Question 1

In a sample of n = 36,the Student's t test statistic for a correlation of r = −.450 would be

Accepted Answer

A) −2.110 
B) −2.938 
C) −2.030 
D) impossible to calculate without knowing α. 
A) −2.110 
B) −2.938 
C) −2.030 
D) impossible to calculate without knowing α.

Question 2

The correlation coefficient r always has the same sign as b1 in Y = b0 + b1X.

Accepted Answer

A) True 
 B)False

Question 3

In a sample of n = 27,the critical value of Student's t for a two-tailed test of significance for a simple bivariate regression at α = .05 is

Accepted Answer

A) ±2.060 
B) ±2.052 
C) ±2.898 
D) ±2.074 
A) ±2.060 
B) ±2.052 
C) ±2.898 
D) ±2.074

Question 4

Which is not a characteristic of the logistic regression model?

Accepted Answer

A) It postulates an S-shaped relationship between X and Y. 
B) It can best be fitted using the maximum likelihood method. 
C) Predictions from the fitted logit model are either 0 or 1. 
D) The logistic model cannot yield predictions greater than 1. 
A) It postulates an S-shaped relationship between X and Y. 
B) It can best be fitted using the maximum likelihood method. 
C) Predictions from the fitted logit model are either 0 or 1. 
D) The logistic model cannot yield predictions greater than 1.

Question 5

When X is farther from its mean,the prediction interval and confidence interval for Y become wider.

Accepted Answer

A) True 
 B)False

Question 6

When using the least squares method,the column of residuals always sums to zero.

Accepted Answer

A) True 
 B)False

Question 7

The sample coefficient of correlation does not have which property?

Accepted Answer

A) It can range from −1.00 up to +1.00. 
B) It is also sometimes called Pearson's r. 
C) It is tested for significance using a t-test. 
D) It assumes that Y is the dependent variable. 
A) It can range from −1.00 up to +1.00. 
B) It is also sometimes called Pearson's r. 
C) It is tested for significance using a t-test. 
D) It assumes that Y is the dependent variable.

Question 8

A local trucking company fitted a regression to relate the travel time (days)of its shipments as a function of the distance traveled (miles).The fitted regression is Time = −7.126 + 0.0214 Distance.If Distance increases by 50 miles,the expected Time would increase by

Accepted Answer

A) 1.07 days. 
B) 7.13 days. 
C) 2.14 days. 
D) 1.73 days. 
A) 1.07 days. 
B) 7.13 days. 
C) 2.14 days. 
D) 1.73 days.

Question 9

In a simple regression Y = b0 + b1X where Y = number of robberies in a city (thousands of robberies),X = size of the police force in a city (thousands of police),and n = 45 randomly chosen large U.S.cities in 2008,we would be least likely to see which problem?

Accepted Answer

A) Autocorrelated residuals (because this is time-series data) 
B) Heteroscedastic residuals (because we are using totals uncorrected for city size) 
C) Nonnormal residuals (because a few larger cities may skew the residuals) 
D) High leverage for some observations (because some cities may be huge) 
A) Autocorrelated residuals (because this is time-series data) 
B) Heteroscedastic residuals (because we are using totals uncorrected for city size) 
C) Nonnormal residuals (because a few larger cities may skew the residuals) 
D) High leverage for some observations (because some cities may be huge)

Question 10

There are usually several possible regression lines that will minimize the sum of squared errors.

Accepted Answer

A) True 
 B)False

Question 11

In a sample of n = 23,the Student's t test statistic for a correlation of r = .500 would be

Accepted Answer

A) 2.559 
B) 2.819 
C) 2.646 
D) impossible to calculate without knowing α. 
A) 2.559 
B) 2.819 
C) 2.646 
D) impossible to calculate without knowing α.

Question 12

William used a sample of 68 large U.S.cities to estimate the relationship between Crime (annual property crimes per 100,000 persons)and Income (median annual income per capita,in dollars).His estimated regression equation was Crime = 428 + 0.050 Income.We can conclude that

Accepted Answer

A) the slope is small so Income has no effect on Crime. 
B) crime seems to create additional income in a city. 
C) wealthy individuals tend to commit more crimes,on average. 
D) the intercept is irrelevant since zero median income is impossible in a large city. 
A) the slope is small so Income has no effect on Crime. 
B) crime seems to create additional income in a city. 
C) wealthy individuals tend to commit more crimes,on average. 
D) the intercept is irrelevant since zero median income is impossible in a large city.

Question 13

If the attendance at a baseball game is to be predicted by the equation Attendance = 16,500 − 75 Temperature,what would be the predicted attendance if Temperature is 90 degrees?

Accepted Answer

A) 6,750 
B) 9,750 
C) 12,250 
D) 10,020 
A) 6,750 
B) 9,750 
C) 12,250 
D) 10,020

Question 14

Which is not correct regarding the estimated slope of the OLS regression line?

Accepted Answer

A) It is divided by its standard error to obtain its t statistic. 
B) It shows the change in Y for a unit change in X. 
C) It is chosen so as to minimize the sum of squared errors. 
D) It may be regarded as zero if its p-value is less than α. 
A) It is divided by its standard error to obtain its t statistic. 
B) It shows the change in Y for a unit change in X. 
C) It is chosen so as to minimize the sum of squared errors. 
D) It may be regarded as zero if its p-value is less than α.

Question 15

A negative correlation between two variables X and Y usually yields a negative p-value for r.

Accepted Answer

A) True 
 B)False

Question 16

The fitted intercept in a regression has little meaning if no data values near X = 0 have been observed.

Accepted Answer

A) True 
 B)False

Question 17

Studentized (or standardized)residuals permit us to detect cases where the regression predicts poorly.

Accepted Answer

A) True 
 B)False

Question 18

When comparing the 90 percent prediction and confidence intervals for a given regression analysis

Accepted Answer

A) the prediction interval is narrower than the confidence interval. 
B) the prediction interval is wider than the confidence interval. 
C) there is no difference between the size of the prediction and confidence intervals. 
D) no generalization is possible about their comparative width. 
A) the prediction interval is narrower than the confidence interval. 
B) the prediction interval is wider than the confidence interval. 
C) there is no difference between the size of the prediction and confidence intervals. 
D) no generalization is possible about their comparative width.

Question 19

A financial regression yielded a standard error of 12 dollars,so a residual of 23 dollars would be

Accepted Answer

A) a rather poor prediction. 
B) an extreme outlier in the residuals. 
C) an observation with high leverage. 
D) an outlier,but not extreme. 
A) a rather poor prediction. 
B) an extreme outlier in the residuals. 
C) an observation with high leverage. 
D) an outlier,but not extreme.

Question 20

In simple linear regression,the coefficient of determination (R2)is estimated from sums of squares in the ANOVA table.

Accepted Answer

A) True 
 B)False

In a sample of n = 36,the Student's t test statistic for a correlation of r = −.450 would be

The correlation coefficient r always has the same sign as b1 in Y = b0 + b1X.

In a sample of n = 27,the critical value of Student's t for a two-tailed test of significance for a simple bivariate regression at α = .05 is

Which is not a characteristic of the logistic regression model?

When X is farther from its mean,the prediction interval and confidence interval for Y become wider.

When using the least squares method,the column of residuals always sums to zero.

The sample coefficient of correlation does not have which property?

A local trucking company fitted a regression to relate the travel time (days)of its shipments as a function of the distance traveled (miles).The fitted regression is Time = −7.126 + 0.0214 Distance.If Distance increases by 50 miles,the expected Time would increase by

In a simple regression Y = b0 + b1X where Y = number of robberies in a city (thousands of robberies),X = size of the police force in a city (thousands of police),and n = 45 randomly chosen large U.S.cities in 2008,we would be least likely to see which problem?

There are usually several possible regression lines that will minimize the sum of squared errors.

In a sample of n = 23,the Student's t test statistic for a correlation of r = .500 would be

William used a sample of 68 large U.S.cities to estimate the relationship between Crime (annual property crimes per 100,000 persons)and Income (median annual income per capita,in dollars).His estimated regression equation was Crime = 428 + 0.050 Income.We can conclude that

If the attendance at a baseball game is to be predicted by the equation Attendance = 16,500 − 75 Temperature,what would be the predicted attendance if Temperature is 90 degrees?

Which is not correct regarding the estimated slope of the OLS regression line?

A negative correlation between two variables X and Y usually yields a negative p-value for r.

The fitted intercept in a regression has little meaning if no data values near X = 0 have been observed.

Studentized (or standardized)residuals permit us to detect cases where the regression predicts poorly.

When comparing the 90 percent prediction and confidence intervals for a given regression analysis

A financial regression yielded a standard error of 12 dollars,so a residual of 23 dollars would be

In simple linear regression,the coefficient of determination (R2)is estimated from sums of squares in the ANOVA table.

Overview of Statistics

Data Collection

Describing Data Visually

Descriptive Statistics

Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling Distributions and Estimation

One-Sample Hypothesis Tests

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Exam 12: Simple Regression

In a sample of n = 36,the Student's t test statistic for a correlation of r = −.450 would be

The correlation coefficient r always has the same sign as b1 in Y = b0 + b1X.

In a sample of n = 27,the critical value of Student's t for a two-tailed test of significance for a simple bivariate regression at α = .05 is

Which is not a characteristic of the logistic regression model?

When X is farther from its mean,the prediction interval and confidence interval for Y become wider.

When using the least squares method,the column of residuals always sums to zero.

The sample coefficient of correlation does not have which property?

A local trucking company fitted a regression to relate the travel time (days)of its shipments as a function of the distance traveled (miles).The fitted regression is Time = −7.126 + 0.0214 Distance.If Distance increases by 50 miles,the expected Time would increase by

In a simple regression Y = b0 + b1X where Y = number of robberies in a city (thousands of robberies),X = size of the police force in a city (thousands of police),and n = 45 randomly chosen large U.S.cities in 2008,we would be least likely to see which problem?

There are usually several possible regression lines that will minimize the sum of squared errors.

In a sample of n = 23,the Student's t test statistic for a correlation of r = .500 would be

William used a sample of 68 large U.S.cities to estimate the relationship between Crime (annual property crimes per 100,000 persons)and Income (median annual income per capita,in dollars).His estimated regression equation was Crime = 428 + 0.050 Income.We can conclude that

If the attendance at a baseball game is to be predicted by the equation Attendance = 16,500 − 75 Temperature,what would be the predicted attendance if Temperature is 90 degrees?

Which is not correct regarding the estimated slope of the OLS regression line?

A negative correlation between two variables X and Y usually yields a negative p-value for r.

The fitted intercept in a regression has little meaning if no data values near X = 0 have been observed.

Studentized (or standardized)residuals permit us to detect cases where the regression predicts poorly.

When comparing the 90 percent prediction and confidence intervals for a given regression analysis

A financial regression yielded a standard error of 12 dollars,so a residual of 23 dollars would be

In simple linear regression,the coefficient of determination (R2)is estimated from sums of squares in the ANOVA table.

Overview of Statistics

Data Collection

Describing Data Visually

Descriptive Statistics

Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling Distributions and Estimation

One-Sample Hypothesis Tests

Two-Sample Hypothesis Tests

Analysis of Variance

Multiple Regression

Chi-Square Tests

Filters