Mathematical Statistics with Applications
7th Edition
ISBN: 9780495110811
Author: Dennis Wackerly, William Mendenhall, Richard L. Scheaffer
Publisher: Cengage Learning
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Chapter 15.10, Problem 57E
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From the data of the following table: Calculate Spearman's rank correlation coefficient between x and y and determine its type. s
The following data are from a random sample of 10 students who participated in a study undertaken to investigate the effect of sleep time (measured in average number of hours of sleep per night) on GPA (grade point average, measured on a 4-point scale).
Student
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1
7
3.28
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9
3.16
3
8
3.75
4
6
2.50
5
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2.91
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3.53
8
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a. Find the equation between GPA (y) as function of sleep time (x).
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*(no use EXCEL)
Listed below are the overhead widths (in cm) of seals measured from photographs and the weights (in kg) of the seals. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the critical values of r using alpha equals 0.05.
Is there sufficient evidence to conclude that there is a linear correlation between overhead widths of seals from photographs and the weights of theseals?
Overhead Width
7.1
7.6
9.7
9.3
8.6
8.2
Weight
115
197
243
198
197
186
Chapter 15 Solutions
Mathematical Statistics with Applications
Ch. 15.3 - What significance levels between = .01 and = .15...Ch. 15.3 - Prob. 2ECh. 15.3 - Clinical data concerning the effectiveness of two...Ch. 15.3 - Prob. 4ECh. 15.3 - New food products are frequently subjected to...Ch. 15.3 - On clear, cold nights in the central Florida...Ch. 15.3 - A psychological experiment was conducted to...Ch. 15.3 - Refer to Exercise 12.15. Using the sign test, do...Ch. 15.3 - Prob. 9ECh. 15.4 - The accompanying table gives the scores of a group...
Ch. 15.4 - Refer to Exercise 15.4. What answers are obtained...Ch. 15.4 - Refer to Exercise 15.6(a). Answer the question by...Ch. 15.4 - Eight subjects were asked to perform a simple...Ch. 15.4 - Two methods, A and B, for controlling traffic were...Ch. 15.4 - Dental researchers have developed a new material...Ch. 15.4 - Refer to Exercise 12.16. With = .01, use the...Ch. 15.4 - Suppose that Y1, Y2,, Yn is a random sample from a...Ch. 15.4 - The spokesperson for an organization supporting...Ch. 15.6 - Find the p-values associated with each of the...Ch. 15.6 - In some tests of healthy, elderly men, a new drug...Ch. 15.6 - Two plastics, each produced by a different...Ch. 15.6 - Prob. 24ECh. 15.6 - Prob. 25ECh. 15.6 - Prob. 26ECh. 15.6 - Prob. 27ECh. 15.6 - Prob. 28ECh. 15.7 - The table that follows contains data on the leaf...Ch. 15.7 - Prob. 30ECh. 15.7 - Three different brands of magnetron tubes (the key...Ch. 15.7 - An experiment was conducted to compare the length...Ch. 15.7 - Prob. 33ECh. 15.7 - Prob. 34ECh. 15.7 - Prob. 35ECh. 15.8 - In a study of palatability of antibiotics for...Ch. 15.8 - Prob. 38ECh. 15.8 - Prob. 39ECh. 15.8 - A serious drought-related problem for farmers is...Ch. 15.8 - Prob. 41ECh. 15.8 - Prob. 42ECh. 15.8 - Prob. 43ECh. 15.8 - Prob. 44ECh. 15.8 - Prob. 45ECh. 15.9 - Prob. 46ECh. 15.9 - Prob. 47ECh. 15.9 - Prob. 48ECh. 15.9 - Prob. 49ECh. 15.9 - Prob. 50ECh. 15.9 - Prob. 52ECh. 15.10 - Prob. 53ECh. 15.10 - Prob. 54ECh. 15.10 - Prob. 55ECh. 15.10 - Prob. 56ECh. 15.10 - Prob. 57ECh. 15.10 - Prob. 58ECh. 15.10 - Refer to Exercise 11.4. Regard both book and...Ch. 15.10 - Prob. 60ECh. 15 - Prob. 62SECh. 15 - Prob. 63SECh. 15 - Prob. 64SECh. 15 - Prob. 65SECh. 15 - Prob. 67SECh. 15 - Prob. 69SECh. 15 - Prob. 70SECh. 15 - Prob. 71SECh. 15 - Prob. 72SECh. 15 - Prob. 74SECh. 15 - Prob. 75SECh. 15 - Prob. 76SECh. 15 - Prob. 77SECh. 15 - Prob. 78SE
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- Listed below are the overhead widths (in cm) of seals measured from photographs and the weights (in kg) of the seals. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the critical values of r using α=0.01. Is there sufficient evidence to conclude that there is a linear correlation between overhead widths of seals from photographs and the weights of the seals? Overhead Width 7.1 7.7 9.7 9.4 8.7 8.3 Weight 111 201 242 204 197 192 Construct a scatterplot. Choose the correct graph below. The linear correlation coefficient is r=enter your response here. (Round to three decimal places as needed.) The critical values are r=enter your response here. (Round to three decimal places as needed. Use a comma to separate answers as needed.)arrow_forwardListed below are the overhead widths (in cm) of seals measured from photographs and the weights (in kg) of the seals. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the critical values of r using α=0.01. Overhead width overhead weight 7.1 111 7.6 164 9.8 250 9.2 192 8.8 205 8.2 183 Is there sufficient evidence to conclude that there is a linear correlation between overhead widths of seals from photographs and the weights of the seals? The linear correlation coefficient is r=? (Round to three decimal places as needed.) The linear correlation coefficient is r=? (Round to three decimal places as needed.) The critical values are r=? (Round to three decimal places as needed. Use a comma to separate answers as needed.) Because the absolute value of the linear correlation coefficient is ______ than the positive critical value, there _______ sufficient evidence to support the claim that there is a linear…arrow_forwardRefer to Exercise 8.S.6. Analyze these data using a Wilcoxon signed-rank test.arrow_forward
- The National Safety Council of the U.S. released the following data on the incidence rates for fatal or lost-worktime injuries per 100 employees for several industries in three recent years. Compute r for each pair of years and determine which years are most highly correlated. Calculate r using 1. the formula and 2. function. Industry Year 1 Year 2 Year 3 Textile 0.46 0.48 0.69 Chemical 0.52 0.62 0.63 Communication 0.9 0.72 0.81 Machinery 1.5 1.74 2.1 Services 2.89 2.03 2.46 Nonferrous metals 1.8 1.92 2 Food 3.29 3.18 3.17 Government 5.73 4.43 4 By formula By Function By formula By Function r1 r2 r3 Please provide a step by step of calculation in excelto give me an understaning on how to calculate in future Thank you in advancearrow_forwardThe authors of this study report a Pearson correlation coefficient estimate of r = 0.23 with a p-value of <0.01. Interpret.arrow_forwardListed below are the overhead widths (in cm) of seals measured from photographs and the weights (in kg) of the seals. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the critical values of r using α=0.01. Is there sufficient evidence to conclude that there is a linear correlation between overhead widths of seals from photographs and the weights of the seals? Overhead Width 7.1 7.6 9.7 9.4 8.8 8.2 Weight 111 198 246 204 202 185 Construct a scatterplot. Choose the correct graph below. (inserted as picture) The linear correlation coefficient is r=__________ (Round to three decimal places as needed.) The critical values are r= (_______,________) (Round to three decimal places as needed. Use a comma to separate answers as needed.) Because the absolute value of the linear correlation coefficient is (greater,less than, equal to) than the positive…arrow_forward
- The accompanying data represent the number of days absent, x, and the final exam score, y, for a sample of college students in a general education course at a large state university. Absences and Final Exam Scores No. of absences, x 0 1 2 3 4 5 6 7 8 9 Final exam score, y 89.7 86.1 83.6 81.8 78.7 74.1 64.4 71.2 64.5 66.4 Critical Values for Correlation Coefficient n 3 0.9974 0.9505 0.8786 0.8117 0.7548 0.7079 0.66610 0.63211 0.60212 0.57613 0.55314 0.53215 0.51416 0.49717 0.48218 0.46819 0.45620 0.44421 0.43322 0.42323 0.41324 0.40425 0.39626 0.38827 0.38128 0.37429 0.36730 0.361n (a) The least-squaresregressionline treating number of absences as the explanatory variable and the final exam score as the response variable. y=negative 2.907−2.907x+89.133 (b) Interpret the slope and the…arrow_forwardThe accompanying data represent the number of days absent, x, and the final exam score, y, for a sample of college students in a general education course at a large state university. Absences and Final Exam Scores No. of absences, x 0 1 2 3 4 5 6 7 8 9 Final exam score, y 89.7 86.1 83.6 81.8 78.7 74.1 64.4 71.2 64.5 66.4 Critical Values for Correlation Coefficient n 3 0.9974 0.9505 0.8786 0.8117 0.7548 0.7079 0.66610 0.63211 0.60212 0.57613 0.55314 0.53215 0.51416 0.49717 0.48218 0.46819 0.45620 0.44421 0.43322 0.42323 0.41324 0.40425 0.39626 0.38827 0.38128 0.37429 0.36730 0.361n (a) The least-squaresregressionline treating number of absences as the explanatory variable and the final exam score as the response variable. y=negative 2.907−2.907x + 89.133 c) predict the final exam score for a student who…arrow_forwardThe accompanying data represent the number of days absent, x, and the final exam score, y, for a sample of college students in a general education course at a large state university. Absences and Final Exam Scores No. of absences, x 0 1 2 3 4 5 6 7 8 9 Final exam score, y 89.7 86.1 83.6 81.8 78.7 74.1 64.4 71.2 64.5 66.4 Critical Values for Correlation Coefficient n 3 0.9974 0.9505 0.8786 0.8117 0.7548 0.7079 0.66610 0.63211 0.60212 0.57613 0.55314 0.53215 0.51416 0.49717 0.48218 0.46819 0.45620 0.44421 0.43322 0.42323 0.41324 0.40425 0.39626 0.38827 0.38128 0.37429 0.36730 0.361n (a) The least-squaresregressionline treating number of absences as the explanatory variable and the final exam score as the response variable. y=negative 2.907−2.907x + 89.133 c) the final exam score for a student who kissed…arrow_forward
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