Mathematical Statistics with Applications
7th Edition
ISBN: 9781133384380
Author: Dennis Wackerly; William Mendenhall; Richard L. Scheaffer
Publisher: Cengage Learning US
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Chapter 15.10, Problem 60E
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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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- A sample of n = 15 pairs of X and Y scores produces a Pearson correlation of r = 0.45, SSY = 90. a) If the regression equation was found for these scores, how much of the Y variability would be predicted by the regression equation (SSregression) and how much would not be predicted (SSresidual)? b) Does the regression equation predict a significant portion of the variability for the Y scores? (Equivalently, is the Pearson correlation significant?)arrow_forwardThe maximum weights (in kilograms) for which one repetition of a half-squat can be performed and the jump heights (in centimeters) for 12 international soccer players are given in the accompanying table. The correlation coefficient, rounded to three decimal places, is r= 0.751. At α = 0.05, is there enough evidence to conclude that there is a significant linear correlation between the variables? Determine the standardized test statistic t=?arrow_forwardA sample of n = 25 pairs of scores (X and Y values) produces a correlation of r = –0.40. Are these sample data sufficient to conclude that there is a significant non-zero correlation between X and Y in the population? Use a two-tailed test at the α = 0.05 level of significance. Which proportion of the variance for the Y scores is predicted by the regression equation?arrow_forward
- Researchers have collected data on the rate of BO disease from a random sample of persons across the country aged 50 and above (n = 250). In particular, researchers are curious in studying a claim made by the cig industry that there is a negative relationship between smoking cigarettes and the risk of contracting BO’s. The researchers have calculated a Pearson’s r correlation of −.709 for the two variables. The researchers have also calculated (using a computer) a significance value of .005.In a paragraph of five to six sentences, based on the results from the correlation, what conclusions can the researchers make about the relationship between smoking and getting BO’s? Ensure that you mention the unit of analysis, the direction of the relationship, the strength of the relationship, whether the findings are statistically significant, and how accurately the results would reflect the population. Do these findings support the cig industry’s claim? Why or why not?arrow_forwardon the basis of the value of linear correlation coefficient, would you conclude, at the /r/>0.9 level, that the data can be reasonably modeled linear equation?arrow_forwardA random sample of 15 observations of house price and house size reveals a correlation coefficient of negative 46. The null and alternative hypotheses are given as the following (rho is population's correlation coefficient) : H0: rho ≥ 0 H1: rho < 0 Using 5% significance level, find the critical valuearrow_forward
- In a random sample of seven statistics students, the number of homework assignments missed (x) and the score on Exam #3 (y) were recorded. Use the (abbreviated) MINITAB output below to test for significant negative correlation between the number of homework assignments missed and the score on Exam #3 at the 1% level of significance. State hypotheses and conclusions.Pearson correlation of x and y = -0.935arrow_forwardWhat is the point estimate of the annual income of a salesperson with three years of college? Test whether the number of years in college has a significant impact on income at α= .05. What are the hypotheses? How do you test the hypotheses? What is the conclusion? What is the value of the correlation coefficient between dependent variable and independent variable? What is the implication of the correlation coefficient? What is the R Square of this model? What does it mean? Use the information in ANOVA table to calculate R square.arrow_forwardIn a certain type of metal test, the normal stress on a specimen is known to be functionally related to the shear resistance. What is the correlation between the two variables using Pearson product-moment correlation coefficient? Normal 27 29 26 28 28 24 Stress(x): 25 27 Shear 27 28 25 27 24 26 Resistance (y): 27 23 22 24arrow_forward
- A researcher believes that more sleep can result in better reaction time. A random sample of adults were involved in the study, where the amount of sleep they got the previous night was recorded and their reaction time was measured the next morning using a standard test for reaction time . The data is given in the table below. At the alpha = 0.05 level of significance , test the researcher's claim that there is a negative linear correlation between sleep and reaction time. Round all results to three decimal places .arrow_forwardAre seatbelts effective at saving lives? We wish to examine whether or not the use of seatbelts reduces fatalities at the a = 0.01 level of significance. Let pN represent the proportion of non-seatbelt wearing passengers who were involved in a crash and died and py represent the proportion of seatbelt wearing passengers who were involved in a crash and died. NOTE: The data used in this study were obtained through observational study...no experiment was conducted! Which would be correct hypotheses for this test? O Ho:PN = pY, H1:PN > pY Ho: PN = pY, H,:PN Py In a random sample of 321 non-seatbelt wearing passengers involved in a car crash, 30 were killed. In a random sample of 492 seatbelt wearing passengers involved in a car crash, 13 were killed. Find the test statistic (2 decimal places): Give the P-value (4 decimal places - if less than 0.001 answer 0): Which is the correct result: Reject the Null Hypothesis O Do not Reject the Null Hypothesis Which would be the appropriate…arrow_forwardIt is assumed that achievement test scores should be correlated with student's classroom performance. One would expect that students who consistently perform well in the classroom (tests, quizzes, etc.) would also perform well on a standardized achievement test (0 - 100 with 100 indicating high achievement). A teacher decides to examine this hypothesis. At the end of the academic year, she computes a correlation between the achievement test scores and the overall GPAS for her students over the entire year. The data for her class are provided below. Achievement 96 94 62 91 77 86 71 59 63 GPA 2.7 3.1 1.6 3.2 3.0 3.8 2.6 3.0 2.2 Achievement 84 98 75 72 86 85 71 93 90 GPA 1.7 3.6 2.6 2.9 2.4 3.4 2.8 3.7 3.2 The correlation coefficient is . (Use graphing calculator. Round answer to three decimal places.)arrow_forward
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