An Introduction to Mathematical Statistics and Its Applications (6th Edition)
6th Edition
ISBN: 9780134114217
Author: Richard J. Larsen, Morris L. Marx
Publisher: PEARSON
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Chapter 11.3, Problem 9Q
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Chapter 11 Solutions
An Introduction to Mathematical Statistics and Its Applications (6th Edition)
Ch. 11.2 - Crickets make their chirping sound by sliding one...Ch. 11.2 - The aging of whisky in charred oak barrels brings...Ch. 11.2 - Prob. 3QCh. 11.2 - Prob. 4QCh. 11.2 - Prob. 5QCh. 11.2 - Prob. 6QCh. 11.2 - The relationship between school funding and...Ch. 11.2 - (a) Find the equation of the least squares...Ch. 11.2 - Prob. 9QCh. 11.2 - Prob. 10Q
Ch. 11.2 - Prob. 11QCh. 11.2 - Verify that the coefficients a and b of the least...Ch. 11.2 - Prob. 13QCh. 11.2 - Prob. 14QCh. 11.2 - Prob. 15QCh. 11.2 - Prob. 16QCh. 11.2 - Prob. 17QCh. 11.2 - A graph of the luxury suite data in Question 8.2.5...Ch. 11.2 - Set up (but do not solve) the equations necessary...Ch. 11.2 - Prob. 20QCh. 11.2 - The growth of federal expenditures is one of the...Ch. 11.2 - Prob. 22QCh. 11.2 - Prob. 24QCh. 11.2 - Prob. 25QCh. 11.2 - Among mammals, the relationship between the age at...Ch. 11.2 - Prob. 27QCh. 11.2 - Years of experience buying and selling commercial...Ch. 11.2 - Prob. 29QCh. 11.2 - The following table shows a portion of the results...Ch. 11.3 - Insect flight ability can be measured in a...Ch. 11.3 - The best straight line through the Massachusetts...Ch. 11.3 - Based on the data in Question 11.2.1, the...Ch. 11.3 - Suppose an experimenter intends to do a regression...Ch. 11.3 - Prob. 5QCh. 11.3 - Prob. 6QCh. 11.3 - Prob. 7QCh. 11.3 - Set up and carry out an appropriate hypothesis...Ch. 11.3 - Test H0:1=0 versus H1:10 for the plumage...Ch. 11.3 - Prob. 10QCh. 11.3 - Derive a formula for a 95% confidence interval for...Ch. 11.3 - Which, if any, of the assumptions of the simple...Ch. 11.3 - Prob. 13QCh. 11.3 - Construct a 90% confidence interval for 2 in the...Ch. 11.3 - Regression techniques can be very useful in...Ch. 11.3 - Construct a 95% confidence interval for E(Y2.750)...Ch. 11.3 - Prob. 18QCh. 11.3 - The fuel economy (in miles per gallon) of an...Ch. 11.3 - In the radioactive exposure example in Question...Ch. 11.3 - Attorneys representing a group of male buyers...Ch. 11.3 - Prob. 23QCh. 11.3 - Show that i=1n(YiY)2=i=1n(YiYi)2+i=1n(YiY)2 for...Ch. 11.4 - Prob. 1QCh. 11.4 - Prob. 2QCh. 11.4 - Prob. 3QCh. 11.4 - Prob. 4QCh. 11.4 - Prob. 5QCh. 11.4 - Let the random variable X take on the values...Ch. 11.4 - Prob. 7QCh. 11.4 - Prob. 8QCh. 11.4 - Prob. 9QCh. 11.4 - Prob. 10QCh. 11.4 - Some baseball fans believe that the number of home...Ch. 11.4 - Many people believe that a salary bonus is a...Ch. 11.4 - The extent to which stress is a contributing...Ch. 11.4 - Burglary and larceny both involve the illegal...Ch. 11.4 - A common saying in golf is You drive for show, but...Ch. 11.5 - Suppose that X and Y have a bivariate normal pdf...Ch. 11.5 - Suppose that X and Y have a bivariate normal...Ch. 11.5 - Prob. 3QCh. 11.5 - Suppose that the random variables X and Y have a...Ch. 11.5 - Prob. 5QCh. 11.5 - Give conditions on a0,b0, and u so that...Ch. 11.5 - Prob. 7QCh. 11.5 - In a study of heart disease (79), the weight (in...Ch. 11.5 - Prob. 9QCh. 11.5 - Prob. 10QCh. 11.5 - The National Collegiate Athletic Association has...
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- The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.arrow_forwardOlympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forwardFind the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_forward
- Consider the following variables: Y=daily productivity score (measured in points) X1=0 if undergraduate student,1 if graduate student X2=hours of sleep per night 1. If you want to test whether type of student modifies the association between hours of sleep per night and daily productivity score, which model (from attached image) should you consider and what is the null hypothesis for this test? A. Use Model 3 and test H0: β2=0 B. Use Model 5 and test H0: β3=0 C. Use Model 5 and test H0: β1=0 D. Use Model 5 and test H0: β2=0 E. Use Model 2 and test H0: β1=0 2. Suppose that you decide to use Model 5 (from pocture attached) to describe the relationship between type of student, hours of sleep per night, and daily productivity score. You use the method of least squares to obtain the following: Y= -0.5 + 3(X1) + 1.5(X2) + 2.5(X1X2) What is the estimated slope relating hours of sleep per night and daily productivity score among undergraduate students? A. 2 B. None of…arrow_forward1. A study of the potential of acrylonitrile to produce brain tumors in rats was conducted by administering the carcinogen in drinking water for 24 months. The results of the study for female rats are tabulated below: Dose (mg/kg-day) Brain tumor incidence 0 1/179 0.12 1/90 0.36 2/91 1.25 4/85 3.65 6/90 10.89 23/88 (a) Determine the potency factor (PF) of the dose-response relationship (assume it is linear). (Don’t forget to account for the one rat that had a brain tumor even though he wasn’t exposed to the chemical). (b) How accurate is the linear model for this data?arrow_forwardA sample of sunshine (x) in percent and temperature in O Fahrenheit (y) is recorded below to perform a linear regression test for whether or not correlation exists at α = .05. Assume test conditions are satisfied. x 28.6 32.1 35 31.6 28.6 30 26.6 33.2 24.2 31.3 y 75.4 91.3 86.9 90.7 85.8 88.3 72.5 86.4 70.7 89.4 What is the regression equation and what is the value of y^y^ when x = 25?arrow_forward
- The birth lengths in cm (x) and birth weights in kg (y) of a sample of 50 newborn female babies are compared, yielding a correlation coefficient of r=0.578 and a linear regression equation of ŷ =−8.89+0.243x The babies all had lengths between 46.5 and 53.0 cm, and weights between 2.50 and 4.05 kg. Based on this, predict the birth weight of a newborn female baby with a birth length of 48.5 cm.arrow_forwardA major credit card company is interested in whether there is a linear relationship between its internal rating of a customer’s credit risk and that of an independent rating agency. The company collected a random sample of 200 customers and used the data to test the claim that there is a linear relationship. The following hypotheses were used to test the claim. H0:β1=0Ha:β1≠0 The test yielded a t-value of 3.34 with a corresponding p-value of 0.001. Which of the following is the correct interpretation of the p-value? If the alternative hypothesis is true, the probability of observing a test statistic at least as extreme as 3.34 is 0.001. If the alternative hypothesis is true, the probability of observing a test statistic at least as extreme as 3.34 is 0.001. A If the alternative hypothesis is true, the probability of observing a test statistic of 3.34 or greater is 0.001. If the alternative hypothesis is true, the probability of observing a test statistic of 3.34 or greater…arrow_forward1) Find the regression equation and r value Drop Height, y (m) Square of Mean Fall time, t^2 (s^2) 0.100 0.0188 0.300 0.0576 0.500 0.0980 1.000 0.198 1.500 0.305 2.500 0.508arrow_forward
- Test the null hypothesis that the slope is zero versus the two-sided alternative in the following setting using the alpha=0.05 signifiance level. n=20, yhat=28.5+1.4x, and SEb1=0.65arrow_forwardIn a regression analysis involving 30 observations, the following estimated regression equation was obtained. ŷ = 16.7 + 3.5x1 − 2.3x2 + 7.9x3 + 2.9x4 (a)Interpret b1 in this estimated regression equation. -b1 = 7.9 is an estimate of the change in y corresponding to a 1 unit change in x3 when x1, x2, and x4 are held constant. -b1 = 2.9 is an estimate of the change in y corresponding to a 1 unit change in x4 when x1, x2, and x3 are held constant. -b1 = 3.5 is an estimate of the change in y corresponding to a 1 unit change in x1 when x2, x3, and x4 are held constant. -b1 = 3.5 is an estimate of the change in y corresponding to a 1 unit change in x2 when x1, x3, and x4 are held constant. -b1 = −2.3 is an estimate of the change in y corresponding to a 1 unit change in x1 when x2, x3, and x4 are held constant.Interpret b2 in this estimated regression equation. -b2 = −2.3 is an estimate of the change in y corresponding to a 1 unit change in x1 when x2, x3, and x4 are held…arrow_forwardGiven are five observations collected in a regression study on two variables. xi 2 6 9 13 20 yi 7 18 9 26 23 Develop the estimated regression equation for these data. ŷ = (c) Use the estimated regression equation to predict the value of y when x = 20.arrow_forward
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