Question 1

One uses _________ to predict the value of a response variable for a given value of an explanatory variable.

Accepted Answer

A)  correlation 
B)  standard deviation 
C)  association 
D)  regression 
A)  correlation 
B)  standard deviation 
C)  association 
D)  regression D

Question 2

The correlation between two variables x and y is 0.5. If we used a regression line to predict y using x, what percent of the variation in y would be explained?

Accepted Answer

A)  50% 
B)  25% 
C)  2.23% 
D)  75% 
E)  70.7% 
A)  50% 
B)  25% 
C)  2.23% 
D)  75% 
E)  70.7% B

Question 3

If the least-squares regression line for predicting y from x is y = 40 + 10x, what is the predicted value of y when x = 5?

Accepted Answer

A)  250 
B)  90 
C)  50 
D)  40 
E)  10 
A)  250 
B)  90 
C)  50 
D)  40 
E)  10 B

Question 4

A variable such that its impact on the results cannot be separated from the impact of the explanatory variable on the outcome is called a

Accepted Answer

A)  treatment. 
B)  confounding variable. 
C)  response variable. 
D)  correlation. 
A)  treatment. 
B)  confounding variable. 
C)  response variable. 
D)  correlation.

Question 5

If there were something genetic which made people simultaneously more susceptible to both smoking and lung cancer, that would be an instance of

Accepted Answer

A)  causation. 
B)  common response. 
C)  the placebo effect. 
D)  confounding. 
A)  causation. 
B)  common response. 
C)  the placebo effect. 
D)  confounding.

Question 6

In a fisheries researcher's experiment, the correlation between the number of eggs in the nest and the number of viable (surviving) eggs for a sample of nests is r = 0.67.
The equation of the regression line for number of viable eggs y versus number of eggs in the nest x is y = 0.72x + 17.07. For a nest with 140 eggs, what is the predicted number of viable eggs?

Accepted Answer

A)  114 eggs 
B)  116 eggs 
C)  118 eggs 
D)  120 eggs 
E)  None of these answers are correct 
A)  114 eggs 
B)  116 eggs 
C)  118 eggs 
D)  120 eggs 
E)  None of these answers are correct

Question 7

A study of child development measures the age (in months) at which a child begins to talk and also the child's score on an ability test given several years later. The study asks whether the age at which a child talks helps predict the later test score. The least- squares regression line of test score y on age x is y = 110 - 1.3x. According to this regression line, what happens (on the average) when a child starts talking one month later?

Accepted Answer

A)  The test score goes down 110 points. 
B)  The test score goes down 1.3 points. 
C)  The test score goes up 110 points. 
D)  The test score goes up 1.3 points. 
E)  The test score is 108.7. 
A)  The test score goes down 110 points. 
B)  The test score goes down 1.3 points. 
C)  The test score goes up 110 points. 
D)  The test score goes up 1.3 points. 
E)  The test score is 108.7.

Question 8

If the least-squares regression line for predicting y from x is y = 500 - 20x, what is the predicted value of y when x = 10?

Accepted Answer

A)  300 
B)  500 
C)  4800 
D)  700 
E)  20 
A)  300 
B)  500 
C)  4800 
D)  700 
E)  20

Question 9

A social scientist wants to use subjects' number of hours of television watched to predict their score on a test of propensity to violence. Subjects who watch more television do tend to get higher scores on the test. But regressing their violence test score on their hours of television watch explained only 16 percent of the total score. What is the correlation between their hours of television watched and violence test scores?

Accepted Answer

A)  0.16 
B)  -0.16 
C)  0.40 
D)  -0.40 
E)  0.32 
A)  0.16 
B)  -0.16 
C)  0.40 
D)  -0.40 
E)  0.32

Question 10

A social scientist learns, upon analyzing her data, that the correlation between a subject's hours of television watched and their score on a test that measures propensity to violence is r = 0.3. One way to use r is to compute the percent of the variation in the violence test score that can be explained by the straight-line relationship between that violence test score and hours of television watched. This percent is about

Accepted Answer

A)  30%. 
B)  70%. 
C)  9%. 
D)  21%. 
E)  7%. 
A)  30%. 
B)  70%. 
C)  9%. 
D)  21%. 
E)  7%.

Question 11

Students who study statistics in college tend to score higher on the Graduate Record Examinations (GRE) math section than students who do not study statistics. Which is true?

Accepted Answer

A)  This shows that studying statistics improves your knowledge for the GRE. 
B)  Students who choose to study statistics are probably already good at math, so we can't conclude anything about cause-and-effect. 
C)  This makes no sense because you can't compute the correlation between studying statistics and GRE math section test scores. 
D)  There is a positive correlation between whether or not a student studied statistics and the student's GRE math section test score. 
A)  This shows that studying statistics improves your knowledge for the GRE. 
B)  Students who choose to study statistics are probably already good at math, so we can't conclude anything about cause-and-effect. 
C)  This makes no sense because you can't compute the correlation between studying statistics and GRE math section test scores. 
D)  There is a positive correlation between whether or not a student studied statistics and the student's GRE math section test score.

Question 12

A high correlation between two variables does not always mean that changes in one cause changes in the other. The best way to get good evidence that cause-and-effect is present is to

Accepted Answer

A)  select a simple random sample from the population of interest. 
B)  arrange the data in a two-way table. 
C)  carry out a randomized comparative experiment. 
D)  make a scatterplot and look for a strong association. 
E)  make a histogram and look for outliers. 
A)  select a simple random sample from the population of interest. 
B)  arrange the data in a two-way table. 
C)  carry out a randomized comparative experiment. 
D)  make a scatterplot and look for a strong association. 
E)  make a histogram and look for outliers.

Question 13

Suppose that the least-squares regression line for predicting y from x is y = 100 + 1.3x. Which of the following is a possible value for the correlation between x and y?

Accepted Answer

A)  1.3 
B)  -1.3 
C)  0 
D)  -0.5 
E)  0.5 
A)  1.3 
B)  -1.3 
C)  0 
D)  -0.5 
E)  0.5

Question 14

The correlation between two variables x and y is -0.6. If we used a regression line to predict y using x, what percent of the variation in y would be explained?

Accepted Answer

A)  77% 
B)  -36% 
C)  36% 
D)  -6% 
E)  6% 
A)  77% 
B)  -36% 
C)  36% 
D)  -6% 
E)  6%

Question 15

In a fisheries researcher's experiment, the correlation between the number of eggs in the nest and the number of viable (surviving) eggs for a sample of nests is r = 0.67.
The correlation r = 0.67 shows that the fact that the nests have different number of eggs explains

Accepted Answer

A)  about 27% of the observed variation in the number of surviving eggs. 
B)  about 45% of the observed variation in the number of surviving eggs. 
C)  about 67% of the observed variation in the number of surviving eggs. 
D)  about 95% of the observed variation in the number of surviving eggs. 
E)  why some people fish at different places in the river. 
A)  about 27% of the observed variation in the number of surviving eggs. 
B)  about 45% of the observed variation in the number of surviving eggs. 
C)  about 67% of the observed variation in the number of surviving eggs. 
D)  about 95% of the observed variation in the number of surviving eggs. 
E)  why some people fish at different places in the river.

Question 16

A study found correlation r = 0.43 between high school math grades (on a 0 to 100 scale) and income 10 years after school. This says that the fact that hot dogs have different amounts of salt explains about

Accepted Answer

A)  18.5% of the observed variation in their calorie counts. 
B)  43% of the observed variation in their calorie counts. 
C)  65.6% of the observed variation in their calorie counts. 
D)  98% of the observed variation in their calorie counts. 
A)  18.5% of the observed variation in their calorie counts. 
B)  43% of the observed variation in their calorie counts. 
C)  65.6% of the observed variation in their calorie counts. 
D)  98% of the observed variation in their calorie counts.

Question 17

The evidence that smoking causes lung cancer is very strong. But it is not the strongest possible statistical evidence because

Accepted Answer

A)  we can't do experiments to compare smokers and non-smokers. 
B)  only smokers have been studied. 
C)  the studies of the effects of smoking are not double-blind. 
D)  all the studies of the effects of smoking involve animals, not humans. 
A)  we can't do experiments to compare smokers and non-smokers. 
B)  only smokers have been studied. 
C)  the studies of the effects of smoking are not double-blind. 
D)  all the studies of the effects of smoking involve animals, not humans.

Question 18

A least-squares regression line is not just any line drawn through the points of a scatterplot. What is special about a least-squares regression line?

Accepted Answer

A)  It passes through all the points. 
B)  It minimizes the squared values of the data. 
C)  It has slope equal to the correlation between the two variables. 
D)  It describes how a response variable y changes as an explanatory variable x takes different values. 
E)  It minimizes the sum of the squared vertical distances of the data points from the line. 
A)  It passes through all the points. 
B)  It minimizes the squared values of the data. 
C)  It has slope equal to the correlation between the two variables. 
D)  It describes how a response variable y changes as an explanatory variable x takes different values. 
E)  It minimizes the sum of the squared vertical distances of the data points from the line.

Question 19

A report in a medical journal notes that the risk of developing Alzheimer's disease among subjects who (voluntarily) regularly took the anti-inflammatory drug ibuprofen (the active ingredient in Advil) was about half the risk among those who did not. Is this good evidence that ibuprofen is effective in preventing Alzheimer's disease?

Accepted Answer

A)  Yes, because the study was a randomized, comparative experiment. 
B)  No, because the effect of ibuprofen is confounded with the placebo effect. 
C)  Yes, because the results were published in a reputable professional journal. 
D)  No, because this is an observational study. A clinical trial would be needed to confirm (or not confirm) the observed effect. 
E)  Yes, because a 50% reduction can't happen just by chance. 
A)  Yes, because the study was a randomized, comparative experiment. 
B)  No, because the effect of ibuprofen is confounded with the placebo effect. 
C)  Yes, because the results were published in a reputable professional journal. 
D)  No, because this is an observational study. A clinical trial would be needed to confirm (or not confirm) the observed effect. 
E)  Yes, because a 50% reduction can't happen just by chance.

Question 20

A year-long fitness center study sought to determine if there is a relationship between the amount of muscle mass gained y (kilograms) and the weekly time spent working out under the guidance of a trainer x (minutes.) The resulting least-squares regression line for the study is y = 2.04 + 0.12x.
For each additional minute (weekly) spent working out, the average muscle mass changed by

Accepted Answer

A)  2.04 kg 
B)  0.12 kg 
C)  204 kg. 
D)  12 kg. 
A)  2.04 kg 
B)  0.12 kg 
C)  204 kg. 
D)  12 kg.

One uses _________ to predict the value of a response variable for a given value of an explanatory variable.

The correlation between two variables x and y is 0.5. If we used a regression line to predict y using x, what percent of the variation in y would be explained?

If the least-squares regression line for predicting y from x is y = 40 + 10x, what is the predicted value of y when x = 5?

A variable such that its impact on the results cannot be separated from the impact of the explanatory variable on the outcome is called a

If there were something genetic which made people simultaneously more susceptible to both smoking and lung cancer, that would be an instance of

If the least-squares regression line for predicting y from x is y = 500 - 20x, what is the predicted value of y when x = 10?

Students who study statistics in college tend to score higher on the Graduate Record Examinations (GRE) math section than students who do not study statistics. Which is true?

A high correlation between two variables does not always mean that changes in one cause changes in the other. The best way to get good evidence that cause-and-effect is present is to

Suppose that the least-squares regression line for predicting y from x is y = 100 + 1.3x. Which of the following is a possible value for the correlation between x and y?

The correlation between two variables x and y is -0.6. If we used a regression line to predict y using x, what percent of the variation in y would be explained?

In a fisheries researcher's experiment, the correlation between the number of eggs in the nest and the number of viable (surviving) eggs for a sample of nests is r = 0.67. The correlation r = 0.67 shows that the fact that the nests have different number of eggs explains

A study found correlation r = 0.43 between high school math grades (on a 0 to 100 scale) and income 10 years after school. This says that the fact that hot dogs have different amounts of salt explains about

The evidence that smoking causes lung cancer is very strong. But it is not the strongest possible statistical evidence because

A least-squares regression line is not just any line drawn through the points of a scatterplot. What is special about a least-squares regression line?

Where Do Data Come From

Samples, Good and Bad

What Do Samples Tell Us

Sample Surveys in the Real World

Experiments, Good and Bad

Experiments in the Real World

Data Ethics

Measuring

Do the Numbers Make Sense

Graphs, Good and Bad

Displaying Distributions With Graphs

Normal Distributions

Describing Relationships: Scatterplots and Correlation

The Consumer Price Index and Government Statistics

Thinking About Chance

Probability Models

Simulation

The House Edge: Expected Values

What Is a Confidence Interval

What Is a Test of Significance

Use and Abuse of Statistical Inference

Two-Way Tables and the Chi-Square Test

Filters

Exam 15: Describing Relationships: Regression, Prediction, and Causation

One uses _________ to predict the value of a response variable for a given value of an explanatory variable.

The correlation between two variables x and y is 0.5. If we used a regression line to predict y using x, what percent of the variation in y would be explained?

If the least-squares regression line for predicting y from x is y = 40 + 10x, what is the predicted value of y when x = 5?

A variable such that its impact on the results cannot be separated from the impact of the explanatory variable on the outcome is called a

If there were something genetic which made people simultaneously more susceptible to both smoking and lung cancer, that would be an instance of

If the least-squares regression line for predicting y from x is y = 500 - 20x, what is the predicted value of y when x = 10?

Students who study statistics in college tend to score higher on the Graduate Record Examinations (GRE) math section than students who do not study statistics. Which is true?

A high correlation between two variables does not always mean that changes in one cause changes in the other. The best way to get good evidence that cause-and-effect is present is to

Suppose that the least-squares regression line for predicting y from x is y = 100 + 1.3x. Which of the following is a possible value for the correlation between x and y?

The correlation between two variables x and y is -0.6. If we used a regression line to predict y using x, what percent of the variation in y would be explained?

In a fisheries researcher's experiment, the correlation between the number of eggs in the nest and the number of viable (surviving) eggs for a sample of nests is r = 0.67. The correlation r = 0.67 shows that the fact that the nests have different number of eggs explains

A study found correlation r = 0.43 between high school math grades (on a 0 to 100 scale) and income 10 years after school. This says that the fact that hot dogs have different amounts of salt explains about

The evidence that smoking causes lung cancer is very strong. But it is not the strongest possible statistical evidence because

A least-squares regression line is not just any line drawn through the points of a scatterplot. What is special about a least-squares regression line?

Where Do Data Come From

Samples, Good and Bad

What Do Samples Tell Us

Sample Surveys in the Real World

Experiments, Good and Bad

Experiments in the Real World

Data Ethics

Measuring

Do the Numbers Make Sense

Graphs, Good and Bad

Displaying Distributions With Graphs

Normal Distributions

Describing Relationships: Scatterplots and Correlation

The Consumer Price Index and Government Statistics

Thinking About Chance

Probability Models

Simulation

The House Edge: Expected Values

What Is a Confidence Interval

What Is a Test of Significance

Use and Abuse of Statistical Inference

Two-Way Tables and the Chi-Square Test

Filters