Elementary Statistics ( 3rd International Edition ) Isbn:9781260092561
3rd Edition
ISBN: 9781259969454
Author: William Navidi Prof.; Barry Monk Professor
Publisher: McGraw-Hill Education
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Chapter 13, Problem 5RE
a.
To determine
To find:The regression equation for the data.
b.
To determine
To find: The confidence interval for the data.
c.
To determine
To find:Whether the concentration of additive is useful in predicting the drying time.
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Students have asked these similar questions
Computer output from a least-squares regression analysis based on a sample of size 17 is shown in the table.
Term
COEFCOEF
SE CoefSE Coef
TT
Constant
7.43
0.59
12.59
xx
5.65
1.14
6.45
Assuming all conditions for inference are met, which of the following defines a 95 percent confidence interval for the slope of the least-squares regression line?
Consider the regression model Y = B0 + B1 X1 + B2 X2 + u. Suppose you want to
test the null hypothesis H0: B1 + B2 = 0, versus the alternative hypothesis H1: B1+
B2 != 0 (!= means "not equal to"). The data set consists of 100 observations.
(a) Suppose we use an F-statistic to conduct the test. What are the degrees of
freedom associated with this test statistic?
(b) Let G(.) be the CDF of the F-distribution for the F-statistic in part (b). Denote
the actual F-statistic by F_act. Suppose someone says that you should reject the null
at the 5% significance level if G(F_act)<0.05. Explain whether you agree with this
approach.
(c) Suppose you find that the F-test in part (b)-(c) and the test in part (a) yield
very different p-values. Do you think this result is correct? Briefly explain your
reasoning.
In a simple linear regression model with one predictor variable, what is the coefficient of determination (R-squared) if the Pearson's correlation coefficient between the predictor and response variable is 0.6?
Chapter 13 Solutions
Elementary Statistics ( 3rd International Edition ) Isbn:9781260092561
Ch. 13.1 - Prob. 7ECh. 13.1 - Prob. 8ECh. 13.1 - In Exercises 9 and 10, determine whether the...Ch. 13.1 - Prob. 10ECh. 13.1 - Prob. 11ECh. 13.1 - Prob. 12ECh. 13.1 - Prob. 13ECh. 13.1 - Prob. 14ECh. 13.1 - Prob. 15ECh. 13.1 - Prob. 16E
Ch. 13.1 - Prob. 17ECh. 13.1 - Prob. 18ECh. 13.1 - Prob. 19ECh. 13.1 - Prob. 20ECh. 13.1 - Prob. 21ECh. 13.1 - Prob. 22ECh. 13.1 - Prob. 23ECh. 13.1 - Prob. 24ECh. 13.1 - Prob. 25ECh. 13.1 - Prob. 26ECh. 13.1 - Prob. 27ECh. 13.1 - Prob. 28ECh. 13.1 - Prob. 26aECh. 13.1 - Calculator display: The following TI-84 Plus...Ch. 13.1 - Prob. 28aECh. 13.1 - Prob. 29ECh. 13.1 - Prob. 30ECh. 13.1 - Confidence interval for the conditional mean: In...Ch. 13.2 - Prob. 3ECh. 13.2 - Prob. 4ECh. 13.2 - Prob. 5ECh. 13.2 - Prob. 6ECh. 13.2 - Prob. 7ECh. 13.2 - Prob. 8ECh. 13.2 - Prob. 9ECh. 13.2 - Prob. 10ECh. 13.2 - Prob. 11ECh. 13.2 - Prob. 12ECh. 13.2 - Prob. 13ECh. 13.2 - Prob. 14ECh. 13.2 - Prob. 15ECh. 13.2 - Prob. 16ECh. 13.2 - Prob. 17ECh. 13.2 - Dry up: Use the data in Exercise 26 in Section...Ch. 13.2 - Prob. 19ECh. 13.2 - Prob. 20ECh. 13.2 - Prob. 21ECh. 13.3 - Prob. 7ECh. 13.3 - Prob. 8ECh. 13.3 - Prob. 9ECh. 13.3 - In Exercises 9 and 10, determine whether the...Ch. 13.3 - Prob. 11ECh. 13.3 - Prob. 12ECh. 13.3 - Prob. 13ECh. 13.3 - For the following data set: Construct the multiple...Ch. 13.3 - Engine emissions: In a laboratory test of a new...Ch. 13.3 - Prob. 16ECh. 13.3 - Prob. 17ECh. 13.3 - Prob. 18ECh. 13.3 - Prob. 19ECh. 13.3 - Prob. 20ECh. 13.3 - Prob. 21ECh. 13.3 - Prob. 22ECh. 13.3 - Prob. 23ECh. 13 - A confidence interval for 1 is to be constructed...Ch. 13 - A confidence interval for a mean response and a...Ch. 13 - Prob. 3CQCh. 13 - Prob. 4CQCh. 13 - Prob. 5CQCh. 13 - Prob. 6CQCh. 13 - Construct a 95% confidence interval for 1.Ch. 13 - Prob. 8CQCh. 13 - Prob. 9CQCh. 13 - Prob. 10CQCh. 13 - Prob. 11CQCh. 13 - Prob. 12CQCh. 13 - Prob. 13CQCh. 13 - Prob. 14CQCh. 13 - Prob. 15CQCh. 13 - Prob. 1RECh. 13 - Prob. 2RECh. 13 - Prob. 3RECh. 13 - Prob. 4RECh. 13 - Prob. 5RECh. 13 - Prob. 6RECh. 13 - Prob. 7RECh. 13 - Prob. 8RECh. 13 - Prob. 9RECh. 13 - Prob. 10RECh. 13 - Air pollution: Following are measurements of...Ch. 13 - Icy lakes: Following are data on maximum ice...Ch. 13 - Prob. 13RECh. 13 - Prob. 14RECh. 13 - Prob. 15RECh. 13 - Prob. 1WAICh. 13 - Prob. 2WAICh. 13 - Prob. 1CSCh. 13 - Prob. 2CSCh. 13 - Prob. 3CSCh. 13 - Prob. 4CSCh. 13 - Prob. 5CSCh. 13 - Prob. 6CSCh. 13 - Prob. 7CS
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- A linear regression model was fit to a set of data containing 18 observations. The computer output of the regression analysis is shown in the table. Term CoefCoef SE CoefSE Coef TT Constant 12.00 5.43 2.210 xx 0.694 0.241 2.880 Assume the conditions for regression are met. Which of the following defines the margin of error when a 95 percent confidence interval for the slope of the least-squares regression line is calculated? (1.75)(0.241) A (1.75)(0.694) B (1.96)(0.241) C (2.12)(0.241)) D (2.12)(0.694) Earrow_forwardNow, the predictors flyer and display were added to the dataset and a multiple linear regression model was fitted. Part of the R output is shown below – Estimate Standard Error Intercept 81.23 35.24 Price -0.0318 0.023 Flyer 10.21 3.28 Display 21.67 13.27 Adj R Square = 78.8% Calculate a 95% confidence interval of Flyer and interpret the same in the context of the problem. Can we say that promoting a product through fliers significantly affect its sales? What is the coefficient of multiple determination of this model? Interpret its value.arrow_forwardGive an example of a research question that would be suitable for computing a: a) Correlation coefficient b) Regression linearrow_forward
- a) Calculate the least square regression line for X on Y of the given data?b) Calculate the coefficient of correlation of the given date? Interpret the value of the coefficient?arrow_forwardGiven the estimated least square regression line y=2.48+1.63x, and the coefficient of determination of 0.81, What is the value of correlation coefficient?arrow_forwardPublic health researchers would like to evaluate whether information on age (in years) and weight (in kg) could be used to predict shoe size of students. The output of the linear regression analysis is given below. 95% confidence interval Unstandardized Beta t Lower bound Upper bound (Constant) 6.493 1.121 -5.191 18.177 Age (years) -0.462 -1.617 -1.037 0.114 Weight (kg) 0.155 7.568 0.114 0.197 Dependent variable: shoe size A) Write null hypotheses for the linear regression analysis. B) Interpret the results of the linear regression in not more than 100 words. C) Write a complete equation for the results of the linear regression analysisarrow_forward
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