active learning lecture slides for use with classroom response systems
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Copyright © 2014, 2011 Pearson Education, Inc. 1
Active Learning Lecture Slides
For use with Classroom Response Systems
Chapter 21The Simple RegressionModel
Copyright © 2014, 2011 Pearson Education, Inc. 2
The simple regression model (SRM) describes the population in regression analysis with one explanatory variable.
A. True
B. False
Copyright © 2014, 2011 Pearson Education, Inc. 3
The simple regression model (SRM) describes the population in regression analysis with one explanatory variable.
A. True
B. False
Copyright © 2014, 2011 Pearson Education, Inc. 4
The average of one variable given that another variable takes on a specific value is called…
A. an absolute mean.
B. a relative mean.
C. a conditional mean.
D. a conditional median.
Copyright © 2014, 2011 Pearson Education, Inc. 5
The average of one variable given that another variable takes on a specific value is called…
A. an absolute mean.
B. a relative mean.
C. a conditional mean.
D. a conditional median.
Copyright © 2014, 2011 Pearson Education, Inc. 6
The deviations of observed responses around the conditional means µy|x are called…
A. mistakes.
B. errors.
C. corrections.
D. averages.
Copyright © 2014, 2011 Pearson Education, Inc. 7
The deviations of observed responses around the conditional means µy|x are called…
A. mistakes.
B. errors.
C. corrections.
D. averages.
Copyright © 2014, 2011 Pearson Education, Inc. 8
Which of the following are assumptions the SRM makes about errors?
A. Independent
B. Equal variance
C. Normal
D. All of the above
Copyright © 2014, 2011 Pearson Education, Inc. 9
Which of the following are assumptions the SRM makes about errors?
A. Independent
B. Equal variance
C. Normal
D. All of the above
Copyright © 2014, 2011 Pearson Education, Inc. 10
The SRM makes assumptions about the values of the explanatory variable.
A. True
B. False
Copyright © 2014, 2011 Pearson Education, Inc. 11
The SRM makes assumptions about the values of the explanatory variable.
A. True
B. False
Copyright © 2014, 2011 Pearson Education, Inc. 12
Which of the following are conditions for the SRM?I. association between y and x is linear II. no obvious lurking variablesIII. errors are independentIV. variances of the residuals are similarV. residuals are nearly normal
A. I, II, and III
B. I, III, and V
C. I, II, III and IV
D. I, II, III, IV and V
Copyright © 2014, 2011 Pearson Education, Inc. 13
Which of the following are conditions for the SRM?I. association between y and x is linear II. no obvious lurking variablesIII. errors are independentIV. variances of the residuals are similarV. residuals are nearly normal
A. I, II, and III
B. I, III, and V
C. I, II, III and IV
D. I, II, III, IV and V
Copyright © 2014, 2011 Pearson Education, Inc. 14
The job of the standard error is to…
A. predict the variation in a sample.
B. estimate the mean variance.
C. estimate the sample to sample variation.
D. predict the sample to sample variation.
Copyright © 2014, 2011 Pearson Education, Inc. 15
The job of the standard error is to…
A. predict the variation in a sample.
B. estimate the mean variance.
C. estimate the sample to sample variation.
D. predict the sample to sample variation.
Copyright © 2014, 2011 Pearson Education, Inc. 16
Failing to reject H0: B1 = 0
A. proves B1 = 0
B. does not prove B1 = 0
C. proves proves B1 > 0
D. proves proves B1 < 0
Copyright © 2014, 2011 Pearson Education, Inc. 17
Failing to reject H0: B1 = 0
A. proves B1 = 0
B. does not prove B1 = 0
C. proves proves B1 > 0
D. proves proves B1 < 0
Copyright © 2014, 2011 Pearson Education, Inc. 18
Failure to reject H0 shows that B1 might be zero, not that it is zero.
A. True
B. False
Copyright © 2014, 2011 Pearson Education, Inc. 19
Failure to reject H0 shows that B1 might be zero, not that it is zero.
A. True
B. False
Copyright © 2014, 2011 Pearson Education, Inc. 20
An interval that is designed to hold a fraction (usually 95%) of the values of the response for a given value x of the explanatory variable in a regression is called a…
A. confidence interval.
B. t-interval.
C. z-interval.
D. prediction interval.
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