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Test Bank for Statistics , 8th Edition

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    Chapter 1 Test A 1-1 Chapter 1 Test A - Multiple Choice Section 1.1 (What are Data?) 1. [Objective: Understand data.] Data can be defined as numbers in context . Suppose you are given the following set of numbers: 1.73, 1.83, 1.57, 1.88, 1.70, 1.65 What additional information would allow you to define these numbers as data? a. Units of measurement. This could represent the heights of six 5-year-olds, in meters. b. Units of measurement. This could represent the heights of six 20-year-olds, in meters. c. We need to know where these numbers were collected. d. We need to know who collected these numbers. Section 1.2 (Classifying and Storing Data) 2. [Objective: Understand methods for coding categorical variables.] According to the following data table, which variable(s) is (are) categorical? Age Gender Weight Ethnicity 23 1 180 1 18 0 126 0 20 0 139 2 19 1 154 1 20 1 202 3 a. None are categorical because there are only numbers in the table b. Age, gender, and ethnicity c. Gender and ethnicity d. Gender 3. [Objective: Distinguish between stacked and unstacked data.] The following data table is organized using which method? Men’s Ages Women’s Ages 35 42 39 33 41 37 37 35 40 39 a. This is stacked data because the ages are separated by groups (in this case, gender). b. This is stacked data because each row represents one person. c. This is unstacked data because the ages are separated by groups (in this case, gender). d. This is unstacked data because each row represents one person.

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    1-2 Chapter 1 Test A 4. [Objective: Distinguish between numerical and categorical variables.] Determine which of the following five variables are numerical and which are categorical. age, gender, weight, ethnicity, favorite math class a. All of the variables are categorical. b. All of the variables are numerical. c. Age, weight, and favorite math class are numerical variables. Gender and ethnicity are categorical variables. d. Age and weight are numerical variables. Gender, ethnicity, and favorite math class are categorical variables. 5. [Objective: Distinguish between a population and a sample.] In a recent school poll, the administrators asked if students were satisfied with the school’s course offerings. What is the population of interest here? a. All students who are satisfied with the course offerings. b. All students who are not satisfied with the course offerings. c. All students who attend the school. d. All students who participated in the poll. Section 1.3 (Organizing Categorical Data) 6. [Objective: Understand what types of variables are used in two-way tables.] A two-way table is useful for describing which types of variables? a. Two numerical variables. b. Two categorical variables. c. One numerical variable. d. One numerical variable and one categorical variable. 7. [Objective: Find and use rates (including percentages).] In a study of 1200 adults, 480 out of the 630 women in the study said they attended a state college or university. What percent of the study’s participants were women? a. 40% b. 47.5% c. 52.5% d. 76.2%

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    Chapter 1 Test A 1-3 8. [Objective: Find and use rates (including percentages).] In a study of 1200 adults, 480 out of the 630 women in the study said they attended a state college or university. What percent of women attended a state college or university? a. 40% b. 47.5% c. 52.5% d. 76.2% 9. [Objective: Find and use rates (including percentages).] According to the following two-way table, what percent of people in the sample prefer dogs? Male Female Dog 40 25 Cat 25 10 a. 25% b. 35% c. 40% d. 65% 10. [Objective: Understand when and why percents are more useful than counts for describing and comparing groups.] According to the following two-way table, why are percentages more useful than counts to compare pet preferences between males and females? Male Female Dog 40 25 Cat 25 10 a. There are more males than females in the sample. b. There are more people who prefer dogs than cats in the sample. c. You should only use counts in a two-way table. d. You should only use percentages in a two-way table. Section 1.4 (Collecting Data to Understand Causality) 11. [Objective: Distinguish between observational studies and controlled experiments.] Determine if the following scenario is an observational study or a controlled experiment. A doctor is interested in determining whether a certain medication increases the risk of high blood pressure. He randomly selects 100 people for his study - 50 who will take the medication, and 50 who will take a placebo. He checks the patients’ blood pressures weekly for six months. a. Observational study b. Controlled experiment c. Neither

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    1-4 Chapter 1 Test A 12. [Objective: Distinguish between observational studies and controlled experiments.] Determine if the following scenario is an observational study or a controlled experiment. A doctor is interested in determining whether a certain medication increases the risk of high blood pressure. He reviews his patients’ medical records and finds that a higher proportion of people who take the medication are suffering from high blood pressure. a. Observational study b. Controlled experiment c. Neither 13. [Objective: Understand difference between treatment and outcome variables.] Researchers conducted an experiment to determine if children who participate in a new after-school tutoring program do better on state-mandated tests than children who do not attend the program. What are the treatment and outcome variables? a. The treatment variable is participation in the after-school program. The outcome variable is whether or not a child attended. b. The treatment variable is participation in the after-school program. The outcome variable is the test score on the state-mandated test. c. The treatment variable is the state-mandated test. The outcome variable is the participation in the after-school program. d. The treatment variable is the state-mandated test. The outcome variable is the test score on the state-mandated test. 14. [Objective: Understand when it is possible to infer a cause-and-effect relationship from a research study and when it is not.] Researchers conducted a study and determined that students who participate in sports are happier than students who do not. Can we conclude that participating in sports makes students happier? a. Yes, this is an observational study and we can conclude causation. b. Yes, this is an experiment and we can conclude causation. c. No, this is an observational study and we cannot conclude causation. d. No, this is an experiment and we cannot conclude causation.

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    Chapter 1 Test A 1-5 15. [Objective: Suggest confounding variables that are likely to occur in some situations.] A gym is offering a new 6-week weight loss exercise program for its members. Members who sign up for the program are weighed and measured once a week for the duration of the program. The owners of the gym want to know if the weight loss program actually helps people lose weight. What variable could be a possible confounding factor in determining the cause of weight loss? a. The person’s commitment to the program. b. The person’s marital status. c. The person’s family structure. d. The person’s diet. 16. [Objective: Determine when information is anecdotal.] In Los Angeles, juice cleansing is very popular. Some people have claimed that the cleanses are beneficial for weight loss, body detoxification, and treatment and prevention of illnesses. Can we conclude that juice cleansing causes these health benefits? a. Yes, the claims are true stories, so we do have evidence of the health benefits. b. No, the claims are lies, so we do not have evidence of the health benefits. c. Yes, the claims are anecdotes and give us a good comparison group to find health differences. d. No, the claims are anecdotes and do not give us a true comparison group to find health differences. 17. [Objective: Understand different requirements for controlled experiments.] What does it mean for an experiment to be double-blinded? a. The researcher does not know which participants are in the treatment and control groups. b. The participants do not know who is in the treatment and control groups. c. Neither the researcher nor the participants know who is in the treatment and control groups. d. The researcher and the participants know which group they are in because it is unethical to keep this information from them.

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    1-6 Chapter 1 Test A Use the following information for questions (18) - (20): A group of 500 patients who suffer from hypothyroidism, a condition in which your thyroid does not produce enough of certain hormones, were asked to participate in a study to determine the effectiveness of a new medication. The patients were randomly divided into two groups, one that was given the actual medication, and one that received a placebo pill. The results of the study are below. Medication Placebo Symptoms improved 205 140 Symptoms did not 65 90 18. [Objective: Understand when it is possible to infer a cause-and-effect relationship from a research study and when it is not.] What percent of patients who took the medication had improved symptoms? a. 41% b. 54% c. 65.2% d. 75.9% 19. [Objective: Understand when it is possible to infer a cause-and-effect relationship from a research study and when it is not.] Was the new medication effective in treating hypothyroidism? a. Yes, a higher percent of patients who took the medication had improved symptoms than the patients who took the placebo. b. Yes, both groups had more patients with improved symptoms. c. No, the patients who took the placebo also had improved symptoms. d. No, this was not a controlled experiment. 20. [Objective: Understand when it is possible to infer a cause-and-effect relationship from a research study and when it is not.] Can we conclude that the improved symptoms were caused by the new medication? a. Yes, this is a controlled experiment. Since a higher percent of patients who took the medication had improved symptoms, we can conclude causation. b. Yes, this is a controlled experiment. We can always conclude causation with a controlled experiment. c. No, even though this is a controlled experiment, there was no difference between the treatment and control groups, so we cannot conclude causation. d. No, even though this is a controlled experiment, there might be a confounding factor since the placebo group had improved symptoms too.

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    Chapter 1 Test A 1-7 Chapter 1 Test A - Answer Key 1. B 2. C 3. C 4. D 5. C 6. B 7. C 8. D 9. D 10. A 11. B 12. A 13. B 14. C 15. D 16. D 17. C 18. D 19. A 20. A

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    Chapter 1 Test B 1-1 Chapter 1 Test B - Multiple Choice Section 1.1 (What are Data?) 1. [Objective: Understand data.] Data can be defined as numbers in context . Suppose you are given the following set of numbers: 18, 22, 22, 20, 19, 21 What additional information would allow you to define these numbers as data? a. We need to know where these numbers were collected. b. We need to know who collected these numbers. c. Units of measurement. This could represent the ages of six high school students. d. Units of measurement. This could represent the ages of six college students. Section 1.2 (Classifying and Storing Data) 2. [Objective: Understand methods for coding categorical variables.] According to the following data table, which variable(s) is (are) categorical? Age Gender Shoe Size Ethnicity 18 1 10 1 23 0 7 0 21 0 6 2 19 1 11 1 20 1 10 3 a. Gender b. Gender and ethnicity c. Gender, shoe size, and ethnicity d. None are categorical because there are only numbers in the table 3. [Objective: Distinguish between stacked and unstacked data.] The following data table is organized using which method? Gender Age Male 35 Female 42 Female 33 Male 37 Female 39 a. This is stacked data because the ages are separated by groups (in this case, gender). b. This is stacked data because each row represents one person. c. This is unstacked data because the ages are separated by groups (in this case, gender). d. This is unstacked data because each row represents one person.

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    1-2 Chapter 1 Test B 4. [Objective: Distinguish between numerical and categorical variables.] Determine which of the following five variables are numerical and which are categorical. age, gender, height, favorite candy, eye color a. Age, height, and favorite candy are numerical variables. Gender and ethnicity are categorical variables. b. Age and height are numerical variables. Gender, favorite candy, and eye color are categorical variables. c. All of the variables are categorical. d. All of the variables are numerical. 5. [Objective: Distinguish between a population and a sample.] In a recent high school poll, the principal asked if students were satisfied with the amount of after-school activities offered. What is the population of interest here? a. All students who attend the school. b. All students who participated in the poll. c. All students who are satisfied with the amount of after-school activities that are offered. d. All students who are not satisfied with the amount of after-school activities that are offered. Section 1.3 Organizing Categorical Data 6. [Objective: Understand what types of variables are used in two-way tables.] A two-way table could be used for which of the following pairs of variables? a. Age and height b. Gender and age c. Gender and favorite class d. Age and favorite class 7. [Objective: Find and use rates (including percentages).] In a study of 1350 elementary school children, 118 out of the 615 girls in the study said they want to be a teacher when they grow up. What percent of the study’s participants were boys? a. 19.2% b. 45.6% c. 54.4% d. 83.7% 8. [Objective: Find and use rates (including percentages).] In a study of 1350 elementary school children, 118 out of the 615 girls in the study said they want to be a teacher when they grow up. What percent of girls want to be a teacher when they grow up? a. 8.7% b. 19.2% c. 45.6% d. 80.8%

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    Chapter 1 Test B 1-3 9. [Objective: Find and use rates (including percentages).] According to the following two-way table, what percent of people in the sample take naps? Male Female Naps 25 30 Does not nap 35 10 a. 25% b. 35% c. 55% d. 60% 10. [Objective: Find and use rates (including percentages).] According to the following two-way table, why are percentages more useful than counts to compare the amount of males and females who take naps? Male Female Naps 25 30 Does not nap 35 10 a. There are more males than females in the sample. b. There are more people who take naps than people who do not in the sample. c. You should only use counts in a two-way table. d. You should only use percentages in a two-way table. Section 1.4 Collecting Data to Understand Causality 11. [Objective: Distinguish between observational studies and controlled experiments.] Determine if the following scenario is an observational study or a controlled experiment. A doctor is interested in determining whether a certain medication reduces migraines. She randomly selects 100 people for his study - 50 who will take the medication, and 50 who will take a placebo. The patients are examined once a week for six weeks. a. Observational study b. Controlled experiment c. Neither 12. [Objective: Distinguish between observational studies and controlled experiments.] Determine if the following scenario is an observational study or a controlled experiment. A doctor is interested in determining whether a certain medication reduces migraines. She reviews her patients’ medical records and finds that a higher proportion of people who take the medication have fewer migraines than those who did not take the medication. a. Observational study b. Controlled experiment c. Neither

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    1-4 Chapter 1 Test B 13. [Objective: Understand difference between treatment and outcome variables.] Researchers conducted an experiment to determine if riding a bike to school improves attention span. What are the treatment and outcome variables? a. The treatment variable is riding a bike to school. The outcome variable is whether or not the child rode a bike to school. b. The treatment variable is riding a bike to school. The outcome variable is the child’s attention span. c. The treatment variable is attention span. The outcome variable is whether or not the child rode a bike to school. d. The treatment variable is attention span. The outcome variable is the child’s attention span score. 14. [Objective: Understand when it is possible to infer a cause-and-effect relationship from a research study and when it is not.] Researchers conducted a study and determined that students who carpool have less friends than students who ride the bus to school. Can we conclude that carpooling causes students to have less friends? a. Yes, this is an observational study and we can conclude causation. b. Yes, this is an experiment and we can conclude causation. c. No, this is an observational study and we cannot conclude causation. d. No, this is an experiment and we cannot conclude causation. 15. [Objective: Suggest confounding variables that are likely to occur in some situations.] A gym is offering a new 6-week diet plan for its members. Members who sign up for the program are weighed and measured once a week for the duration of the program. The owners of the gym want to know if the diet plan actually helps people lose weight. What variable could be a possible confounding factor in determining the cause of weight loss? a. The person’s education level. b. The person’s marital status. c. The person’s social life. d. The person’s exercise routine. 16. [Objective: Determine when information is anecdotal.] Coconut oil has become quite popular in recent years. People who use coconut oil claim it helps with hair care, skin care, stress relief, weight loss, and a boosted immune system. Can we conclude that the use of coconut oil causes these health benefits? a. Yes, the claims are anecdotes and give us a good comparison group to find health differences. b. No, the claims are anecdotes and do not give us a true comparison group to find health differences. c. Yes, the claims are true stories, so we do have evidence of the health benefits. d. No, the claims are lies, so we do not have evidence of the health benefits.

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    Chapter 1 Test B 1-5 17. [Objective: Understand different requirements for controlled experiments.] What does it mean for an experiment to be random? a. Assignment into the control and treatment groups is determined by chance. b. Assignment into the control and treatment groups is determined by the researcher. c. Assignment into the control and treatment groups is determined by the participants. d. Assignment into the control and treatment groups is determined by a person who is not involved in the research. Use the following information for questions (18) - (20): A group of 500 patients who suffer from skin cancer were asked to participate in a study to determine the effectiveness of a new medication. The patients were randomly divided into two groups, one that was given the actual medication, and one that received a placebo pill. A good outcome was defined as the cancer being in remission after 6 months of treatment. The results of the study are below. Medication Placebo Remission 160 130 Not in 80 130 18. [Objective: Understand when it is possible to infer a cause-and-effect relationship from a research study and when it is not.] Approximately what percent of patients who took the medication had cancer remission? a. 48% b. 50% c. 58% d. 67% 19. [Objective: Understand when it is possible to infer a cause-and-effect relationship from a research study and when it is not.] Was the new medication effective for cancer remission? a. Yes, a higher percent of patients who took the medication had cancer remissions than the patients who took the placebo. b. Yes, both groups had more patients with cancer remissions. c. No, the patients who took the placebo also had cancer remissions. d. No, this was not a controlled experiment.

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    1-6 Chapter 1 Test B 20. [Objective: Understand when it is possible to infer a cause-and-effect relationship from a research study and when it is not.] Can we conclude that the cancer remissions were caused by the new medication? a. Yes, this is a controlled experiment. Since a higher percent of patients who took the medication had cancer remissions, we can conclude causation. b. Yes, this is a controlled experiment. We can always conclude causation with a controlled experiment. c. No, even though this is a controlled experiment, there was no difference between the treatment and control groups, so we cannot conclude causation. d. No, even though this is a controlled experiment, there might be a confounding factor since the placebo group had cancer remissions too.

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    Chapter 1 Test B 1-7 Chapter 1 Test B - Answer Key 1. D 2. B 3. B 4. B 5. A 6. C 7. C 8. B 9. C 10. A 11. B 12. A 13. B 14. C 15. D 16. B 17. A 18. D 19. A 20. A

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    Chapter 1 Test C 1-1 Chapter 1 Test C - Short Answer Section 1.1 (What are Data?) 1. [Objective: Understand data.] Give an example of how data could be collected about you on a daily basis. Section 1.2 (Classifying and Storing Data) 2. [Objective: Understand methods for coding categorical variables.] In the following table, gender is a categorical variable. Give one possible way the variable could have been coded. Age Gender Shoe Size 18 1 10 23 0 7 21 0 6 19 1 11 20 1 10 3. [Objective: Distinguish between stacked and unstacked data.] Determine whether the following data table is stacked or unstacked and explain your reasoning. Age School Year 18 Freshman 20 Sophomore 19 Sophomore 21 Junior 21 Senior 4. [Objective: Distinguish between numerical and categorical variables.] Give an example of one categorical variable and one numerical variable. 5. [Objective: Distinguish between a population and a sample.] In a recent survey at UCLA, some incoming freshmen students were asked if they planned to take more than one math class before they graduated. What is the population of interest here and what is the sample? Section 1.3 (Organizing Categorical Data) 6. [Objective: Understand what types of variables are used in two-way tables.] What types of variables are represented in a two-way table? Give an example. 7. [Objective: Find and use rates (including percentages).] In a recent study of 1200 adult smokers, 125 out of the 560 males in the study said they were interested in joining a help group to quit smoking. What percent of the study’s participants were female?

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    1-2 Chapter 1 Test C 8. [Objective: Find and use rates (including percentages).] In a recent study of 1200 adult smokers, 125 out of the 560 males in the study said they were interested in joining a help group to quit smoking. What percent of males are interested in joining this group? 9. [Objective: Find and use rates (including percentages).] According to the following two-way table, what percent of people in the sample eat breakfast? Male Female Eat breakfast 35 40 Skips breakfast 20 5 10. [Objective: Find and use rates (including percentages).] According to the following two-way table, why are percentages more useful than counts to compare the amount of males and females who eat breakfast? Male Female Eat breakfast 35 40 Skips breakfast 20 5 Section 1.4 (Collecting Data to Understand Causality) 11. [Objective: Distinguish between observational studies and controlled experiments.] Determine if the following scenario is an observational study or a controlled experiment and explain your reasoning. A school teacher is interested in determining whether students who take multiple choice tests do better than students who take true/false tests. She has been giving multiple choice tests since she started teaching and is wondering if she should change her testing method. She randomly assigns half of her students to take a multiple choice test about grammar rules, and the other half to take a true/false test about grammar rules. She compares the test scores of the students in each group. 12. [Objective: Distinguish between observational studies and controlled experiments.] Determine if the following scenario is an observational study or a controlled experiment and explain your reasoning. A doctor is interested in determining whether a certain medication is effective at treating abdominal pain. He reviews his patients’ medical records and finds that a higher proportion of people who took the medication fewer abdominal pain symptoms than those who did not take the medication. 13. [Objective: Understand difference between treatment and outcome variables.] Researchers conducted an experiment to determine if having a dog day on college campuses during final exam week lowers students’ stress levels. A dog day is when dogs from a local animal shelter are brought onto campus for students to play and interact with. What are the treatment and outcome variables for this experiment?

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    Chapter 1 Test C 1-3 14. [Objective: Understand when it is possible to infer a cause-and-effect relationship from a research study and when it is not.] Researchers conducted a study and determined that coworkers who socialize outside of work are more productive than coworkers who do not. Can we conclude that socializing outside of work causes coworkers to be more productive? Explain your reasoning. 15. [Objective: Suggest confounding variables that are likely to occur in some situations.] A college is offering a new free tutoring program for students in an introductory statistics class. The school wants to know if this new program improves students’ test scores on their midterms and final exams. What variable could be a possible confounding factor in determining why students’ scores improved or not? 16. [Objective: Determine when information is anecdotal.] Give an example of how anecdotal evidence can be used to persuade consumers to purchase a product. 17. [Objective: Understand different requirements for controlled experiments.] What is the difference between a blind and a double blind study? Which is most ideal? Use the following information for questions (18) - (20): A group of 500 patients who suffer from severe migraines were asked to participate in a study to determine the effectiveness of a new medication. The patients were randomly divided into two groups, one that was given the actual medication, and one that received a placebo pill. A good outcome was defined as a reduction in the number of migraines during a month’s time. The results of the study are below. Medication Placebo Migraines reduced 185 70 Migraines did not 90 155 18. [Objective: Understand when it is possible to infer a cause-and-effect relationship from a research study and when it is not.] Approximately what percent of patients who took the medication had a reduction in the amount of migraines? 19. [Objective: Understand when it is possible to infer a cause-and-effect relationship from a research study and when it is not.] Was the new medication effective for reducing migraines? Explain your reasoning and include any calculations. 20. [Objective: Understand when it is possible to infer a cause-and-effect relationship from a research study and when it is not.] Can we conclude that the reduction of migraines was caused by the new medication? Explain your reasoning.

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    1-4 Chapter 1 Test C Chapter 1 Test C – Answer Key 1. Answers will vary. Examples might include: Facebook postings, Twitter tweets, Instagram photos, emails sent/received, credit/debit card swipes, GPS, text messaging, etc. 2. 2 possible ways to code: 0 - Male, 1 - Female; OR 0 - Female, 1 - Male 3. This is stacked data because each row represents one person. 4. Answers will vary. Examples might include: categorical - gender, favorite candy, year in school, favorite color, etc.; numerical - age, height, weight, speed, etc. 5. The population is the entire freshman class at UCLA. The sample includes the particular freshmen who participated in the survey. 6. Two categorical variables. Answers will vary. Examples might include: gender & favorite color, gender & year in school, year in school & favorite animal, etc. 7. 640 0.533 53.3% 1200   8. 125 0.223 22.3% 560   9. 75 0.75 75% 100   10. The group sizes are different. There are 55 males, but only 45 females. 11. This is a controlled experiment because the students are randomly assigned to the treatment group (true/false test) and the control group (multiple choice test). 12. This is an observational study because the doctor did not randomly assign patients into groups. Instead, he simply looked at medical files. 13. Treatment variable - whether or not a campus had a dog day . Outcome variable - students’ stress levels during final exams. 14. No, this is an observational study and we cannot conclude causation. 15. Answers will vary. Examples might include: a student’s access to other help/tutoring programs, a student’s major on campus (e.g. a mathematics major versus a history major), a student’s study skills prior to the program, etc. 16. Answers will vary. Examples might include: (1) a pregnancy blog references a few individual women’s experiences with cocoa butter lotion and its reduction of stretch marks, (2) a local health store includes quotes from 5 customers on an advertisement that claims coconut oil consumption can reduce stress and improve health, (3) a commercial for skincare products interviews a small group of people that claim the product has cured their acne, etc.

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    Chapter 1 Test C 1-5 17. In a blind study, the participants do not know which group they have been assigned to. For example, in a medical experiment, the patients do not know if they are receiving actual medication or just a placebo. In a double blind study, neither the researchers, nor the participants know which group the participants have been assigned to. A double blind study is better than a blind study. 18. 185 185 0.6727 67.3% 185 90 275     19. Yes, a higher percent of patients who took the medication had fewer migraines ( 185 67.3% 275  ) than the patients who took the placebo ( 70 31.1% 225  ). 20. Yes, this is a controlled experiment. Since a higher percent of patients who took the medication had fewer migraines, we can conclude causation.

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    Chapter 2 Test A 2-1 Chapter 2 Test A - Multiple Choice Section 2.1 (Visualizing Variation in Numerical Data) 1. [Objective: Understand the difference between how observations are recorded in dotplots, histograms, and stemplots.] How are individual observations recorded in a dotplot, a histogram, and a stemplot? a. A dotplot displays the actual values of observations. A histogram displays a dot for every observation. A stemplot uses bars to display intervals of observations. b. A dotplot displays a dot for every observation. A histogram uses bars to display intervals of observations. A stemplot displays the actual values of observations. c. A dotplot displays the actual values of observations. A histogram uses bars to display intervals of observations. A stemplot displays a dot for every observation. d. A dotplot uses bars to display intervals of observations. A histogram displays a dot for every observation. A stemplot displays the actual values of observations. 2. [Objective: Understand the difference between frequencies and relative frequencies.] What is the difference between a histogram and a relative frequency histogram? a. A histogram uses numbers to record how many observations are in a data set, and a relative histogram uses categories. b. A histogram uses categories to record how many observations are in a data set, and a relative histogram uses counts. c. A histogram uses counts to record how many observations are in a data set, and a relative histogram uses proportions. d. A histogram uses proportions to record how many observations are in a data set, and a relative histogram uses counts.

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    2-2 Chapter 2 Test A 3. [Objective: Determine significance of bin width in a histogram.] In the following histogram, what can you conclude about the bin width? a. The bin width is too small. We are given too much detail. b. The bin width is too large. We are given too much detail. c. The bin width is too small. We are hiding details of the distribution. d. The bin width is too large. We are hiding details of the distribution. 4. [Objective: Understand that a distribution of a sample of data can be displayed multiple ways.] Which histogram represents the same data as the dotplot shown below?

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    Chapter 2 Test A 2-3 Section 2.2 (Summarizing Important Features of a Numerical Distribution) 5. [Objective: Know what to pay attention to in distributions of numerical data.] When examining distributions of numerical data, what three components should you look for? a. Symmetry, center, and spread b. Symmetry, skewness, and spread c. Shape, symmetry, and spread d. Shape, center, and spread 6. [Objective: Understand modality in distributions.] Which of the following would likely show a bimodal distribution in a histogram? a. The heights of all students in a high school band. b. The ages of students who attend a 4-year university. c. The number of hours preschoolers plays outside. d. The final exam grades for an introductory statistics course. For questions (7) - (9), match one of the histograms below with its appropriate description. 7. [Objective: Recognize the shape of a distribution.] The distribution of scores on an easy test is displayed in histogram . 8. [Objective: Recognize the shape of a distribution.] The distribution of household income in a large city is displayed in histogram . 9. [Objective: Recognize the shape of a distribution.] The distribution of female heights is displayed in histogram .

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    2-4 Chapter 2 Test A 10. [Objective: Understand how to find typical values from a histogram.] The following histogram represents audience movie ratings (on a scale of 1-100) of 489 movies. What is the typical movie rating given by audiences according to this distribution? a. The typical value is about 40. b. The typical value is about 50. c. The typical value is about 60. d. The typical value is about 70. 11. [Objective: Determine differences in variability.] Order the following histograms from least to most variability. a. (i), (ii), (iii) b. (ii), (i), (iii) c. (ii), (iii), (i) d. (iii), (i), (ii)

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    Chapter 2 Test A 2-5 12. [Objective: Interpreting typical values of bimodal distributions.] What is the typical value for the histogram shown below? a. The typical value is 40 because it is the center of the distribution. b. The typical value is 40 because it is the average of 20 and 60. c. Since the data are bimodal, a typical value cannot be found. d. Since the data are bimodal, there are two typical values - one is about 20 and the other is about 60. Section 2.3 (Visualizing Variation in Categorical Variables) 13. [Objective: Understand differences between bar charts and histograms.] What is the difference between a bar chart and a histogram? a. They can both be used to represent numerical data. b. They can both be used to represent categorical data. c. A bar chart represents numerical data and a histogram represents categorical data. d. A bar chart represents categorical data and a histogram represents numerical data.

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    2-6 Chapter 2 Test A 14. [Objective: Interpreting bar charts.] Which statement below is NOT supported by the following bar chart? a. More females wear sunscreen than males. b. Very few people, in general, always wear sunscreen. c. More males wear sunscreen than females. d. About 50% of males never wear sunscreen. Section 2.4 (Summarizing Categorical Distributions) 15. [Objective: Determine the variability of categorical data from a bar chart.] The bar charts below depict the veteran statuses of Americans, separated by gender. Which bar chart has more variability in veteran status? Why? a. The female bar chart shows more variability because many of the observations fall into one category (“Non-Veteran”). b. The female bar chart shows more variability because there are more observations in the different categories than there are for males. c. The male bar chart shows more variability because many of the observations fall into one category (“Non-Veteran”). d. The male bar chart shows more variability because there are more observations in the different categories than there are for females.

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    Chapter 2 Test A 2-7 16. [Objective: Understand the term mode when describing categorical variables.] What does it mean to find the mode of a bar chart? a. You cannot find a mode for categorical data. Modes are only used with numerical data. b. The mode can be found by finding the bar, or category, with the most observations. c. The mode can be found by adding up the total number of categories. d. The mode can be found by adding up the total number of observations and dividing by the number of categories. Section 2.5 (Interpreting Graphs) Use the following information to answer questions (17) - (18): A large state university conducted a survey among their students and received 300 responses. The survey asked the students to provide the following information: * Age * Year in School (Freshman, Sophomore, Junior, Senior) * Gender * GPA 17. [Objective: Determine appropriate graph based on variable type.] What type of graph would you use to describe the variable Age? a. A histogram because Age is a numerical variable. b. A histogram because Age is a categorical variable. c. A bar chart because Age is a numerical variable. d. A bar chart because Age is a categorical variable. 18. [Objective: Determine appropriate graph based on variable type.] What type of graph would you use to describe the variables Gender and Year in School? a. A side-by-side histogram should be used since these are two numerical variables. b. A side-by-side histogram should be used since these are two categorical variables. c. A side-by-side bar chart should be used since these are two numerical variables. d. A side-by-side bar chart should be used since these are two categorical variables.

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    2-8 Chapter 2 Test A A word cloud was created using the first chapter of Lewis Carroll’s Alice’s Adventures in Wonderland. (Note that filler words such as “the,” “a/an,” and “and” were excluded from the plot.) Use the word cloud to answer questions (19) - (20). 19. [Objective: Interpreting word clouds.] According to the word cloud, what is the most common word in the first chapter of Alice’s Adventures in Wonderland? Why? a. The most common word is “alice” because it is the largest in size. b. The most common word is “alice” because she is a main character in the story. c. The most common word is “marked” because it appears at the top of the cloud. d. The most common word is “garden” because it appears in the middle of the cloud. 20. [Objective: Pitfalls of using word clouds.] What information is NOT explicitly portrayed in the word cloud? a. The words that occur most frequently in the chapter. b. The specific word that occurs most often. c. The number of times each word occurs.

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    Chapter 2 Test A 2-9 Chapter 2 Test A - Answer Key 1. B 2. C 3. A 4. A 5. D 6. A 7. A 8. C 9. B 10. C 11. D 12. D 13. D 14. C 15. D 16. B 17. A 18. D 19. A 20. C

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    Chapter 2 Test B 2-1 Chapter 2 Test B - Multiple Choice Section 2.1 (Visualizing Variation in Numerical Data) 1. [Objective: Determine significance of bin width in a histogram.] In the following histogram, what can you conclude about the bin width? a. The bin width is too small. We are given too much detail. b. The bin width is too large. We are given too much detail. c. The bin width is too small. We are hiding details of the distribution. d. The bin width is too large. We are hiding details of the distribution. 2. [Objective: Understand the difference between frequencies and relative frequencies in a histogram.] The two histograms below display the exact same data. How do the plots differ? a. Histogram (i) uses frequencies to simply count the number of observations at a given value. Histogram (ii) uses relative frequencies to show the proportion of observations at a given value. b. Histogram (i) uses relative frequencies to show the proportion of observations at a given value. Histogram (ii) uses frequencies to simply count the number of observations at a given value. c. Histograms (i) and (ii) are exactly the same; there are no differences between the plots. d. Histograms (i) and (ii) do not display the same data because the values listed on the y -axis do not match.

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    2-2 Chapter 2 Test B 3. [Objective: Understand the difference between how observations are recorded in dotplots and stemplots.] How are individual observations recorded in a dotplot versus a stemplot? a. A dotplot displays the actual values of observations. A stemplot uses bars to display intervals of observations. b. A dotplot displays the actual values of observations. A stemplot displays a dot for every observation. c. A dotplot displays a dot for every observation. A stemplot displays the actual values of observations. d. A dotplot displays a dot for every observation. A stemplot uses bars to display intervals of observations. 4. [Objective: Understand that a distribution of a sample of data can be displayed multiple ways.] Which dotplot represents the same data as the histogram shown below?

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