Bundle: Introduction to Statistics and Data Analysis, 5th + WebAssign Printed Access Card: Peck/Olsen/Devore. 5th Edition, Single-Term
5th Edition
ISBN: 9781305620711
Author: Roxy Peck, Chris Olsen, Jay L. Devore
Publisher: Cengage Learning
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Chapter 14.1, Problem 9E
a.
To determine
Construct a graph for the given
b.
To determine
Check whether the mean chlorine content is higher for a degree of delignification 8 or 10.
c.
To determine
Find the change in mean chlorine content when the degree of delignification increases from 8 to 9 and 9 to 10.
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The measure of standard error can also be applied to the parameter estimates resulting from linear regressions.
For example, consider the following linear regression equation that describes the relationship between education and wage:
WAGEi=β0+β1EDUCi+εi
where WAGEi is the hourly wage of person i (i.e., any specific person) and EDUCi is the number of years of education for that same person. The residual εi encompasses other factors that influence wage, and is assumed to be uncorrelated with education and have a mean of zero.
Suppose that after collecting a cross-sectional data set, you run an OLS regression to obtain the following parameter estimates:
WAGEi=−11.5+6.1 EDUCi
If the standard error of the estimate of β1 is 1.32, then the true value of β1 lies between(4.78, 4.12, 3.46, 5.44) and (6.76, 7.42, 8.74) . As the number of observations in a data set grows, you would expect this range to (DECREASE , INCREASE) in size.
A linear regression model has been estimated for the variables Y="monthly consumption of veal (kg)", X1="monthly monetary household income (thousand EUR)" and X2="household size (number of members)" using data for a random sample of 80 households. The following results have been obtained:
b0=0.3 b1=0.5 b2=0.7 R-sq=0.9 R=0.95，Interpret the value of regression coefficient b2.
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e. Find a 95% CI for the regression coefficient for temperature for both
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Chapter 14 Solutions
Bundle: Introduction to Statistics and Data Analysis, 5th + WebAssign Printed Access Card: Peck/Olsen/Devore. 5th Edition, Single-Term
Ch. 14.1 - Prob. 1ECh. 14.1 - The authors of the paper Weight-Bearing Activity...Ch. 14.1 - Prob. 3ECh. 14.1 - Prob. 4ECh. 14.1 - Prob. 5ECh. 14.1 - Prob. 6ECh. 14.1 - Prob. 7ECh. 14.1 - Prob. 8ECh. 14.1 - Prob. 9ECh. 14.1 - The relationship between yield of maize (a type of...
Ch. 14.1 - Prob. 11ECh. 14.1 - A manufacturer of wood stoves collected data on y...Ch. 14.1 - Prob. 13ECh. 14.1 - Prob. 14ECh. 14.1 - Prob. 15ECh. 14.2 - Prob. 16ECh. 14.2 - State as much information as you can about the...Ch. 14.2 - Prob. 18ECh. 14.2 - Prob. 19ECh. 14.2 - Prob. 20ECh. 14.2 - The ability of ecologists to identify regions of...Ch. 14.2 - Prob. 22ECh. 14.2 - Prob. 23ECh. 14.2 - Prob. 24ECh. 14.2 - Prob. 25ECh. 14.2 - Prob. 26ECh. 14.2 - This exercise requires the use of a statistical...Ch. 14.2 - Prob. 28ECh. 14.2 - The article The Undrained Strength of Some Thawed...Ch. 14.2 - Prob. 30ECh. 14.2 - Prob. 31ECh. 14.2 - Prob. 32ECh. 14.2 - Prob. 33ECh. 14.2 - This exercise requires the use of a statistical...Ch. 14.2 - This exercise requires the use of a statistical...Ch. 14.3 - Prob. 36ECh. 14.3 - Prob. 37ECh. 14.3 - Prob. 38ECh. 14.3 - Prob. 39ECh. 14.3 - The article first introduced in Exercise 14.28 of...Ch. 14.3 - Data from a random sample of 107 students taking a...Ch. 14.3 - Benevolence payments are monies collected by a...Ch. 14.3 - Prob. 43ECh. 14.3 - Prob. 44ECh. 14.3 - Prob. 45ECh. 14.3 - Prob. 46ECh. 14.3 - Exercise 14.26 gave data on fish weight, length,...Ch. 14.3 - Prob. 48ECh. 14.3 - Prob. 49ECh. 14.3 - Prob. 50ECh. 14.4 - Prob. 51ECh. 14.4 - Prob. 52ECh. 14.4 - The article The Analysis and Selection of...Ch. 14.4 - Prob. 54ECh. 14.4 - Prob. 55ECh. 14.4 - Prob. 57ECh. 14.4 - Prob. 58ECh. 14.4 - Prob. 59ECh. 14.4 - Prob. 60ECh. 14.4 - This exercise requires use of a statistical...Ch. 14.4 - Prob. 62ECh. 14 - Prob. 63CRCh. 14 - Prob. 64CRCh. 14 - The accompanying data on y = Glucose concentration...Ch. 14 - Much interest in management circles has focused on...Ch. 14 - Prob. 67CRCh. 14 - Prob. 68CRCh. 14 - Prob. 69CRCh. 14 - A study of pregnant grey seals resulted in n = 25...Ch. 14 - Prob. 71CRCh. 14 - Prob. 72CRCh. 14 - This exercise requires the use of a statistical...
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- An article in Wood Science and Technology, "Creep in Chipboard, Part 3: Initial Assessment of the Influence of Moisture Content and Level of Stressing on Rate of Creep and Time to Failure" (1981, Vol. 15, pp. 125-144) studied the deflection (mm) of particleboard from stress levels of relative humidity. Assume that the two variables are related according to the simple linear regression model. The data are shown below x = Stress level (%) 54 54 61 61 68 68 75 75 75 y = Deflection (mm) 16.473 18.693 14.305 15.121 13.505 11.64 11.168 12.534 11.224 a. Calculate the least square estimates of the intercept (a) and slope (b). What is the estimate of o (c)? b. Find the estimate of the mean deflection if the stress level can be limited to 69% (d). C. Estimate the change in the mean deflection associated with a 8% increment in stress level (e). (a) (Round your answer to 2 decimal places.) (b) i (Round your answer to 3 decimal places.) (c) i (Round your answer to 3 decimal places.) (d) i (Round…arrow_forwardAn article in Wood Science and Technology, "Creep in Chipboard, Part 3: Initial Assessment of the Influence of Moisture Content and Level of Stressing on Rate of Creep and Time to Failure" (1981, Vol. 15, pp. 125-144) studied the deflection (mm) of particleboard from stress levels of relative humidity. Assume that the two variables are related according to the simple linear regression model. The data are shown below x= Stress level (%) 54 54 61 61 68 68 75 75 75 y = Deflection (mm) 16.473 18.693 14.305 15.121 13.505 11.64 11.168 12.534 11.224 a. Calculate the least square estimates of the intercept (a) and slope (b). What is the estimate of o (c)? b. Find the estimate of the mean deflection if the stress level can be limited to 66% (d). C. Estimate the change in the mean deflection associated with a 5% increment in stress level (e). (a) i 32.05 (Round your answer to 2 decimal places.) (b) i ! (Round your answer to 3 decimal places.) (Round your answer to 3 decimal places.) i (d) i…arrow_forwardAn article in Wood Science and Technology, "Creep in Chipboard, Part 3: Initial Assessment of the Influence of Moisture Content and Level of Stressing on Rate of Creep and Time to Failure" (1981, Vol. 15, pp. 125-144) studied the deflection (mm) of particleboard from stress levels of relative humidity. Assume that the two variables are related according to the simple linear regression model. The data are shown below x = Stress level (%) 54 54 61 61 68 68 75 75 75 y = Deflection (mm) 16.473 18.693 14.305 15.121 13.505 11.64 11.168 12.534 11.224 a. Calculate the least square estimates of the intercept (a) and slope (b). What is the estimate of o?(c)? b. Find the estimate of the mean deflection if the stress level can be limited to 69% (d). c. Estimate the change in the mean deflection associated with a 9% increment in stress level (e). (a) i (Round your answer to 2 decimal places.) (b) i (Round your answer to 3 decimal places.) (c) i (Round your answer to 3 decimal places.) (d) i (Round…arrow_forward
- An article in Wood Science and Technology, "Creep in Chipboard, Part 3: Initial Assessment of the Influence of Moisture Content and Level of Stressing on Rate of Creep and Time to Failure" (1981, Vol. 15, pp. 125-144) studied the deflection (mm) of particleboard from stress levels of relative humidity. Assume that the two variables are related according to the simple linear regression model. The data are shown below. x- Stress level (%) 54 75 54 61 61 68 68 75 75 y- Deflection (mm) | 16.476 18.694 14.307 15.123 13.506 11.640 11.169 12.536 11.226 (a) Test for significance of regression usinga = 0.01. (b) Estimate to 3 decimal places the standard errors of the intercept and slope. se( ß o) = se( B 1) = iarrow_forwardA sales manager has collected the following data on annual sales (y) and years of experience (x) . Sales person Years of Experience (x) Annual Sales (K’000) (y) 1 80 3 97 4 92 4 102 6 103 6 8 111 10 119 10 123 11 117 13 136 Draw a scatter diagram. Does a linear relationship between x and y seem appropriate Estimate the simple linear regression line. Interpret the parameters in the model (c) What practical use could be made of this equation? Use the estimated regression equation to predict annual sales for a sales man with 9 years of experience At the 5% level of significance would…arrow_forwardLook at the following regression table where the dependent variable is the demand for illegal massage services in a city in the United States. Specifically, the dependent variable is the number of customers per hour (Models 1 and 2) or per day (Models 3 and 4). (a) Explain why the coefficient for Population/1,000 in Model 2 is very different from the one in Model 4?(b) Can you reject H0 in Model 1 if H0 : βP opulation/1,000 = 0.01, H1 : βPopulation/1,000 6= 0.01, and α = 0.01?arrow_forward
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