPAs are compared for seven randomly chosen students in each class level at Oxnard
University. Does the data prove a significant difference in mean GPAs? GPA1
GPA for Randomly Selected Students in Four Business Majors
Accounting Finance Human Resources Marketing
2.48 3.16 2.93 3.54
2.19 3.01 2.89 3.71
2.62 3.07 3.48 2.94
3.15 2.88 3.33 3.46
3.56 3.33 3.53 3.50
2.53 2.87 2.95 3.25
3.31 2.85 3.58 3.20
11.4 Sales of People magazine are compared over a 5-week period at four Borders outlets in Chicago.
Does the data prove a significant difference in mean weekly sales? Magazines
Weekly Sales
Store 1 Store 2 Store 3 Store 4
102 97 89 100
106 77 91 116
105 82 75 87
115 80 106 102
112 101 94 100
11.6 Refer to Exercise 11.2. Which pairs of mean examination times differ significantly (4 physicians)?
Physicians
11.2 One particular morning, the length of time spent in the examination rooms is recorded for each
patient seen by each physician at an orthopedic clinic. Does the data prove a significant difference
in mean times? Physicians
Time in Exam Rooms (Minutes)FIGURE 11.12
Physician 1 Physician 2 Physician 3 Physician 4
34 33 17 28
25 35 30 33
27 31 30 31
31 31 26 27
26 42 32 32
34 33 28 33
21 26 40
29
11.14 Engineers are testing company fleet vehicle fuel economy (miles per gallon) performance by
using different types of fuel. One vehicle of each size is tested. Does this sample prove that there
is a significant difference in treatment means? MPG2
87 Octane 89 Octane 91 Octane Ethanol 5% Ethanol 10%
Compact 27.2 30.0 30.3 26.8 25.8
Mid-Size 23.0 25.6 28.6 26.6 23.3
Full-Size 21.4 22.5 22.2 18.9 20.8
SUV 18.7 24.1 22.1 18.7 17.4
11.16 A beer distributor is comparing quarterly sales of Coors Light (number of six-packs sold) at
three convenience stores. Does this sample prove a significant difference in treatment means?
BeerSales
Store 1 Store 2 Store 3
Qtr 1 1,521 1,298 1,708
Qtr 2 1,396 1,492 1,382
Qtr 3 1,178 1,052 1,132
Qtr 4 1,730 1,659 1,851
Chapter 12: Section Exercise  #2, 4, 6, 8, 10
Instructions for Exercises 12.2 and 12.3: (a) Make an Excel scatter plot. What does it suggest about
the population correlation between X and Y? (b) Make an Excel worksheet to calculate SSxx , SSyy , and
SSxy . Use these sums to calculate the sample correlation coefficient. Check your work by using Excel's
function =CORREL(array1,array2). (c) Use Appendix D to find t.05 for a two-tailed test for zero correlation.
(d) Calculate the t test statistic. Can you reject ρ = 0? (e) Use Excel's function =TDIST(t,deg_freedom,tails)
to calculate the two-tail p-value.
12.2 Part-Time Weekly Earnings ($) by College Students WeekPay
Hours Worked (X) Weekly Pay (Y)
10 93
15 171
20 204
20 156
35 261
Instructions for Exercises 12.4-12.6: (a) Make a scatter plot of the data. What does it suggest about the
correlation between X and Y? (b) Use Excel, MegaStat, or MINITAB to calculate the correlation coefficient.
(c) Use Excel or Appendix D to find t.05 for a two-tailed test. (d) Calculate the t test statistic.
(e) Calculate the critical value of rα. (f) Can you reject ρ = 0?
12.4 Moviegoer Spending ($) on Snacks Movies
Age (X) Spent (Y)
30 2.85
50 6.50
34 1.50
12 6.35
37 6.20
33 6.75
36 3.60
26 6.10
18 8.35
46 4.35
12.6 Number of Orders and Shipping Cost ($) ShipCost
Orders (X) Ship Cost (Y)
1,068 4,489
1,026 5,611
767 3,290
885 4,113
1,156 4,883
1,146 5,425
892 4,414
938 5,506
769 3,346
677 3,673
1,174 6,542
1,009 5,088
12.8 (a) Interpret the slope of the fitted regression Sales = 842 − 37.5 Price. (b) If Price = 20, what is
the prediction for Sales? (c) Would the intercept be meaningful if this regression represents DVD
sales at Blockbuster?
12.10 The regression equation NetIncome = 2,277 + .0307 Revenue was fitted from a sample of 100
leading world companies (variables are in millions of dollars). (a) Interpret the slope. (b) Is the intercept
meaningful? Explain. (c) Make a prediction of NetIncome when Revenue = 1,000. (Data are
from www.forbes.com and Forbes 172, no. 2 [July 21, 2003], pp. 108-110.) Global100
Chapter 13 (no p-values): Section Exercise # 2, 4 ,6
13.2 Observations are taken on sales of a certain mountain bike in 30 sporting goods stores. The
regression model was Y = total sales (thousands of dollars), X1 = display floor space (square
meters), X2 = competitors' advertising expenditures (thousands of dollars), X3 = advertised price
(dollars per unit). (a) Write the fitted regression equation. (b) Interpret each coefficient. (c) Would
the intercept seem to have meaning in this regression? (d) Make a prediction for Sales when
FloorSpace = 80, CompetingAds = 100, and Price = 1,200. Bikes
13.4 Refer to the ANOVA table for this regression. (a) State the degrees of freedom for the F test for
overall significance. (b) Use Appendix F to look up the critical value of F for α = .05. (c) Calculate
the F statistic. Is the regression significant overall? (d) Calculate R2 and R2
adj, showing your
formulas clearly. Bikes
Source d.f. SS MS
Regression 3 1,196,410 398,803
Error 26 379,332 14,590
Total 29 1,575,742
13.6 Observations are taken on sales of a certain mountain bike in 30 sporting goods stores. The
regression model was Y = total sales (thousands of dollars), X1 = display floor space (square
meters), X2 = competitors' advertising expenditures (thousands of dollars), X3 = advertised
price (dollars per unit), X4 = rebate rate (percent of retail price). (a) Calculate the t statistic for
each coefficient to test for β = 0. (b) Look up the critical value of Student's t in Appendix D for a
two-tailed test at α = .01. Which coefficients differ significantly from zero? (c) Use Excel to find
the p-value for each coefficient. Bikes
Predictor Coefficient SE
Intercept 1225.4 397.3
FloorSpace      11.522     1.330
CompetingAds      −6.935     3.905
Price      −0.14955     0.08927
See attached files.

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