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AP STATS FINAL PREP 2017-2018
CHAPTER 6In a particular game, a fair die is tossed. If the number of spots showing is either 4 or 5 you win $1, if the number of spots showing is 6 you win $4, and if the number of spots showing is 1, 2, or 3 you win nothing. Let X be the amount that you win.
Which of the following is the expected value of X?
a. $0.00
b. $1.00
c. $2.50
d. $4.00
e. $6.00
CHAPTER 6In a particular game, a fair die is tossed. If the number of spots showing is either 4 or 5 you win $1, if the number of spots showing is 6 you win $4, and if the number of spots showing is 1, 2, or 3 you win nothing. Let X be the amount that you win.
Which of the following is the expected value of X?
a. $0.00
b. $1.00
c. $2.50
d. $4.00
e. $6.00
CHAPTER 6In a particular game, a fair die is tossed. If the number of spots showing is either 4 or 5 you win $1, if the number of spots showing is 6 you win $4, and if the number of spots showing is 1, 2, or 3 you win nothing. Let X be the amount that you win.
Which of the following is the standard deviation of X?
a. $1.00
b. $1.35
c. $1.41
d. $1.78
e. $2.00
CHAPTER 6In a particular game, a fair die is tossed. If the number of spots showing is either 4 or 5 you win $1, if the number of spots showing is 6 you win $4, and if the number of spots showing is 1, 2, or 3 you win nothing. Let X be the amount that you win.
Which of the following is the standard deviation of X?
a. $1.00
b. $1.35
c. $1.41
d. $1.78
e. $2.00
CHAPTER 6“Insert tab A into slot B” is something you might read in the assembly instructions for pre-fabricated bookshelves. Suppose that tab A varies in size according to a Normal distribution with a mean of 30 mm. and a standard deviation of 0.5 mm., and the size of slot B is also Normally distributed, with a mean of 32 mm. and a standard deviation of 0.8 mm. The two parts are randomly and independently selected for packaging. What is the probability that tab A won’t fit into slot B?
a. 0.0007
b. 0.0170
c. 0.0618
d. 0.9382
e. 0.9830
CHAPTER 6“Insert tab A into slot B” is something you might read in the assembly instructions for pre-fabricated bookshelves. Suppose that tab A varies in size according to a Normal distribution with a mean of 30 mm. and a standard deviation of 0.5 mm., and the size of slot B is also Normally distributed, with a mean of 32 mm. and a standard deviation of 0.8 mm. The two parts are randomly and independently selected for packaging. What is the probability that tab A won’t fit into slot B?
a. 0.0007
b. 0.0170
c. 0.0618
d. 0.9382
e. 0.9830
CHAPTER 6Your friend Albert has invented a game involving two ten-sided dice. One of the dice has threes, fours, and fives on its faces, the other has sixes, eights, and tens. He won’t tell you how many of each number there are on the faces, but he does tell you that if X = the result of a single roll of the first die and Y = the result of a single roll of the second die, then Let Z = the sum of the two dice when each is rolled once.
What is the expected value of Z?
a. 1.7
b. 4.4
c. 8.8
d. 8.9
e. 11.6
CHAPTER 6
Your friend Albert has invented a game involving two ten-sided dice. One of the dice has threes, fours, and fives on its faces, the other has sixes, eights, and tens. He won’t tell you how many of each number there are on the faces, but he does tell you that if X = the result of a single roll of the first die and Y = the result of a single roll of the second die, then Let Z = the sum of the two dice when each is rolled once.
What is the expected value of Z?
a. 1.7
b. 4.4
c. 8.8
d. 8.9
e. 11.6
CHAPTER 6Your friend Albert has invented a game involving two ten-sided dice. One of the dice has threes, fours, and fives on its faces, the other has sixes, eights, and tens. He won’t tell you how many of each number there are on the faces, but he does tell you that if X = the result of a single roll of the first die and Y = the result of a single roll of the second die, then Let Z = the sum of the two dice when each is rolled once.
What is the standard deviation of Z?
a. 1.20
b. 1.30
c. 1.45
d. 1.70
e. 2.89
CHAPTER 6Your friend Albert has invented a game involving two ten-sided dice. One of the dice has threes, fours, and fives on its faces, the other has sixes, eights, and tens. He won’t tell you how many of each number there are on the faces, but he does tell you that if X = the result of a single roll of the first die and Y = the result of a single roll of the second die, then Let Z = the sum of the two dice when each is rolled once.
What is the standard deviation of Z?
a. 1.20
b. 1.30
c. 1.45
d. 1.70
e. 2.89
CHAPTER 6Your friend Albert has invented a game involving two ten-sided dice. One of the dice has threes, fours, and fives on its faces, the other has sixes, eights, and tens. He won’t tell you how many of each number there are on the faces, but he does tell you that if X = the result of a single roll of the first die and Y = the result of a single roll of the second die, then Let Z = the sum of the two dice when each is rolled once.
Here’s Albert’s game: You give him $10 each time you roll, and he pays you (in dollars) the amount that comes up on the dice. If P = the amount of money you gain each time you roll, the mean and standard deviation of P are:
a. 𝜇 = −1.6; 𝜎 = 1.45
b. 𝜇 = 1.6; 𝜎 = 1.45
c. 𝜇 = 1.6; 𝜎 = 1.2
d. 𝜇 = −1.6; 𝜎 = −13.8
e. 𝜇 = 1.6; 𝜎 = 13.8
CHAPTER 6Your friend Albert has invented a game involving two ten-sided dice. One of the dice has threes, fours, and fives on its faces, the other has sixes, eights, and tens. He won’t tell you how many of each number there are on the faces, but he does tell you that if X = the result of a single roll of the first die and Y = the result of a single roll of the second die, then Let Z = the sum of the two dice when each is rolled once.
Here’s Albert’s game: You give him $10 each time you roll, and he pays you (in dollars) the amount that comes up on the dice. If P = the amount of money you gain each time you roll, the mean and standard deviation of P are:
a. 𝜇 = −1.6; 𝜎 = 1.45
b. 𝜇 = 1.6; 𝜎 = 1.45
c. 𝜇 = 1.6; 𝜎 = 1.2
d. 𝜇 = −1.6; 𝜎 = −13.8
e. 𝜇 = 1.6; 𝜎 = 13.8
CHAPTER 6An ecologist studying starfish populations collects the following data on randomly-selected 1-meter by 1-meter plots on a rocky coastline.
--The number of starfish in the plot.
--The total weight of starfish in the plot.
--The percentage of area in the plot that is covered by barnacles (a popular food for starfish).
--Whether or not the plot is underwater midway between high and low tide.
How many of these measurements can be treated as continuous random variables and how many as discrete random variables?
a. Three continuous, one discrete.
b. Two continuous, two discrete.
c. One continuous, three discrete.
d. Two continuous, one discrete, and a fourth that cannot be treated as a random variable
e. One continuous, two discrete, and a fourth that cannot be treated as a random variable.
CHAPTER 6An ecologist studying starfish populations collects the following data on randomly-selected 1-meter by 1-meter plots on a rocky coastline.
--The number of starfish in the plot.
--The total weight of starfish in the plot.
--The percentage of area in the plot that is covered by barnacles (a popular food for starfish).
--Whether or not the plot is underwater midway between high and low tide.
How many of these measurements can be treated as continuous random variables and how many as discrete random variables?
a. Three continuous, one discrete.
b. Two continuous, two discrete.
c. One continuous, three discrete.
d. Two continuous, one discrete, and a fourth that cannot be treated as a random variable.
e. One continuous, two discrete, and a fourth that cannot be treated as a random variable.
CHAPTER 5Each day, Mr. Bayona chooses a one-digit number from a random number table to decide if he will walk to work or drive that day. The numbers 0 through 3 indicate he will drive, 4 through 9 mean he will walk. If he drives, he has a probability of 0.1 of being late. If he walks, his probability of being late rises to 0.25. Let W = Walk, D = Drive, L = Late, and NL = Not Late. Which of the following tree diagrams summarizes these probabilities?
A B C D E
CHAPTER 5Each day, Mr. Bayona chooses a one-digit number from a random number table to decide if he will walk to work or drive that day. The numbers 0 through 3 indicate he will drive, 4 through 9 mean he will walk. If he drives, he has a probability of 0.1 of being late. If he walks, his probability of being late rises to 0.25. Let W = Walk, D = Drive, L = Late, and NL = Not Late. Which of the following tree diagrams summarizes these probabilities?
A B C D E
CHAPTER 5You ask a sample of 370 people, "Should clinical trials on issues such as heart attacks that affect both sexes use subjects of just one sex?" The responses are in the table below. Suppose you choose one of these people at random
What is the probability that the person said "Yes," given that she is a woman?
a. 0.20
b. 0.22
c. 0.25
d. 0.50
e. 0.575
Yes No
Male 34 105
Female 46 185
CHAPTER 5You ask a sample of 370 people, "Should clinical trials on issues such as heart attacks that affect both sexes use subjects of just one sex?" The responses are in the table below. Suppose you choose one of these people at random
What is the probability that the person said "Yes," given that she is a woman?
a. 0.20
b. 0.22
c. 0.25
d. 0.50
e. 0.575
Yes No
Male 34 105
Female 46 185
CHAPTER 5You ask a sample of 370 people, "Should clinical trials on issues such as heart attacks that affect both sexes use subjects of just one sex?" The responses are in the table below. Suppose you choose one of these people at random
What is the probability that the person is a woman, given that she said “Yes?”
a. 0.20
b. 0.22
c. 0.25
d. 0.50
e. 0.575
Yes No
Male 34 105
Female 46 185
CHAPTER 5You ask a sample of 370 people, "Should clinical trials on issues such as heart attacks that affect both sexes use subjects of just one sex?" The responses are in the table below. Suppose you choose one of these people at random
What is the probability that the person is a woman, given that she said “Yes?”
a. 0.20
b. 0.22
c. 0.25
d. 0.50
e. 0.575
Yes No
Male 34 105
Female 46 185
CHAPTER 5In a particular game, a fair die is tossed. If the number of spots showing is either four or five, you score 1 point. If the number of spots showing is six, you score 4 points. And if the number of spots showing is one, two, or three, you score 0. You are going to play the game twice.
The probability that you score 4 points both times is
a. 1/36.
b. 1/12
c. 1/6.
d. 1/4.
e. 1/3.
CHAPTER 5In a particular game, a fair die is tossed. If the number of spots showing is either four or five, you score 1 point. If the number of spots showing is six, you score 4 points. And if the number of spots showing is one, two, or three, you score 0. You are going to play the game twice.
The probability that you score 4 points both times is
a. 1/36.
b. 1/12
c. 1/6.
d. 1/4.
e. 1/3.
CHAPTER 5In a particular game, a fair die is tossed. If the number of spots showing is either four or five, you score 1 point. If the number of spots showing is six, you score 4 points. And if the number of spots showing is one, two, or three, you score 0. You are going to play the game twice.
The probability that you score at least 1 point both times is
a. 1/36.
b. 4/36.
c. 1/4.
d. 1/2.
e. 3/4.
CHAPTER 5In a particular game, a fair die is tossed. If the number of spots showing is either four or five, you score 1 point. If the number of spots showing is six, you score 4 points. And if the number of spots showing is one, two, or three, you score 0. You are going to play the game twice.
The probability that you score at least 1 point both times is
a. 1/36.
b. 4/36.
c. 1/4.
d. 1/2.
e. 3/4.
CHAPTER 5A box has 10 tickets in it, two of which are winning tickets. You draw a ticket at random. If it's a winning ticket, you win. If not, you get another chance, as follows: your losing ticket is replaced in the box by a winning ticket (so now there are 10 tickets, as before, but 3 of them are winning tickets). You get to draw again, at random. Which of the following are legitimate methods for using simulation to estimate the probability of winning?
I. Choose, at random, a two-digit number. If the first digit is 0 or 1, you win on the first draw; If the first digit is 2 through 9, but the second digit is 0, 1, or 2, you win on the second draw. Any other two-digit number means you lose.
II. Choose, at random, a one-digit number. If it is 0 or 1, you win. If it is 2 through 9, pick a second number. If the second number is 8, 9, or 0, you win. Otherwise, you lose.
III. Choose, at random, a one-digit number. If it is 0 or 1, you win on the first draw. If it is 2, 3, or 4, you win on the second draw; If it is 5 through 9, you lose.
a. I only
b. II only
c. III only
d. I and II
e. I, II, and III
CHAPTER 5A box has 10 tickets in it, two of which are winning tickets. You draw a ticket at random. If it's a winning ticket, you win. If not, you get another chance, as follows: your losing ticket is replaced in the box by a winning ticket (so now there are 10 tickets, as before, but 3 of them are winning tickets). You get to draw again, at random. Which of the following are legitimate methods for using simulation to estimate the probability of winning?
I. Choose, at random, a two-digit number. If the first digit is 0 or 1, you win on the first draw; If the first digit is 2 through 9, but the second digit is 0, 1, or 2, you win on the second draw. Any other two-digit number means you lose.
II. Choose, at random, a one-digit number. If it is 0 or 1, you win. If it is 2 through 9, pick a second number. If the second number is 8, 9, or 0, you win. Otherwise, you lose.
III. Choose, at random, a one-digit number. If it is 0 or 1, you win on the first draw. If it is 2, 3, or 4, you win on the second draw; If it is 5 through 9, you lose.
a. I only
b. II only
c. III only
d. I and II
e. I, II, and III
CHAPTER 5A ten-sided die has each of the digits from 0 to 9 on one of its faces. Which of the following best describes what it means to say that the probability of rolling a 3 is 0.1?
a. If you roll the die thousands of times, the proportion of times that you roll a 3 will be close to 0.1.
b. If you roll the die 10 times, one of the rolls will be a 3.
c. If you roll the die 10,000 times, 1000 of the rolls will be 3’s.
d. It would be impossible to roll the die 25 times and not get any 3’s.
e. If the first two rolls are 3’s, the probability of rolling a 3 on the next roll is slightly less than 0.1.
CHAPTER 5A ten-sided die has each of the digits from 0 to 9 on one of its faces. Which of the following best describes what it means to say that the probability of rolling a 3 is 0.1?
a. If you roll the die thousands of times, the proportion of times that you roll a 3 will be close to 0.1.
b. If you roll the die 10 times, one of the rolls will be a 3.
c. If you roll the die 10,000 times, 1000 of the rolls will be 3’s.
d. It would be impossible to roll the die 25 times and not get any 3’s.
e. If the first two rolls are 3’s, the probability of rolling a 3 on the next roll is slightly less than 0.1.
CHAPTER 4In order to assess the effects of exercise on reducing cholesterol, a researcher took a random sample of fifty people from a local gym who exercised regularly and another random sample of fifty people from the surrounding community who did not exercise regularly. They all reported to a clinic to have their cholesterol measured. The subjects were unaware of the purpose of the study, and the technician measuring the cholesterol was not aware of whether or not subjects exercised regularly.
Which of the following best describes the inferences the researcher can make based on his results?
a. He can make inferences about cause and effect, but not about the populations from which the samples were taken.
b. He can make inferences about the populations from which the samples were taken, but not about cause and effect.
c. He can make inferences about both cause and effect and the populations from which the samples were taken.
d. He cannot make inferences about either cause and effect or the populations from which the samples were taken.
e. There is not enough information to make judgments about the scope of inference.
CHAPTER 4In order to assess the effects of exercise on reducing cholesterol, a researcher took a random sample of fifty people from a local gym who exercised regularly and another random sample of fifty people from the surrounding community who did not exercise regularly. They all reported to a clinic to have their cholesterol measured. The subjects were unaware of the purpose of the study, and the technician measuring the cholesterol was not aware of whether or not subjects exercised regularly.
Which of the following best describes the inferences the researcher can make based on his results?
a. He can make inferences about cause and effect, but not about the populations from which the samples were taken.
b. He can make inferences about the populations from which the samples were taken, but not about cause and effect.
c. He can make inferences about both cause and effect and the populations from which the samples were taken.
d. He cannot make inferences about either cause and effect or the populations from which the samples were taken.
e. There is not enough information to make judgments about the scope of inference.
CHAPTER 4A farmer wishes to determine which of two brands of baby pig pellets, Kent or Moormans, produces better weight gains. Two of his sows each give birth to litters of 10 pigs on the same day, so he decides to give the baby pigs in litter A only Kent pellets, while the pigs in litter B will get only Moormans pellets. After four weeks, the average weight gain for pigs in litter A is greater than the average weight gain for pigs in litter B.
The farmer has conducted a(n)
a. stratified random sample.
b. matched pairs design.
c. observational study.
d. experiment, but not a completely randomized experiment.
e. completely randomized experiment.
CHAPTER 4A farmer wishes to determine which of two brands of baby pig pellets, Kent or Moormans, produces better weight gains. Two of his sows each give birth to litters of 10 pigs on the same day, so he decides to give the baby pigs in litter A only Kent pellets, while the pigs in litter B will get only Moormans pellets. After four weeks, the average weight gain for pigs in litter A is greater than the average weight gain for pigs in litter B.
The farmer has conducted a(n)
a. stratified random sample.
b. matched pairs design.
c. observational study.
d. experiment, but not a completely randomized experiment.
e. completely randomized experiment.
CHAPTER 4A farmer wishes to determine which of two brands of baby pig pellets, Kent or Moormans, produces better weight gains. Two of his sows each give birth to litters of 10 pigs on the same day, so he decides to give the baby pigs in litter A only Kent pellets, while the pigs in litter B will get only Moormans pellets. After four weeks, the average weight gain for pigs in litter A is greater than the average weight gain for pigs in litter B.
The brand of pellets is
a. a parameter.
b. the response variable.
c. the explanatory variable.
d. the placebo effect.
e. a dependent variable.
CHAPTER 4A farmer wishes to determine which of two brands of baby pig pellets, Kent or Moormans, produces better weight gains. Two of his sows each give birth to litters of 10 pigs on the same day, so he decides to give the baby pigs in litter A only Kent pellets, while the pigs in litter B will get only Moormans pellets. After four weeks, the average weight gain for pigs in litter A is greater than the average weight gain for pigs in litter B.
The brand of pellets is
a. a parameter.
b. the response variable.
c. the explanatory variable.
d. the placebo effect.
e. a dependent variable.
CHAPTER 4A farmer wishes to determine which of two brands of baby pig pellets, Kent or Moormans, produces better weight gains. Two of his sows each give birth to litters of 10 pigs on the same day, so he decides to give the baby pigs in litter A only Kent pellets, while the pigs in litter B will get only Moormans pellets. After four weeks, the average weight gain for pigs in litter A is greater than the average weight gain for pigs in litter B.
The feed they get is not the only factor affecting the rate at which pigs gain weight. Genetic differences also affect weight gain. It is likely that the pigs in litter A are genetically different from the pigs in litter B, since the two litters have different mothers. Since the farmer is only interested in determining which brand of pellets is better, the study suffers from
a. confounding.
b. common response.
c. convenience sampling.
d. invalid measurement.
e. experimenter bias.
CHAPTER 4A farmer wishes to determine which of two brands of baby pig pellets, Kent or Moormans, produces better weight gains. Two of his sows each give birth to litters of 10 pigs on the same day, so he decides to give the baby pigs in litter A only Kent pellets, while the pigs in litter B will get only Moormans pellets. After four weeks, the average weight gain for pigs in litter A is greater than the average weight gain for pigs in litter B.
The feed they get is not the only factor affecting the rate at which pigs gain weight. Genetic differences also affect weight gain. It is likely that the pigs in litter A are genetically different from the pigs in litter B, since the two litters have different mothers. Since the farmer is only interested in determining which brand of pellets is better, the study suffers from
a. confounding.
b. common response.
c. convenience sampling.
d. invalid measurement.
e. experimenter bias.
CHAPTER 4A farmer wishes to determine which of two brands of baby pig pellets, Kent or Moormans, produces better weight gains. Two of his sows each give birth to litters of 10 pigs on the same day, so he decides to give the baby pigs in litter A only Kent pellets, while the pigs in litter B will get only Moormans pellets. After four weeks, the average weight gain for pigs in litter A is greater than the average weight gain for pigs in litter B.
If the farmer had fed Kent pellets to an SRS of 5 pigs from litter A and an SRS of 5 pigs from litter B, with the remaining 10 pigs getting Moormans pellets, then he would have been using
a. a systematic random sample.
b. a convenience sample.
c. a matched-pairs design.
d. a block design.
e. a completely randomized design.
CHAPTER 4A farmer wishes to determine which of two brands of baby pig pellets, Kent or Moormans, produces better weight gains. Two of his sows each give birth to litters of 10 pigs on the same day, so he decides to give the baby pigs in litter A only Kent pellets, while the pigs in litter B will get only Moormans pellets. After four weeks, the average weight gain for pigs in litter A is greater than the average weight gain for pigs in litter B.
If the farmer had fed Kent pellets to an SRS of 5 pigs from litter A and an SRS of 5 pigs from litter B, with the remaining 10 pigs getting Moormans pellets, then he would have been using
a. a systematic random sample.
b. a convenience sample.
c. a matched-pairs design.
d. a block design.
e. a completely randomized design.
CHAPTER 4A farmer wishes to determine which of two brands of baby pig pellets, Kent or Moormans, produces better weight gains. Two of his sows each give birth to litters of 10 pigs on the same day, so he decides to give the baby pigs in litter A only Kent pellets, while the pigs in litter B will get only Moormans pellets. After four weeks, the average weight gain for pigs in litter A is greater than the average weight gain for pigs in litter B.
The weight of the pigs after four weeks is
a. a parameter.
b. the response variable.
c. the explanatory variable.
d. the placebo effect.
e. stratified.
CHAPTER 4A farmer wishes to determine which of two brands of baby pig pellets, Kent or Moormans, produces better weight gains. Two of his sows each give birth to litters of 10 pigs on the same day, so he decides to give the baby pigs in litter A only Kent pellets, while the pigs in litter B will get only Moormans pellets. After four weeks, the average weight gain for pigs in litter A is greater than the average weight gain for pigs in litter B.
The weight of the pigs after four weeks is
a. a parameter.
b. the response variable.
c. the explanatory variable.
d. the placebo effect.
e. stratified.
CHAPTER 3
The height (in feet) and volume (in cubic feet) of usable lumber of 32 cherry trees are measured by a researcher. The goal is to determine if volume of usable lumber can be estimated from the height of a tree.
In this study, the response variable is
a. height of researcher.
b. volume of lumber.
c. height of tree.
d. the measuring instrument used to measure volume.
e. impossible to determine.
CHAPTER 3
The height (in feet) and volume (in cubic feet) of usable lumber of 32 cherry trees are measured by a researcher. The goal is to determine if volume of usable lumber can be estimated from the height of a tree.
In this study, the response variable is
a. height of researcher.
b. volume of lumber.
c. height of tree.
d. the measuring instrument used to measure volume.
e. impossible to determine.
CHAPTER 3
The height (in feet) and volume (in cubic feet) of usable lumber of 32 cherry trees are measured by a researcher. The goal is to determine if volume of usable lumber can be estimated from the height of a tree.
I. There is a positive association between height and volume.
II. There is an outlier in the plot.
III. As the height of a cherry tree increases, the volume of useable lumber it yields increases.
a. I only
b. II only
c. III only
d. I and II
e. I, II, and III
CHAPTER 3
The height (in feet) and volume (in cubic feet) of usable lumber of 32 cherry trees are measured by a researcher. The goal is to determine if volume of usable lumber can be estimated from the height of a tree.
I. There is a positive association between height and volume.
II. There is an outlier in the plot.
III. As the height of a cherry tree increases, the volume of useable lumber it yields increases.
a. I only
b. II only
c. III only
d. I and II
e. I, II, and III
CHAPTER 3
The height (in feet) and volume (in cubic feet) of usable lumber of 32 cherry trees are measured by a researcher. The goal is to determine if volume of usable lumber can be estimated from the height of a tree.
If the data point (65,70) were removed from this study, how would the value of the correlation r change?
a. r would be smaller, since there are fewer data points.
b. r would be smaller, because this point falls in the pattern of the rest of the data.
c. r would be larger, since the x and y coordinates are larger than the mean x and mean y, respectively.
d. r would be larger, since this point does not fall in the pattern of the rest of the data.
e. r would not change, since it’s value does not depend which variable is used for x and which is used for y.
CHAPTER 3
The height (in feet) and volume (in cubic feet) of usable lumber of 32 cherry trees are measured by a researcher. The goal is to determine if volume of usable lumber can be estimated from the height of a tree.
If the data point (65,70) were removed from this study, how would the value of the correlation r change?
a. r would be smaller, since there are fewer data points.
b. r would be smaller, because this point falls in the pattern of the rest of the data.
c. r would be larger, since the x and y coordinates are larger than the mean x and mean y, respectively.
d. r would be larger, since this point does not fall in the pattern of the rest of the data.
e. r would not change, since it’s value does not depend which variable is used for x and which is used for y.
CHAPTER 3
A study of the effects of television on child development measured how many hours of television each of 125 grade school children watched per week during a school year and each child’s reading score. Which variable would you put on the horizontal axis of a scatterplot of the data?
a. Reading score, because it is the response variable.
b. Reading score, because it is the explanatory variable.
c. Hours of television, because it is the response variable.
d. Hours of television, because it is the explanatory variable.
e. It makes no difference, because there is no explanatory-response distinction in this study.
CHAPTER 3
A study of the effects of television on child development measured how many hours of television each of 125 grade school children watched per week during a school year and each child’s reading score. Which variable would you put on the horizontal axis of a scatterplot of the data?
a. Reading score, because it is the response variable.
b. Reading score, because it is the explanatory variable.
c. Hours of television, because it is the response variable.
d. Hours of television, because it is the explanatory variable.
e. It makes no difference, because there is no explanatory-response distinction in this study.
CHAPTER 3The following table and scatter plot present data on wine consumption (in liters per person per year) and death rate from heart attacks (in deaths per 100,000 people per year) in 19 developed Western countries.
Do these data provide strong evidence that drinking wine actually causes a reduction in heart disease deaths?
a. Yes. The strong straight-line association in the plot shows that wine has a strong effect on heart disease deaths.
b. No. Countries that drink lots of wine may differ in other ways from countries that drink little wine. We can't be sure the wine accounts for the difference in heart disease deaths.
c. No. r does not equal –1.
d. No. The plot shows that differences among countries are not large enough to be important.
e. No. The plot shows that deaths go up as more alcohol from wine is consumed.
CHAPTER 3The following table and scatter plot present data on wine consumption (in liters per person per year) and death rate from heart attacks (in deaths per 100,000 people per year) in 19 developed Western countries.
Do these data provide strong evidence that drinking wine actually causes a reduction in heart disease deaths?
a. Yes. The strong straight-line association in the plot shows that wine has a strong effect on heart disease deaths.
b. No. Countries that drink lots of wine may differ in other ways from countries that drink little wine. We can't be sure the wine accounts for the difference in heart disease deaths.
c. No. r does not equal –1.
d. No. The plot shows that differences among countries are not large enough to be important.
e. No. The plot shows that deaths go up as more alcohol from wine is consumed.
CHAPTER 3The following table and scatter plot present data on wine consumption (in liters per person per year) and death rate from heart attacks (in deaths per 100,000 people per year) in 19 developed Western countries.
If heart disease death rate were expressed as deaths per 1,000 people instead of as deaths per 100,000 people, how would the correlation rbetween wine consumption and heart disease death rate change?
a. r would be divided by 100.
b. r would be divided by 10.
c. r would not change.
d. r would be multiplied by 10.
e. r would be multiplied by 100.
CHAPTER 3The following table and scatter plot present data on wine consumption (in liters per person per year) and death rate from heart attacks (in deaths per 100,000 people per year) in 19 developed Western countries.
If heart disease death rate were expressed as deaths per 1,000 people instead of as deaths per 100,000 people, how would the correlation rbetween wine consumption and heart disease death rate change?
a. r would be divided by 100.
b. r would be divided by 10.
c. r would not change.
d. r would be multiplied by 10.
e. r would be multiplied by 100.
CHAPTER 3The following table and scatter plot present data on wine consumption (in liters per person per year) and death rate from heart attacks (in deaths per 100,000 people per year) in 19 developed Western countries.
The correlation between wine consumption and heart disease deaths is one of the following values. From the scatterplot, which must it be?
a. r = –0.84
b. r = –0.25
c. r is very close to 0
d. r = 0.25
e. r = 0.84
CHAPTER 3The following table and scatter plot present data on wine consumption (in liters per person per year) and death rate from heart attacks (in deaths per 100,000 people per year) in 19 developed Western countries.
The correlation between wine consumption and heart disease deaths is one of the following values. From the scatterplot, which must it be?
a. r = –0.84
b. r = –0.25
c. r is very close to 0
d. r = 0.25
e. r = 0.84
CHAPTER 3
The correlation coefficient measures
a. whether there is a relationship between two variables.
b. the strength of the relationship between two quantitative variables.
c. whether or not a scatterplot shows an interesting pattern.
d. whether a cause and effect relation exists between two variables.
e. the strength of the linear relationship between two quantitative variables.
CHAPTER 3
The correlation coefficient measures
a. whether there is a relationship between two variables.
b. the strength of the relationship between two quantitative variables.
c. whether or not a scatterplot shows an interesting pattern.
d. whether a cause and effect relation exists between two variables.
e. the strength of the linear relationship between two quantitative variables.
CHAPTER 3
Which of the following are most likely to be negatively correlated?
a. The total floor space and the price of an apartment in New York.
b. The percentage of body fat and the time it takes to run a mile for male college students.
c. The heights and yearly earnings of 35-year-old U.S. adults.
d. Gender and yearly earnings among 35-year-old U.S. adults.
e. The prices and the weights of all racing bicycles sold last year in Chicago.
CHAPTER 3
Which of the following are most likely to be negatively correlated?
a. The total floor space and the price of an apartment in New York.
b. The percentage of body fat and the time it takes to run a mile for male college students.
c. The heights and yearly earnings of 35-year-old U.S. adults.
d. Gender and yearly earnings among 35-year-old U.S. adults.
e. The prices and the weights of all racing bicycles sold last year in Chicago.
CHAPTER 3
Consider the following scatterplot of amounts of CO (carbon monoxide) and NOX (nitrogen oxide) in grams per mile driven in the exhausts of cars. The least-squares regression line has been drawn in the plot.
The intercept of the least-squares regression line is approximately
a. –0.7.
b. –0.1.
c. 1.8.
d. 2.0.
e. 18.
CHAPTER 3Consider the following scatterplot of amounts of CO (carbon monoxide) and NOX (nitrogen oxide) in grams per mile driven in the exhausts of cars. The least-squares regression line has been drawn in the plot.
The intercept of the least-squares regression line is approximately
a. –0.7.
b. –0.1.
c. 1.8.
d. 2.0.
e. 18.
CHAPTER 3Consider the following scatterplot of amounts of CO (carbon monoxide) and NOX (nitrogen oxide) in grams per mile driven in the exhausts of cars. The least-squares regression line has been drawn in the plot.
Based on the scatterplot, the least-squares line would predict that a car that emits 10 grams of CO per mile driven would emit approximately how many grams of NOX per mile driven?
a. 10.0
b. 1.7
c. 2.2
d. 1.1
e. 0.7
CHAPTER 3Consider the following scatterplot of amounts of CO (carbon monoxide) and NOX (nitrogen oxide) in grams per mile driven in the exhausts of cars. The least-squares regression line has been drawn in the plot.
Based on the scatterplot, the least-squares line would predict that a car that emits 10 grams of CO per mile driven would emit approximately how many grams of NOX per mile driven?
a. 10.0
b. 1.7
c. 2.2
d. 1.1
e. 0.7
CHAPTER 3Consider the following scatterplot of amounts of CO (carbon monoxide) and NOX (nitrogen oxide) in grams per mile driven in the exhausts of cars. The least-squares regression line has been drawn in the plot.
In the scatterplot, the point indicated by the open circle
a. has a negative value for the residual.
b. has a positive value for the residual.
c. has a zero value for the residual.
d. has a zero value for the correlation.
e. is an outlier.
CHAPTER 3Consider the following scatterplot of amounts of CO (carbon monoxide) and NOX (nitrogen oxide) in grams per mile driven in the exhausts of cars. The least-squares regression line has been drawn in the plot.
In the scatterplot, the point indicated by the open circle
a. has a negative value for the residual.
b. has a positive value for the residual.
c. has a zero value for the residual.
d. has a zero value for the correlation.
e. is an outlier.
CHAPTER 3
Suppose we fit the least-squares regression line to a set of data. If a plot of the residuals shows a curved pattern,
a. a straight line is not a good summary for the data.
b. the correlation must be 0.
c. the correlation must be positive.
d. outliers must be present.
e. r2 = 0.
CHAPTER 3
Suppose we fit the least-squares regression line to a set of data. If a plot of the residuals shows a curved pattern,
a. a straight line is not a good summary for the data.
b. the correlation must be 0.
c. the correlation must be positive.
d. outliers must be present.
e. r2 = 0.
CHAPTER 3
Which of the following statements about influential points and outliers are true?
I. An influential point always has a high residual.
II. Outliers are always influential points.
III. Removing an influential point always causes a marked change in either the correlation, the regression equation, or both.
a. I only.
b. II only.
c. III only.
d. II and III only.
e. I, II, and III are all true.
CHAPTER 3
Which of the following statements about influential points and outliers are true?
I. An influential point always has a high residual.
II. Outliers are always influential points.
III. Removing an influential point always causes a marked change in either the correlation, the regression equation, or both.
a. I only.
b. II only.
c. III only.
d. II and III only.
e. I, II, and III are all true.
CHAPTER 3Below is a scatter plot (with the least squares regression line) for calories and protein (in grams) in one cup of 11 varieties of dried beans. The computer output for this regression is below the plot.
Predictor Coef SE Coef T P
Constant 2.08 15.93 0.13 0.899
Calories 0.06297 0.02409 2.61 0.028
S = 3.37648 R-Sq = 43.2% R-Sq(adj) = 36.9%
The circled point on the scatter plot represents lima beans, which have 621 calories and 37 grams of protein. The residual for lima beans is:
a. –37.0
b. –4.18
c. 4.18
d. 37.0
e. 41.18
CHAPTER 3Below is a scatter plot (with the least squares regression line) for calories and protein (in grams) in one cup of 11 varieties of dried beans. The computer output for this regression is below the plot.
Predictor Coef SE Coef T P
Constant 2.08 15.93 0.13 0.899
Calories 0.06297 0.02409 2.61 0.028
S = 3.37648 R-Sq = 43.2% R-Sq(adj) = 36.9%
The circled point on the scatter plot represents lima beans, which have 621 calories and 37 grams of protein. The residual for lima beans is:
a. –37.0
b. –4.18
c. 4.18
d. 37.0
e. 41.18
CHAPTER 3Below is a scatter plot (with the least squares regression line) for calories and protein (in grams) in one cup of 11 varieties of dried beans. The computer output for this regression is below the plot.
Predictor Coef SE Coef T P
Constant 2.08 15.93 0.13 0.899
Calories 0.06297 0.02409 2.61 0.028
S = 3.37648 R-Sq = 43.2% R-Sq(adj) = 36.9%
Which of the following statements is a correct interpretation of the slope of the regression line?
a. For each 1-unit increase in the calorie content, the predicted protein content increases by 2.08 grams.
b. For each 1-unit increase in the calorie content, the predicted protein content increases by 0.063 grams.
c. For each 1-gram increase in the protein content, the predicted calorie content increases by 2.08 grams.
d. For each 1-gram increase in the protein content, the predicted calorie content increases by 0.063 grams.
e. For each 1-gram increase in the protein content, the predicted calorie content increases by 0.024 grams.
CHAPTER 3Below is a scatter plot (with the least squares regression line) for calories and protein (in grams) in one cup of 11 varieties of dried beans. The computer output for this regression is below the plot.
Predictor Coef SE Coef T P
Constant 2.08 15.93 0.13 0.899
Calories 0.06297 0.02409 2.61 0.028
S = 3.37648 R-Sq = 43.2% R-Sq(adj) = 36.9%
Which of the following statements is a correct interpretation of the slope of the regression line?
a. For each 1-unit increase in the calorie content, the predicted protein content increases by 2.08 grams.
b. For each 1-unit increase in the calorie content, the predicted protein content increases by 0.063 grams.
c. For each 1-gram increase in the protein content, the predicted calorie content increases by 2.08 grams.
d. For each 1-gram increase in the protein content, the predicted calorie content increases by 0.063 grams.
e. For each 1-gram increase in the protein content, the predicted calorie content increases by 0.024 grams.
CHAPTER 3Below is a scatter plot (with the least squares regression line) for calories and protein (in grams) in one cup of 11 varieties of dried beans. The computer output for this regression is below the plot.
One cup of dried soybeans contains 846 calories. Which of the following statement is appropriate?
a. We can predict that the protein content for soybeans is 55.4 grams.
b. We can predict that the protein content for soybeans is 53.3 grams
c. We can predict that the protein content for soybeans is 51.2 grams
d. Unless we are given the observed protein content for soybeans, we can’t calculate the predicted protein content.
e. It would be inappropriate to predict the protein content of soybeans with this regression model, since their calorie content is well beyond the range of these data.
CHAPTER 3Below is a scatter plot (with the least squares regression line) for calories and protein (in grams) in one cup of 11 varieties of dried beans. The computer output for this regression is below the plot.
One cup of dried soybeans contains 846 calories. Which of the following statement is appropriate?
a. We can predict that the protein content for soybeans is 55.4 grams.
b. We can predict that the protein content for soybeans is 53.3 grams
c. We can predict that the protein content for soybeans is 51.2 grams
d. Unless we are given the observed protein content for soybeans, we can’t calculate the predicted protein content.
e. It would be inappropriate to predict the protein content of soybeans with this regression model, since their calorie content is well beyond the range of these data.
CHAPTER 3Below is a scatter plot (with the least squares regression line) for calories and protein (in grams) in one cup of 11 varieties of dried beans. The computer output for this regression is below the plot.
Predictor Coef SE Coef T P
Constant 2.08 15.93 0.13 0.899
Calories 0.06297 0.02409 2.61 0.028
S = 3.37648 R-Sq = 43.2% R-Sq(adj) = 36.9%
Which of the following best describes what the number S = 3.37648 represents?
a. The slope of the regression line is 3.37648.
b. The standard deviation of the explanatory variable, calories, is 3.37648.
c. The standard deviation of the response variable, protein content, is 3.37648.
d. The standard deviation of the residuals is 3.37648.
e. The ratio of the standard deviation of protein to the standard deviation of calories is 3.37648.
CHAPTER 3Below is a scatter plot (with the least squares regression line) for calories and protein (in grams) in one cup of 11 varieties of dried beans. The computer output for this regression is below the plot.
Predictor Coef SE Coef T P
Constant 2.08 15.93 0.13 0.899
Calories 0.06297 0.02409 2.61 0.028
S = 3.37648 R-Sq = 43.2% R-Sq(adj) = 36.9%
Which of the following best describes what the number S = 3.37648 represents?
a. The slope of the regression line is 3.37648.
b. The standard deviation of the explanatory variable, calories, is 3.37648.
c. The standard deviation of the response variable, protein content, is 3.37648.
d. The standard deviation of the residuals is 3.37648.
e. The ratio of the standard deviation of protein to the standard deviation of calories is 3.37648.
CHAPTER 3A fisheries biologist studying whitefish in a Canadian Lake collected data on the length (in centimeters) and egg production for 25 female fish. A scatter plot of her results and computer regression analysis of egg production versus fish length are given below.
Which of the following is the plot of residuals versus fish lengths?
A B C D E
CHAPTER 3A fisheries biologist studying whitefish in a Canadian Lake collected data on the length (in centimeters) and egg production for 25 female fish. A scatter plot of her results and computer regression analysis of egg production versus fish length are given below.
Which of the following is the plot of residuals versus fish lengths?
A B C D E
CHAPTER 3
A study gathers data on the outside temperature during the winter, in degrees Fahrenheit, and the amount of natural gas a household consumes, in cubic feet per day. Call the temperature x and gas consumption y. The house is heated with gas, so x helps explain y. The least-squares regression line for predicting y from x is
ො𝑦 = 1344 − 19𝑥
On a day when the temperature is 20°F, the regression line predicts that gas used will be about
a. 1724 cubic feet.
b. 1383 cubic feet.
c. 1325 cubic feet.
d. 964 cubic feet.
e. none of these.
CHAPTER 3
A study gathers data on the outside temperature during the winter, in degrees Fahrenheit, and the amount of natural gas a household consumes, in cubic feet per day. Call the temperature x and gas consumption y. The house is heated with gas, so x helps explain y. The least-squares regression line for predicting y from x is
ො𝑦 = 1344 − 19𝑥
On a day when the temperature is 20°F, the regression line predicts that gas used will be about
a. 1724 cubic feet.
b. 1383 cubic feet.
c. 1325 cubic feet.
d. 964 cubic feet.
e. none of these.
CHAPTER 3
A study gathers data on the outside temperature during the winter, in degrees Fahrenheit, and the amount of natural gas a household consumes, in cubic feet per day. Call the temperature xand gas consumption y. The house is heated with gas, so x helps explain y. The least-squares regression line for predicting y from x is
ො𝑦 = 1344 − 19𝑥
What does the number 1344 represent in the equation?
a. Predicted gas usage (in cubic feet) when the temperature is 19 degrees Fahrenheit.
b. Predicted gas usage (in cubic feet) when the temperature is 0 degrees Fahrenheit.
c. It’s the y-intercept of the regression line, but it has no practical purpose in the context of the problem.
d. The maximum possible gas a household can use.
e. None of the above.
CHAPTER 3
A study gathers data on the outside temperature during the winter, in degrees Fahrenheit, and the amount of natural gas a household consumes, in cubic feet per day. Call the temperature xand gas consumption y. The house is heated with gas, so x helps explain y. The least-squares regression line for predicting y from x is
ො𝑦 = 1344 − 19𝑥
What does the number 1344 represent in the equation?
a. Predicted gas usage (in cubic feet) when the temperature is 19 degrees Fahrenheit.
b. Predicted gas usage (in cubic feet) when the temperature is 0 degrees Fahrenheit.
c. It’s the y-intercept of the regression line, but it has no practical purpose in the context of the problem.
d. The maximum possible gas a household can use.
e. None of the above.
CHAPTER 2
You can roughly locate the mean of a density curve by eye because it is
a. the point at which the curve would balance if made of solid material.
b. the point that divides the area under the curve into two equal parts.
c. the point at which the curve reaches its peak.
d. the point where the curvature changes direction.
e. the point at which the height of the graph is equal to 1.
CHAPTER 2
You can roughly locate the mean of a density curve by eye because it is
a. the point at which the curve would balance if made of solid material.
b. the point that divides the area under the curve into two equal parts.
c. the point at which the curve reaches its peak.
d. the point where the curvature changes direction.
e. the point at which the height of the graph is equal to 1.
CHAPTER 2
You can roughly locate the median of a density curve by eye because it is
a. the point at which the curve would balance if made of solid material.
b. the point that divides the area under the curve into two equal parts.
c. the point at which the curve reaches its peak.
d. the point where the curvature changes direction.
e. the point at which the height of the graph is equal to 1.
CHAPTER 2
You can roughly locate the median of a density curve by eye because it is
a. the point at which the curve would balance if made of solid material.
b. the point that divides the area under the curve into two equal parts.
c. the point at which the curve reaches its peak.
d. the point where the curvature changes direction.
e. the point at which the height of the graph is equal to 1.
CHAPTER 2
Here is a list of exam scores for the 14 students in Mr. Williams’s calculus class:
60 61 61 65 72 75 75 78 81 81 85 89 91 98
What is the percentile of the person whose score was 85?
a. 15%
b. 21%
c. 29%
d. 71%
e. 85%
CHAPTER 2
Here is a list of exam scores for the 14 students in Mr. Williams’s calculus class:
60 61 61 65 72 75 75 78 81 81 85 89 91 98
What is the percentile of the person whose score was 85?
a. 15%
b. 21%
c. 29%
d. 71%
e. 85%
CHAPTER 2An ecologist who was studying starfish populations collected starfish of the species Pisaster was interested in the distribution of sizes of starfish on a certain shoreline. One measure of size is “arm length.” Below is a cumulative relative frequency distribution for the arm length of 102 Pisaster individuals.
The median and interquartile range of this distribution are approximately:
a. Median is 15.2; Intequartile range is 12.5 to 16.2
b. Median is 13; Interquartile range is 13 to 16.1
c. Median is 13; Interquartile range is 3.1
d. Median is 13; Intequartile range is 3.7
e. Median is 15.2; Intequartile range is 3.7
CHAPTER 2An ecologist who was studying starfish populations collected starfish of the species Pisaster was interested in the distribution of sizes of starfish on a certain shoreline. One measure of size is “arm length.” Below is a cumulative relative frequency distribution for the arm length of 102 Pisaster individuals.
The median and interquartile range of this distribution are approximately:
a. Median is 15.2; Intequartile range is 12.5 to 16.2
b. Median is 13; Interquartile range is 13 to 16.1
c. Median is 13; Interquartile range is 3.1
d. Median is 13; Intequartile range is 3.7
e. Median is 15.2; Intequartile range is 3.7
CHAPTER 2
The distribution of household incomes in a small town is strongly skewed to the right. The mean income is $42,000 and the standard deviation is $24,000. The Ames family’s household income is $60,000. The z-score for the Ames family’s income is
a. –0.75
b. 0.3
c. 0.75
d. 0.86
e. None of these, because z-score cannot be used unless the distribution is Normal.
CHAPTER 2
The distribution of household incomes in a small town is strongly skewed to the right. The mean income is $42,000 and the standard deviation is $24,000. The Ames family’s household income is $60,000. The z-score for the Ames family’s income is
a. –0.75
b. 0.3
c. 0.75
d. 0.86
e. None of these, because z-score cannot be used unless the distribution is Normal.
CHAPTER 2Ramon is planning on buying a new car. He’s looking at the Ford Escape—a sport-utility vehicle—which gets 28 highway miles per gallon, and the Ford Fusion—a mid-sized sedan—which gets 31 highway miles per gallon. The mean fuel efficiency for all sport utility vehicles is 23, with a standard deviation of 7.6. The mean of all mid-sized sedans is 27, with a standard deviation of 5.2. Which vehicle has a better standing, relative to others of the same style?
a. The Ford Fusion sedan has a better relative standing, because it’s z-score is higher
b. The Ford Fusion sedan has a better relative standing., because it’s z-score is closer to 0.
c. The Ford Escape SUV has a better relative standing, because it’s z-score is higher
d. The Ford Escape SUV has a better relative standing, because it’s z-score is closer to 0.
e. We can’t make any comparisons unless we know that the distribution of fuel efficiency for vehicle types is Normally distributed.
CHAPTER 2Ramon is planning on buying a new car. He’s looking at the Ford Escape—a sport-utility vehicle—which gets 28 highway miles per gallon, and the Ford Fusion—a mid-sized sedan—which gets 31 highway miles per gallon. The mean fuel efficiency for all sport utility vehicles is 23, with a standard deviation of 7.6. The mean of all mid-sized sedans is 27, with a standard deviation of 5.2. Which vehicle has a better standing, relative to others of the same style?
a. The Ford Fusion sedan has a better relative standing, because it’s z-score is higher
b. The Ford Fusion sedan has a better relative standing., because it’s z-score is closer to 0.
c. The Ford Escape SUV has a better relative standing, because it’s z-score is higher
d. The Ford Escape SUV has a better relative standing, because it’s z-score is closer to 0.
e. We can’t make any comparisons unless we know that the distribution of fuel efficiency for vehicle types is Normally distributed.
CHAPTER 2
28 31 34 35 37 41 42 42 42 47
49 51 52 52 60 61 67 72 75 77
A sample was taken of the salaries of 20 employees of a large company. The
following are the salaries (in thousands of dollars) for this year. For convenience,
the data are ordered.
Suppose each employee in the company receives a $3,000 raise for next year
(each employee's salary is increased by $3,000).
The mean salary for the employees will
a. be unchanged.
b. increase by $3,000.
c. be multiplied by $3,000.
d. increase by $3000e. increase by $150.
CHAPTER 2
28 31 34 35 37 41 42 42 42 47
49 51 52 52 60 61 67 72 75 77
A sample was taken of the salaries of 20 employees of a large company. The
following are the salaries (in thousands of dollars) for this year. For convenience,
the data are ordered.
Suppose each employee in the company receives a $3,000 raise for next year
(each employee's salary is increased by $3,000).
The mean salary for the employees will
a. be unchanged.
b. increase by $3,000.
c. be multiplied by $3,000.
d. increase by $3000e. increase by $150.
CHAPTER 2
28 31 34 35 37 41 42 42 42 47
49 51 52 52 60 61 67 72 75 77
Suppose each employee in the company receives a $3,000 raise for next year
(each employee's salary is increased by $3,000).
The standard deviation of the salaries for the employees will
a. be unchanged.
b. increase by $3,000.
c. be multiplied by $3,000.
d. increase by .
e. decrease by $3,000.
CHAPTER 2
28 31 34 35 37 41 42 42 42 47
49 51 52 52 60 61 67 72 75 77
Suppose each employee in the company receives a $3,000 raise for next year
(each employee's salary is increased by $3,000).
The standard deviation of the salaries for the employees will
a. be unchanged.
b. increase by $3,000.
c. be multiplied by $3,000.
d. increase by .
e. decrease by $3,000.
CHAPTER 2
28 31 34 35 37 41 42 42 42 47
49 51 52 52 60 61 67 72 75 77
Suppose each employee in the company receives a $3,000 raise for next year
(each employee's salary is increased by $3,000).
The z-scores of the salaries for the employees will
a. be unchanged.
b. increase by $3,000.
c. be multiplied by $3,000.
d. increase by .
e. decrease by $3,000.
CHAPTER 2
28 31 34 35 37 41 42 42 42 47
49 51 52 52 60 61 67 72 75 77
Suppose each employee in the company receives a $3,000 raise for next year
(each employee's salary is increased by $3,000).
The z-scores of the salaries for the employees will
a. be unchanged.
b. increase by $3,000.
c. be multiplied by $3,000.
d. increase by .
e. decrease by $3,000.
CHAPTER 2
Items produced by a manufacturing process are supposed to weigh 90 grams. The manufacturing process is such, however, that there is variability in the items produced and they do not all weigh exactly 90 grams. The distribution of weights can be approximated by a Normal distribution with mean 90 grams and a standard deviation of 1 gram. About what percentage of the items will either weigh less than 87 grams or more than 93 grams?
a. 0.15%
b. 0.3%
c. 6%
d. 94%
e. 99.7%
CHAPTER 2
Items produced by a manufacturing process are supposed to weigh 90 grams. The manufacturing process is such, however, that there is variability in the items produced and they do not all weigh exactly 90 grams. The distribution of weights can be approximated by a Normal distribution with mean 90 grams and a standard deviation of 1 gram. About what percentage of the items will either weigh less than 87 grams or more than 93 grams?
a. 0.15%
b. 0.3%
c. 6%
d. 94%
e. 99.7%
CHAPTER 2
Birthweights at a local hospital have a Normal distribution with a mean of 110 oz. and a standard deviation of 15 oz. Which of the following is the proportion of infants with birthweights between 125 oz. and 140 oz.?
a. 0.135
b. 0.270
c. 0.475
d. 0.680
e. 0.815
CHAPTER 2
Birthweights at a local hospital have a Normal distribution with a mean of 110 oz. and a standard deviation of 15 oz. Which of the following is the proportion of infants with birthweights between 125 oz. and 140 oz.?
a. 0.135
b. 0.270
c. 0.475
d. 0.680
e. 0.815
CHAPTER 2
If the heights of 99.7% of American men are between 5' 0" and 7' 0", what is your estimate of the standard deviation of the height of American men?
a. 1"
b. 3"
c. 4"
d. 6"
e. 12"
CHAPTER 2
If the heights of 99.7% of American men are between 5' 0" and 7' 0", what is your estimate of the standard deviation of the height of American men?
a. 1"
b. 3"
c. 4"
d. 6"
e. 12"
CHAPTER 2
A company produces ceramic floor tiles that are supposed to have a surface area of 16.0 square inches. Due to variability in the manufacturing process, the actual surface area has a Normal distribution with a mean of 16.1 square inches and a standard deviation of 0.2 square inches. The proportion of tiles produced by the process with surface area less than 16.0 square inches is
a. 0.1915.
b. 0.3085.
c. 0.3173.
d. 0.4115.
e. 0.6915.
CHAPTER 2
A company produces ceramic floor tiles that are supposed to have a surface area of 16.0 square inches. Due to variability in the manufacturing process, the actual surface area has a Normal distribution with a mean of 16.1 square inches and a standard deviation of 0.2 square inches. The proportion of tiles produced by the process with surface area less than 16.0 square inches is
a. 0.1915.
b. 0.3085.
c. 0.3173.
d. 0.4115.
e. 0.6915.
CHAPTER 2
The time to complete a standardized exam is approximately Normal with a mean of 70 minutes and a standard deviation of 10 minutes. How much time should be given to complete the exam so that 80% of the students will complete the exam in the time given?
a. 61.6 minutes
b. 78.4 minutes
c. 79.8 minutes
d. 84 minutes
e. 92.8 minutes
CHAPTER 2
The time to complete a standardized exam is approximately Normal with a mean of 70 minutes and a standard deviation of 10 minutes. How much time should be given to complete the exam so that 80% of the students will complete the exam in the time given?
a. 61.6 minutes
b. 78.4 minutes
c. 79.8 minutes
d. 84 minutes
e. 92.8 minutes
CHAPTER 2
The plot shown below is a Normal probability plot for the total annual cost (tuition plus room and board) to attend 126 of the top colleges in the country in 2005. Which statement is true for these data?
a. The data are clearly Normally distributed.
b. The data are approximately Normally distributed.
c. The data are clearly skewed to the left.
d. The data are clearly skewed to the right.
e. There is insufficient information to determine the shape of the distribution.
CHAPTER 2
When a basketball player makes a pass to a teammate who then scores, he earns an “assist.” Below is a Normal probability plot for the number of assists earned by all players in the National Basketball Association during the 2010 regular season.
Which of the following statements about the shape of this distribution is true?
a. The distribution is Normal.
b. The distribution is approximately Normal.
c. The distribution is roughly symmetric.
d. The distribution has no potential outliers.
e. The distribution is skewed.
CHAPTER 2
When a basketball player makes a pass to a teammate who then scores, he earns an “assist.” Below is a Normal probability plot for the number of assists earned by all players in the National Basketball Association during the 2010 regular season.
Which of the following statements about the shape of this distribution is true?
a. The distribution is Normal.
b. The distribution is approximately Normal.
c. The distribution is roughly symmetric.
d. The distribution has no potential outliers.
e. The distribution is skewed.
CHAPTER 1
A survey typically records many variables of interest to the researchers involved. Below are some of the variables from a survey conducted by the U.S. Postal Service. Which of the variables is categorical?
a. County of residence
b. Number of people, both adults and children, living in the household
c. Total household income, before taxes, in 1993
d. Age of respondent
e. Number of rooms in the dwelling
CHAPTER 1
A survey typically records many variables of interest to the researchers involved. Below are some of the variables from a survey conducted by the U.S. Postal Service. Which of the variables is categorical?
a. County of residence
b. Number of people, both adults and children, living in the household
c. Total household income, before taxes, in 1993
d. Age of respondent
e. Number of rooms in the dwelling
CHAPTER 1
You open a package of plain M & M candies and count how many there are of each color. The distribution of the variable “candy color” is:
a. The colors: Red, Orange, Green, Yellow, Brown, and Blue.
b. The total number of candies in the package.
c. Six—the number of different colors there are in the package.
d. The six different colors and how many there are of each.
e. Since “color” is a categorical variable, it doesn’t have a distribution.
CHAPTER 1
You open a package of plain M & M candies and count how many there are of each color. The distribution of the variable “candy color” is:
a. The colors: Red, Orange, Green, Yellow, Brown, and Blue.
b. The total number of candies in the package.
c. Six—the number of different colors there are in the package.
d. The six different colors and how many there are of each.
e. Since “color” is a categorical variable, it doesn’t have a distribution.
CHAPTER 1
You measure the age (years), weight (pounds), and marital status (single, married, divorced, or widowed) of 1400 women. How many variables did you measure?
a. 1
b. 2
c. 3
d. 1400
e. 1403
CHAPTER 1
You measure the age (years), weight (pounds), and marital status (single, married, divorced, or widowed) of 1400 women. How many variables did you measure?
a. 1
b. 2
c. 3
d. 1400
e. 1403
CHAPTER 1
The table below shows the results of the New Hampshire Republican Presidential Primary on January 10, 2012.
Which of the following lists of graphs are all appropriate ways of presenting these data?
a. Bar graph, Pie Chart, Box plot
b. Bar graph, Box plot
c. Bar graph, Pie Chart
d. Bar Graph only
e. Pie Chart only
Candidate Percentage of Votes
Mitt Romney 39
Ron Paul 23
John Huntsman 17
Rick Santorum 9
Newt Gingrich 9
Other 3
CHAPTER 1
The table below shows the results of the New Hampshire Republican Presidential Primary on January 10, 2012.
Which of the following lists of graphs are all appropriate ways of presenting these data?
a. Bar graph, Pie Chart, Box plot
b. Bar graph, Box plot
c. Bar graph, Pie Chart
d. Bar Graph only
e. Pie Chart only
Candidate Percentage of Votes
Mitt Romney 39
Ron Paul 23
John Huntsman 17
Rick Santorum 9
Newt Gingrich 9
Other 3
CHAPTER 1
Below is a histogram of the heights of gold-medal-winning high jumps in the Olympic Games since 1896.
Which of the following statements is supported by this histogram?
a. The median jump is between 75 and 80 inches.
b. The median jump is between 80 and 85 inches.
c. The smallest jump must be below 65 inches.
d. The winning jump in the 1976 Olympic Games was 40 inches.
e. The mean jump was equal to the median jump.
CHAPTER 1
Below is a histogram of the heights of gold-medal-winning high jumps in the Olympic Games since 1896.
Which of the following statements is supported by this histogram?
a. The median jump is between 75 and 80 inches.
b. The median jump is between 80 and 85 inches.
c. The smallest jump must be below 65 inches.
d. The winning jump in the 1976 Olympic Games was 40 inches.
e. The mean jump was equal to the median jump.
CHAPTER 1
Below is a histogram of the heights of gold-medal-winning high jumps in the Olympic Games since 1896.
Which of the following values is closest to the mean jump?
a. 70 inches.
b. 74 inches.
c. 75 inches.
d. 81 inches.
e. 86 inches.
CHAPTER 1
Below is a histogram of the heights of gold-medal-winning high jumps in the Olympic Games since 1896.
Which of the following values is closest to the mean jump?
a. 70 inches.
b. 74 inches.
c. 75 inches.
d. 81 inches.
e. 86 inches.
CHAPTER 1
Below is a histogram of the heights of gold-medal-winning high jumps in the Olympic Games since 1896.
Based on this histogram, the percentage of the winning jumps that were at least 80 inches is about
a. 10%.
b. 35%.
c. 45%.
d. 55%.
e. 90%.
CHAPTER 1
Below is a histogram of the heights of gold-medal-winning high jumps in the Olympic Games since 1896.
Based on this histogram, the percentage of the winning jumps that were at least 80 inches is about
a. 10%.
b. 35%.
c. 45%.
d. 55%.
e. 90%.
CHAPTER 1
Which of the following statements is true?
a. In a distribution that is skewed right, the median is larger than the mean.
b. Fifty percent of the scores in a distribution are between the first and third quartile.
c. The third quartile of a distribution is always greater than the mean.
d. The median of a distribution is always greater than the mean.
e. The range of a distribution is typically smaller than the interquartile range.
CHAPTER 1
Which of the following statements is true?
a. In a distribution that is skewed right, the median is larger than the mean.
b. Fifty percent of the scores in a distribution are between the first and third quartile.
c. The third quartile of a distribution is always greater than the mean.
d. The median of a distribution is always greater than the mean.
e. The range of a distribution is typically smaller than the interquartile range.
CHAPTER 1
Mr. Williams asked the 26 seniors in his statistics class how many A.P. courses they had taken during high school. Below is a dot plot summarizing the results of his survey.
Which of the following is a
correct box plot for these
data?
CHAPTER 1
Mr. Williams asked the 26 seniors in his statistics class how many A.P. courses they had taken during high school. Below is a dot plot summarizing the results of his survey.
Which of the following is a
correct box plot for these
data? B
CHAPTER 1
There are three children in a room, ages three, four, and five. If another four-year-old child enters the room the
a. mean age will stay the same but the variance will increase.
b. mean age will stay the same but the variance will decrease.
c. mean age and variance will stay the same.
d. mean age and variance will increase.
e. mean age and variance will decrease.
CHAPTER 1
There are three children in a room, ages three, four, and five. If another four-year-old child enters the room the
a. mean age will stay the same but the variance will increase.
b. mean age will stay the same but the variance will decrease.
c. mean age and variance will stay the same.
d. mean age and variance will increase.
e. mean age and variance will decrease.
CHAPTER 1
A lobster fisherman is keeping track of the productivity of a set of traps he has placed in a favorite location. Below are the numbers of lobsters in these traps over the course of 12 different hauls.
0 3 3 3 4 5 5 6 7 7 12 14
According to the 1.5 x IQR rule, which values in the above distribution are outliers?
a. 0 only
b. 14 only
c. 12 and 14
d. 0 and 14
e. 0, 12, and 14
CHAPTER 1
A lobster fisherman is keeping track of the productivity of a set of traps he has placed in a favorite location. Below are the numbers of lobsters in these traps over the course of 12 different hauls.
0 3 3 3 4 5 5 6 7 7 12 14
According to the 1.5 x IQR rule, which values in the above distribution are outliers?
a. 0 only
b. 14 only
c. 12 and 14
d. 0 and 14
e. 0, 12, and 14
CHAPTER 1
All of the following distributions have a mean of 10. Which has the largest standard deviation?
a. 5, 5, 5, 10, 10, 10, 15, 15, 15
b. 5, 5, 5, 15, 15, 15
c. 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15
d. 10, 10, 10, 10, 10, 10, 10, 10
e. 5, 8, 10, 12, 15
CHAPTER 1
All of the following distributions have a mean of 10. Which has the largest standard deviation?
a. 5, 5, 5, 10, 10, 10, 15, 15, 15
b. 5, 5, 5, 15, 15, 15
c. 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15
d. 10, 10, 10, 10, 10, 10, 10, 10
e. 5, 8, 10, 12, 15
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