Control groups are used in experiments in order to

Control groups are used in experiments in order to 

(a) control the effects of outside variables on the outcome

(b) control the subjects of a study to ensure that all participate equally

(c) guarantee that someone other than the investigators, who have a vested interest in the outcome, controls how the experiment is conducted

(d) achieve a proper and uniform level of randomization

(e) reduce the variability in results




Answer: A

A researcher observes that, on average, the number of divorces in cities with Major League Baseball teams is larger than in cities without Major League Baseball teams. The most plausible explanation for this observed association is that the

A researcher observes that, on average, the number of divorces in cities with Major League Baseball teams is larger than in cities without Major League Baseball teams. The most plausible explanation for this observed association is that the 

(a) presence of a Major League Baseball team causes the number of divorces to rise (perhaps husbands are spending too much time at the ballpark)
(b) high number of divorces is responsible for the presence of Major League Baseball teams (more single men means potentially more fans at the ballpark, making it attractive for an owner to relocate to such cities)
(c) association is due to the presence of a lurking variable (Major League teams tend to be in large cities with more people, hence a greater number of divorces)
(d) association makes no sense, since many married couples go to the ballpark together


Answer: C

A nutritionist wants to study the effect of storage time (6, 12, and 18 months) on the amount of vitamin C present in freeze dried fruit when stored for these lengths of time. Vitamin C is measured in milligrams per 100 milligrams of fruit. Six fruit packs were randomly assigned to each of the three storage times. The treatment, experimental unit, and response are respectively

A nutritionist wants to study the effect of storage time (6, 12, and 18 months) on the amount of vitamin C present in freeze dried fruit when stored for these lengths of time. Vitamin C is measured in milligrams per 100 milligrams of fruit. Six fruit packs were randomly assigned to each of the three storage times. The treatment, experimental unit, and response are respectively 

(a) A specific storage time, amount of vitamin C, a fruit pack
(b) A fruit pack, amount of vitamin C, a specific storage time
(c) Random assignment, a fruit pack, amount of vitamin C
(d) A specific storage time, a fruit pack, amount of vitamin C
(e) A specific storage time, the nutritionist, amount of vitamin C



Answer: D

A survey was done in the town of Mechanicsville to estimate the proportion of cars that are red and made by companies based in Japan. A random sample of 25 cars from a student parking lot at Lee-Davis High School was taken. Which of the following statements is not correct?

A survey was done in the town of Mechanicsville to estimate the proportion of cars that are red and made by companies based in Japan. A random sample of 25 cars from a student parking lot at Lee-Davis High School was taken. Which of the following statements is not correct? 

(a) This sample may not be representative of the cars in Mechanicsville because mainly students park at Lee-Davis High School
(b) If the particular parking space is Vacant, we can simply select another parking space at random because it is unlikely that a space being Vacant is related to the color or manufacturer of the car
(c) It would an error to simply select the first 25 parking spaces in the lot closest to the auditorium because there are a number of parking spaces there reserved for Drivers Ed vehicles, whose primary color is white
(d) A different team doing the sampling independently would obtain different s for their sample proportions
(e) The results will be the same regardless of the time of day that the sample is taken


Answer: E

To test the effect of music on productivity, a group of assembly line workers are given portable mp3 players to play whatever music they choose while working for one month. For another month, they work without music. The order of the two treatments for each worker is determined randomly. This is

To test the effect of music on productivity, a group of assembly line workers are given portable mp3 players to play whatever music they choose while working for one month. For another month, they work without music. The order of the two treatments for each worker is determined randomly. This is 

(a) an observational study
(b) a matched pairs experiment
(c) a completely randomized experiment
(d) a block design, but not a matched pairs experiment
(e) impossible to classify unless more details of the study are provided.



Answer: B

A researcher for a consumer products company is field testing a new formula for laundry detergent. He has contracted with 60 families, each with two children, who have agreed to test the product. He randomly assigns 30 families to the group that will use the new formula and 30 to the group that will use the company's current detergent formula. The most important reason for this random assignment is that

A researcher for a consumer products company is field testing a new formula for laundry detergent. He has contracted with 60 families, each with two children, who have agreed to test the product. He randomly assigns 30 families to the group that will use the new formula and 30 to the group that will use the company's current detergent formula. The most important reason for this random assignment is that 

(a) randomization makes the analysis easier since the data can be collected and entered into the computer in any order
(b) randomization eliminates the impact of any confounding variables
(c) randomization is a good way to create two groups of 30 families that are as similar as possible, so that comparisons can be made between the two groups
(d) randomization ensures that the study is double-blind
(e) randomization reduces the impact of outliers


Answer: C

A maple sugar manufacturer wants to estimate the average trunk diameter of Sugar Maples trees in a large forest. There are too many trees to list them all and take a SRS, so he divides the forest into several hundred 10 meter by 10 meter plots, selects 25 plots at random, and measures the diameter of every Sugar Maple in each one. This is an example of a

A maple sugar manufacturer wants to estimate the average trunk diameter of Sugar Maples trees in a large forest. There are too many trees to list them all and take a SRS, so he divides the forest into several hundred 10 meter by 10 meter plots, selects 25 plots at random, and measures the diameter of every Sugar Maple in each one. This is an example of a 

(a) multistage sample
(b) stratified sample
(c) simple random sample
(d) cluster sample
(e) convenience sample


Answer: D

A new headache remedy was given to a group of 25 subjects who had headaches for hours after taking the new remedy, 20 of the subjects reported that their headaches had disappeared. From this information you conclude

A new headache remedy was given to a group of 25 subjects who had headaches for hours after taking the new remedy, 20 of the subjects reported that their headaches had disappeared. From this information you conclude 

(a) that the remedy is effective for the treatment of headaches
(b) nothingbecause the sample size is too small
(c) nothing, because there is no control group for comparison
(d) that the new treatment is better than aspirin
(e) that the remedy is not effective for the treatment of headaches



Answer: C

Which statements below about the least square regression are correct?

Which statements below about the least square regression are correct? 

I. Switching the explanatory and response variables will not change the least square regression line

II. The slope of the line is very sensitive to outliers with large residuals

III. A value of r^2 close to 1 does not guarantee that the relationship between the variables is linear

(a) Only I
(b) Only II
(c) Only III
(d) Both II and III
(e) I, II, and III

Answer: C

What does the residual plot tell you about the linear model?

What does the residual plot tell you about the linear model? 

 
(a) A residual plot is not an appropriate means for evaluating a linear model
(b) The curved patter ninth residual plot suggest that there is no association between the weight and height of basketball players
(c)The curved pattern in the residual plot suggests that the linear model is not appropriate
(d)There are not enough data points to draw any conclusions from the residual plot
(e)The linear model is appropriate, because there are approximately the same number of points above and below the horizontal line in the residual plot

Answer: C

All but one of the following statements contains an error. Which statement could be correct?

All but one of the following statements contains an error. Which statement could be correct? 

(a) There is a correlation of 0.54 between the position of a football player plays and his weight

(b) We found a correlation of r = -0.63 between gender and political party preference

(c) The correlation between the distance travelled by a hiker and the time spent hiking is r = 0.9 meters per second

(d) We found a high correlation between the height and age of children r = 1.12

(e) The correlation between mid-August soil moisture and the per-acre yield of tomatoes is r=0.53




Answer: E

The correlation between the heights of fathers and the heights of their (fully grown) sons is r = 0.52. This value was based on both variables being measured in inches. If fathers' heights were measured in feet (one foot equals 12 inches), and sons' heights were measured in furlongs (one furlong equals 7920 inches), the correlation between heights of fathers and heights of sons would be

The correlation between the heights of fathers and the heights of their (fully grown) sons is r = 0.52. This value was based on both variables being measured in inches. If fathers' heights were measured in feet (one foot equals 12 inches), and sons' heights were measured in furlongs (one furlong equals 7920 inches), the correlation between heights of fathers and heights of sons would be 

a. much smaller than 0.52
b. slightly smaller than0.52
c. unchanged equal to 0.52
d. slightly larger than 0.52
e. much larger than 0.52

Answer: C

Other things being equal, larger automobile engines consume more fuel. You are planning an experiment to study the effect of engine size (in liters) on the gas mileage (in miles per gallon) of sport utility vehicles In this study,

Other things being equal, larger automobile engines consume more fuel. You are planning an experiment to study the effect of engine size (in liters) on the gas mileage (in miles per gallon) of sport utility vehicles In this study, 

(a) gas mileage is a response variable, and you expect to find a negative association
(b) gas mileage is a response variable, and you expect to find a positive association
(c) gas mileage is an explanatory variable, and you expect to find a strong negative association
(d) gas mileage is an explanatory variable, and you expect to find a strong positive association
(e) gas mileage is an explanatory variable, and you expect to find very little association


Answer: A

A fire department in a rural county reports that its response time to fires is approximately Normally distributed with a mean of 22 minutes and a standard deviation if 11.9 minutes. Approximately what proportion of their response time is over 20 minutes?

A fire department in a rural county reports that its response time to fires is approximately Normally distributed with a mean of 22 minutes and a standard deviation if 11.9 minutes. Approximately what proportion of their response time is over 20 minutes? 

A. 0.03
B. 0.21
C. 0.25
D. 0.75
E. 0.79




Answer: C

Which of the following properties is true for all Normal density curves?

Which of the following properties is true for all Normal density curves? 

I. They are symmetric
II. The curve reaches its peak at the mean
III. 95% percent of the area under the curve is within one/standard deviation of the mean



(a) I only
(b) II only
(c) I and II only
(d) I and III only
(e) All three statements are correct



Answer: C

The distribution of the time it takes for different people to solve a certain crossword puzzle is strongly skewed to the right, with a mean of 30 minutes and a standard deviation of 15 N minutes. The distribution of z-scores for those times is r

The distribution of the time it takes for different people to solve a certain crossword puzzle is strongly skewed to the right, with a mean of 30 minutes and a standard deviation of 15 N minutes. The distribution of z-scores for those times is r 

(a) Normally distributed, with mean 30 and standard deviation 15

(b) Skewed to the right, with mean 30 and standard deviation 15

(c) Normally distributed, with mean 0 and standard deviation 1

(d) Skewed to the right, with mean 0 and standard deviation 1

(e) Skewed to the right, but the mean and standard deviation cannot be determined without more information




Answer: D

The area under the standard Normal Curve corresponding to -0.3 < Z < 1.6 is

The area under the standard Normal Curve corresponding to -0.3<Z<1.6 is 

A. 0.3273
B. 0.4713
C. 0.5631
D. 0.9542
E. None of the above



Answer: C

A medical researcher collects health data on many women in each of several countries. One of the variables measured for each woman in the study is her weight in pounds. The following list gives the five-number summary for the weights of adult women in one of the countries.

A medical researcher collects health data on many women in each of several countries. One of the variables measured for each woman in the study is her weight in pounds. The following list gives the five-number summary for the weights of adult women in one of the countries. 

C country A 92, 110, 120, 160, 240

About percent of Country A women weigh between 110 and 240 pounds?



A. 50%
B. 65%
C. 75%
D. 85%
E. 95%



Answer: C

The mean birth weight of infants born at a certain hospital in the month of April was 128 oz. with a standard deviation of 10.2 oz. Which of the following is a correct interpretation of standard deviation?

The mean birth weight of infants born at a certain hospital in the month of April was 128 oz. with a standard deviation of 10.2 oz. Which of the following is a correct interpretation of standard deviation? 

(3) All the infants born in April weighed between 117.8 oz. and 138.2 oz.
(b) About half the infants born in April weighed between 117.8 oz. and 138.2 oz.
(c) The difference between the mean weight and the median weight of infants born in April was 10.2 oz.
(d) The distance between the weight of each infant bon in April and the mean weight was, on average, about 10.2 oz.
(e) The mean weight of infants born in subsequent months is likely to be within 10.2 oz. of the mean weight in April.


Answer: D

A small company that prints custom t-shirts has 6 employees, one of whom is the owner and manager. Suppose the owner makes $120,000 per year and the other employees make between $40,000 and $50,000 per year. One day, the owner decides to give himself a $30,000 raise. Which of the following describes how the company's mean and median salaries would change?

A small company that prints custom t-shirts has 6 employees, one of whom is the owner and manager. Suppose the owner makes $120,000 per year and the other employees make between $40,000 and $50,000 per year. One day, the owner decides to give himself a $30,000 raise. Which of the following describes how the company's mean and median salaries would change? 

(a) The mean and median would both increase by $5,000.
(b) The mean would increase by $5,000 and the median would not change.
(e) The mean would increase by $6,000 and the median would not change.
(d) The median would increase by $6,000 and the mean would not change.
(e) The mean would increase by $6,000, but we cannot determine the change in the median without more information.




Answer: B

If a distribution is skewed to the right, which of the following is true?

If a distribution is skewed to the right, which of the following is true? 

(a) The mean must be less than the median.
(b) The mean and median must be equal.
(c) The mean must be greater than the median.
(d) The mean is either equal to or less than the median.
(e) It's impossible to tell which of the above statement sistrue without seeing the data



Answer: C

If removing an observation from a data set would have a marked change on the position of the LSRL, fit to the data, what is the point called:

If removing an observation from a data set would have a marked change on the position of the LSRL, fit to the data, what is the point called:

a. Robust
b. A residual
c. A response
d. Influential
e. None of the above



Answer: d. Influential

Two variables, an explanatory variable x and a response variable y, are measured on each of several individuals. The correlation between these variables is found to be 0.88. To help us interpret this correlation, we should do which of the following?

Two variables, an explanatory variable x and a response variable y, are measured on each of several individuals. The correlation between these variables is found to be 0.88. To help us interpret this correlation, we should do which of the following?

a. Compute the least-squares regression line of y on x and consider whether the slope is positive or negative.
b. Interchange the roles of x and y (ie, treat x as the response variable and y as the explanatory variable) and recompute the correlation.
c. Plot the data.
d. Determine whether x or y has larger values before computing the residuals.
e. All of the above.


Answer: c. Plot the data.

Suppose we fit a least-squares regression line to a set of data. What is true if a plot of the residuals shows a curved pattern?

Suppose we fit a least-squares regression line to a set of data. What is true if a plot of the residuals shows a curved pattern?

a. A straight line is not a good model for the data.
b. The correlation must be 0.
c. The correlation must be positive.
d. Outliers must be present.
e. The regression line might or might not be a good model for the data, depending on the extent of the curve.



Answer: a. A straight line is not a good model for the data.

Which of the following relationships is most likely to result in a strong negative correlation?

Which of the following relationships is most likely to result in a strong negative correlation?

a. The number of people showering in a college dorm and the water pressure in each shower.
b. The outdoor temperature and the number of fans running in non-air conditioned dorm rooms.
c. The comfort rating of a mattress and the number of hours of uninterrupted sleep obtained.
d. The price of a home and its square footage.
e. The fuel efficiency of a car (miles per gallon) and its speed.


Answer: a. The number of people showering in a college dorm and the water pressure in each shower.

If data set A of (x, y) data has correlation coefficient r=0.65, and a second data set B has correlation r= -0.65, then

If data set A of (x, y) data has correlation coefficient r=0.65, and a second data set B has correlation r= -0.65, then

a. the points in A exhibit a stronger linear association than B.
b. the points in B exhibit a stronger linear association than A.
c. neither A nor B has a stronger linear association.
d. you can't tell which data set has a stronger linear association without seeing the data or seeing the scatterplots.
e. a mistake has been made-r cannot be negative.


Answer: c. neither A nor B has a stronger linear association.

In the setting of the previous problem, about what percent of the variation in the number of service calls is explained by the linear relation between number of service calls and number of machines?

In the setting of the previous problem, about what percent of the variation in the number of service calls is explained by the linear relation between number of service calls and number of machines?

a. 86%
b. 93%
c. 74%
d. None of these
e. Can't tell from the information given



Answer: c. 74%

A copy machine dealer has data on the number x of copy machines at each of 89 customer locations and the number y of service calls in a month at each location. Summary calculations given are X bar=8.4, Sx=2.1, Y bar=14.2, Sy=3.8, and r=0.86. What is the slope of the least-squares regression line of number of service calls on number of copiers?

A copy machine dealer has data on the number x of copy machines at each of 89 customer locations and the number y of service calls in a month at each location. Summary calculations given are X bar=8.4, Sx=2.1, Y bar=14.2, Sy=3.8, and r=0.86. What is the slope of the least-squares regression line of number of service calls on number of copiers?

a. 0.86
b. 1.56
c. 0.48
d. None of these
e. Can't tell from the information given



Answer: b. 1.56

A community college announces that the correlation between college entrance exam grades and scholastic achievement was found to be -1.08. On the basis of this you would tell the college that

A community college announces that the correlation between college entrance exam grades and scholastic achievement was found to be -1.08. On the basis of this you would tell the college that

a. the entrance exam is a good predictor of success.
b. the exam is a poor predictor of success.
c. students who do best on this exam will be poor students.
d. students at this school are underachieving.
e. the college should hire a new statistician.



Answer: e. the college should hire a new statistician.

Which of the following statements is/are true?

Which of the following statements is/are true?

I. Correlation and regression require explanatory and response variables.
II. Scatterplots require that both variables be quantitative.
III. Every least-squares regression line passes through (X bar, Y bar).



a. I and II only
b. I and III only
c. II and III only
d. I, II, and III
e. None of the above



Answer: c. II and III only

A regression of the amount of calories in a serving of breakfast cereal vs the amount of fat gave the following results: Calories = 97.1053+9.6525 (Fat). Which of the following is FALSE?

A regression of the amount of calories in a serving of breakfast cereal vs the amount of fat gave the following results: Calories = 97.1053+9.6525 (Fat). Which of the following is FALSE?

a. It is estimated that for every additional gram of fat in the cereal, the number of calories increases by about 10.
b. It is estimated that in cereals with no fat, the total amount of calories is about 97.
c. If a cereal has 2 g of fat, then it is estimated that the total number of calories is about 116.
d. The correlation between amount of fat and calories is positive.
e. One cereal has 140 calories and 5 g of fat. Its residual is about 5 cal.



Answer: e. One cereal has about 140 calories and 5 g of fat. Its residual is about 5 cal.

In the scatterplot in the previous question, if each x-value were decreased by one unit and the y-values remained the same, then the correlation r would

In the scatterplot in the previous question, if each x-value were decreased by one unit and the y-values remained the same, then the correlation r would

a. decrease by one unit
b. decrease slightly
c. increase slightly
d. stay the same
e. can't tell without knowing the data values.



Answer: d. stay the same.

There is an approximate linear relationship between the height of females and their age (from 5 to 18 years) described by height = 50.3+6.01 (age) where height is measured in centimeters and age in years. Which of the following is not correct?

There is an approximate linear relationship between the height of females and their age (from 5 to 18 years) described by height = 50.3+6.01 (age) where height is measured in centimeters and age in years. Which of the following is not correct?

a. The estimated slope is 6.01, which implies that children increase by about 6 cm for each year they grow older.
b. The estimated height of a child who is 10 years old is about 110 cm.
c. The estimated intercept is 50.3 cm, which implies that children reach this height when they are 50.3/6.01=8.4 years old.
d. The average height of children when they are 5 years old is about 50% of the average height when they are 18 years old.
e. My niece is about 8 years old and is about 115 cm tall. She is taller than average.



Answer: c. The estimated intercept is 50.3 cm, which implies that children reach this height when they are 50.3/6.01=8.4 years old.

You have data for many families on the parents' income and the years of education their eldest child completes. When you make your scatterplot,

You have data for many families on the parents' income and the years of education their eldest child completes. When you make your scatterplot,

a. the explanatory variable is parents' income, and you expect to see a negative association.
b. the explanatory variable is parents' income, and you expect to see a positive association.
c. the explanatory variable is parents' income, and you expect to see very little association.
d. the explanatory variable is years of education, and you expect to see a negative association.
e. the explanatory variable is years of education, and you expect to see a positive association.


Answer: b. the explanatory variable is the parents' income, and you expect to see a positive association.

All but one of the following statements contains a blunder. Which statement could be correct?

All but one of the following statements contains a blunder. Which statement could be correct?

a. There is a correlation of 0.54 between the position a football player plays and his weight.
b. We found a correlation of r= -0.63 between gender and political party preference.
c. The correlation between the gas mileage of a car and its weight is r=0.71 mpg.
d. We found a high correlation (r=1.09) between height and age of children.
e. The correlation between planting rate and yield of tomatoes was found to be r=0.23.



Answer: e. The correlation between planting rate and yield of tomatoes was found to be r=0.23.

Refer to the previous problem. On the final exam Carla scored 98. What is the value of her residual?

Refer to the previous problem. On the final exam Carla scored 98. What is the value of her residual?

a. -2.5
b. 0
c. 2.5
d. 98
e. None of the above



Answer: c. 2.5

In a statistics course, a linear regression equation was computed to predict the final-exam score from the score on the first test. The equation was y=10+0.9x where y is the final-exam score and x is the score on the first test. Carla scored 95 on the first test. What is the predicted value of her score on the final exam?

In a statistics course, a linear regression equation was computed to predict the final-exam score from the score on the first test. The equation was y=10+0.9x where y is the final-exam score and x is the score on the first test. Carla scored 95 on the first test. What is the predicted value of her score on the final exam?

a. 85.5
b. 90
c. 95
d. 95.5
e. None of the above



Answer: d. 95.5