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  1. Preface
  2. 1 Sampling and Data
    1. Introduction
    2. 1.1 Definitions of Statistics, Probability, and Key Terms
    3. 1.2 Data, Sampling, and Variation in Data and Sampling
    4. 1.3 Frequency, Frequency Tables, and Levels of Measurement
    5. 1.4 Experimental Design and Ethics
    6. 1.5 Data Collection Experiment
    7. 1.6 Sampling Experiment
    8. Key Terms
    9. Chapter Review
    10. Practice
    11. Homework
    12. Bringing It Together: Homework
    13. References
    14. Solutions
  3. 2 Descriptive Statistics
    1. Introduction
    2. 2.1 Stem-and-Leaf Graphs (Stemplots), Line Graphs, and Bar Graphs
    3. 2.2 Histograms, Frequency Polygons, and Time Series Graphs
    4. 2.3 Measures of the Location of the Data
    5. 2.4 Box Plots
    6. 2.5 Measures of the Center of the Data
    7. 2.6 Skewness and the Mean, Median, and Mode
    8. 2.7 Measures of the Spread of the Data
    9. 2.8 Descriptive Statistics
    10. Key Terms
    11. Chapter Review
    12. Formula Review
    13. Practice
    14. Homework
    15. Bringing It Together: Homework
    16. References
    17. Solutions
  4. 3 Probability Topics
    1. Introduction
    2. 3.1 Terminology
    3. 3.2 Independent and Mutually Exclusive Events
    4. 3.3 Two Basic Rules of Probability
    5. 3.4 Contingency Tables
    6. 3.5 Tree and Venn Diagrams
    7. 3.6 Probability Topics
    8. Key Terms
    9. Chapter Review
    10. Formula Review
    11. Practice
    12. Bringing It Together: Practice
    13. Homework
    14. Bringing It Together: Homework
    15. References
    16. Solutions
  5. 4 Discrete Random Variables
    1. Introduction
    2. 4.1 Probability Distribution Function (PDF) for a Discrete Random Variable
    3. 4.2 Mean or Expected Value and Standard Deviation
    4. 4.3 Binomial Distribution
    5. 4.4 Geometric Distribution
    6. 4.5 Hypergeometric Distribution
    7. 4.6 Poisson Distribution
    8. 4.7 Discrete Distribution (Playing Card Experiment)
    9. 4.8 Discrete Distribution (Lucky Dice Experiment)
    10. Key Terms
    11. Chapter Review
    12. Formula Review
    13. Practice
    14. Homework
    15. References
    16. Solutions
  6. 5 Continuous Random Variables
    1. Introduction
    2. 5.1 Continuous Probability Functions
    3. 5.2 The Uniform Distribution
    4. 5.3 The Exponential Distribution
    5. 5.4 Continuous Distribution
    6. Key Terms
    7. Chapter Review
    8. Formula Review
    9. Practice
    10. Homework
    11. References
    12. Solutions
  7. 6 The Normal Distribution
    1. Introduction
    2. 6.1 The Standard Normal Distribution
    3. 6.2 Using the Normal Distribution
    4. 6.3 Normal Distribution (Lap Times)
    5. 6.4 Normal Distribution (Pinkie Length)
    6. Key Terms
    7. Chapter Review
    8. Formula Review
    9. Practice
    10. Homework
    11. References
    12. Solutions
  8. 7 The Central Limit Theorem
    1. Introduction
    2. 7.1 The Central Limit Theorem for Sample Means (Averages)
    3. 7.2 The Central Limit Theorem for Sums
    4. 7.3 Using the Central Limit Theorem
    5. 7.4 Central Limit Theorem (Pocket Change)
    6. 7.5 Central Limit Theorem (Cookie Recipes)
    7. Key Terms
    8. Chapter Review
    9. Formula Review
    10. Practice
    11. Homework
    12. References
    13. Solutions
  9. 8 Confidence Intervals
    1. Introduction
    2. 8.1 A Single Population Mean using the Normal Distribution
    3. 8.2 A Single Population Mean using the Student t Distribution
    4. 8.3 A Population Proportion
    5. 8.4 Confidence Interval (Home Costs)
    6. 8.5 Confidence Interval (Place of Birth)
    7. 8.6 Confidence Interval (Women's Heights)
    8. Key Terms
    9. Chapter Review
    10. Formula Review
    11. Practice
    12. Homework
    13. References
    14. Solutions
  10. 9 Hypothesis Testing with One Sample
    1. Introduction
    2. 9.1 Null and Alternative Hypotheses
    3. 9.2 Outcomes and the Type I and Type II Errors
    4. 9.3 Distribution Needed for Hypothesis Testing
    5. 9.4 Rare Events, the Sample, Decision and Conclusion
    6. 9.5 Additional Information and Full Hypothesis Test Examples
    7. 9.6 Hypothesis Testing of a Single Mean and Single Proportion
    8. Key Terms
    9. Chapter Review
    10. Formula Review
    11. Practice
    12. Homework
    13. References
    14. Solutions
  11. 10 Hypothesis Testing with Two Samples
    1. Introduction
    2. 10.1 Two Population Means with Unknown Standard Deviations
    3. 10.2 Two Population Means with Known Standard Deviations
    4. 10.3 Comparing Two Independent Population Proportions
    5. 10.4 Matched or Paired Samples
    6. 10.5 Hypothesis Testing for Two Means and Two Proportions
    7. Key Terms
    8. Chapter Review
    9. Formula Review
    10. Practice
    11. Homework
    12. Bringing It Together: Homework
    13. References
    14. Solutions
  12. 11 The Chi-Square Distribution
    1. Introduction
    2. 11.1 Facts About the Chi-Square Distribution
    3. 11.2 Goodness-of-Fit Test
    4. 11.3 Test of Independence
    5. 11.4 Test for Homogeneity
    6. 11.5 Comparison of the Chi-Square Tests
    7. 11.6 Test of a Single Variance
    8. 11.7 Lab 1: Chi-Square Goodness-of-Fit
    9. 11.8 Lab 2: Chi-Square Test of Independence
    10. Key Terms
    11. Chapter Review
    12. Formula Review
    13. Practice
    14. Homework
    15. Bringing It Together: Homework
    16. References
    17. Solutions
  13. 12 Linear Regression and Correlation
    1. Introduction
    2. 12.1 Linear Equations
    3. 12.2 Scatter Plots
    4. 12.3 The Regression Equation
    5. 12.4 Testing the Significance of the Correlation Coefficient
    6. 12.5 Prediction
    7. 12.6 Outliers
    8. 12.7 Regression (Distance from School)
    9. 12.8 Regression (Textbook Cost)
    10. 12.9 Regression (Fuel Efficiency)
    11. Key Terms
    12. Chapter Review
    13. Formula Review
    14. Practice
    15. Homework
    16. Bringing It Together: Homework
    17. References
    18. Solutions
  14. 13 F Distribution and One-Way ANOVA
    1. Introduction
    2. 13.1 One-Way ANOVA
    3. 13.2 The F Distribution and the F-Ratio
    4. 13.3 Facts About the F Distribution
    5. 13.4 Test of Two Variances
    6. 13.5 Lab: One-Way ANOVA
    7. Key Terms
    8. Chapter Review
    9. Formula Review
    10. Practice
    11. Homework
    12. References
    13. Solutions
  15. A | Review Exercises (Ch 3-13)
  16. B | Practice Tests (1-4) and Final Exams
  17. C | Data Sets
  18. D | Group and Partner Projects
  19. E | Solution Sheets
  20. F | Mathematical Phrases, Symbols, and Formulas
  21. G | Notes for the TI-83, 83+, 84, 84+ Calculators
  22. H | Tables
  23. Index

4.1 Probability Distribution Function (PDF) for a Discrete Random Variable

Use the following information to answer the next five exercises: A company wants to evaluate its attrition rate, in other words, how long new hires stay with the company. Over the years, they have established the following probability distribution.

Let X = the number of years a new hire will stay with the company.

Let P(x) = the probability that a new hire will stay with the company x years.

1.

Complete Table 4.19 using the data provided.

xP(x)
00.12
10.18
20.30
30.15
4
50.10
60.05
Table 4.19
2.

P(x = 4) = _______

3.

P(x ≥ 5) = _______

4.

On average, how long would you expect a new hire to stay with the company?

5.

What does the column “P(x)” sum to?


Use the following information to answer the next six exercises: A baker is deciding how many batches of muffins to make to sell in his bakery. He wants to make enough to sell every one and no fewer. Through observation, the baker has established a probability distribution.

xP(x)
10.15
20.35
30.40
40.10
Table 4.20
6.

Define the random variable X.

7.

What is the probability the baker will sell more than one batch? P(x > 1) = _______

8.

What is the probability the baker will sell exactly one batch? P(x = 1) = _______

9.

On average, how many batches should the baker make?


Use the following information to answer the next four exercises: Ellen has music practice three days a week. She practices for all of the three days 85% of the time, two days 8% of the time, one day 4% of the time, and no days 3% of the time. One week is selected at random.

10.

Define the random variable X.

11.

Construct a probability distribution table for the data.

12.

We know that for a probability distribution function to be discrete, it must have two characteristics. One is that the sum of the probabilities is one. What is the other characteristic?


Use the following information to answer the next five exercises: Javier volunteers in community events each month. He does not do more than five events in a month. He attends exactly five events 35% of the time, four events 25% of the time, three events 20% of the time, two events 10% of the time, one event 5% of the time, and no events 5% of the time.

13.

Define the random variable X.

14.

What values does x take on?

15.

Construct a PDF table.

16.

Find the probability that Javier volunteers for less than three events each month. P(x < 3) = _______

17.

Find the probability that Javier volunteers for at least one event each month. P(x > 0) = _______

4.2 Mean or Expected Value and Standard Deviation

18.

Complete the expected value table.

x P(x) x*P(x)
00.2
10.2
20.4
30.2
Table 4.21
19.

Find the expected value from the expected value table.

x P(x) x*P(x)
20.12(0.1) = 0.2
40.34(0.3) = 1.2
60.46(0.4) = 2.4
80.28(0.2) = 1.6
Table 4.22
20.

Find the standard deviation.

x P(x) x*P(x) (xμ)2P(x)
2 0.1 2(0.1) = 0.2 (2–5.4)2(0.1) = 1.156
4 0.3 4(0.3) = 1.2 (4–5.4)2(0.3) = 0.588
6 0.4 6(0.4) = 2.4 (6–5.4)2(0.4) = 0.144
8 0.2 8(0.2) = 1.6 (8–5.4)2(0.2) = 1.352
Table 4.23
21.

Identify the mistake in the probability distribution table.

x P(x) x*P(x)
10.150.15
20.250.50
30.300.90
40.200.80
50.150.75
Table 4.24
22.

Identify the mistake in the probability distribution table.

x P(x) x*P(x)
10.150.15
20.250.40
30.250.65
40.200.85
50.151
Table 4.25

Use the following information to answer the next five exercises: A physics professor wants to know what percent of physics majors will spend the next several years doing post-graduate research. He has the following probability distribution.

x P(x) x*P(x)
10.35
20.20
30.15
4
50.10
60.05
Table 4.26
23.

Define the random variable X.

24.

Define P(x), or the probability of x.

25.

Find the probability that a physics major will do post-graduate research for four years. P(x = 4) = _______

26.

FInd the probability that a physics major will do post-graduate research for at most three years. P(x ≤ 3) = _______

27.

On average, how many years would you expect a physics major to spend doing post-graduate research?


Use the following information to answer the next seven exercises: A ballet instructor is interested in knowing what percent of each year's class will continue on to the next, so that she can plan what classes to offer. Over the years, she has established the following probability distribution.

  • Let X = the number of years a student will study ballet with the teacher.
  • Let P(x) = the probability that a student will study ballet x years.
28.

Complete Table 4.27 using the data provided.

x P(x) x*P(x)
1 0.10
2 0.05
3 0.10
4
5 0.30
6 0.20
7 0.10
Table 4.27
29.

In words, define the random variable X.

30.

P(x = 4) = _______

31.

P(x < 4) = _______

32.

On average, how many years would you expect a child to study ballet with this teacher?

33.

What does the column "P(x)" sum to and why?

34.

What does the column "x*P(x)" sum to and why?

35.

You are playing a game by drawing a card from a standard deck and replacing it. If the card is a face card, you win $30. If it is not a face card, you pay $2. There are 12 face cards in a deck of 52 cards. What is the expected value of playing the game?

36.

You are playing a game by drawing a card from a standard deck and replacing it. If the card is a face card, you win $30. If it is not a face card, you pay $2. There are 12 face cards in a deck of 52 cards. Should you play the game?

4.3 Binomial Distribution

Use the following information to answer the next eight exercises: The Higher Education Research Institute at UCLA collected data from 203,967 incoming first-time, full-time freshmen from 270 four-year colleges and universities in the U.S. 71.3% of those students replied that, yes, they believe that same-sex couples should have the right to legal marital status. Suppose that you randomly pick eight first-time, full-time freshmen from the survey. You are interested in the number that believes that same sex-couples should have the right to legal marital status.

37.

In words, define the random variable X.

38.

X ~ _____(_____,_____)

39.

What values does the random variable X take on?

40.

Construct the probability distribution function (PDF).

x P(x)
Table 4.28
41.

On average (μ), how many would you expect to answer yes?

42.

What is the standard deviation (σ)?

43.

What is the probability that at most five of the freshmen reply “yes”?

44.

What is the probability that at least two of the freshmen reply “yes”?

4.4 Geometric Distribution

Use the following information to answer the next six exercises: The Higher Education Research Institute at UCLA collected data from 203,967 incoming first-time, full-time freshmen from 270 four-year colleges and universities in the U.S. 71.3% of those students replied that, yes, they believe that same-sex couples should have the right to legal marital status. Suppose that you randomly select freshman from the study until you find one who replies “yes.” You are interested in the number of freshmen you must ask.

45.

In words, define the random variable X.

46.

X ~ _____(_____,_____)

47.

What values does the random variable X take on?

48.

Construct the probability distribution function (PDF). Stop at x = 6.

x P(x)
1
2
3
4
5
6
Table 4.29
49.

On average (μ), how many freshmen would you expect to have to ask until you found one who replies "yes?"

50.

What is the probability that you will need to ask fewer than three freshmen?

4.5 Hypergeometric Distribution

Use the following information to answer the next five exercises: Suppose that a group of statistics students is divided into two groups: business majors and non-business majors. There are 16 business majors in the group and seven non-business majors in the group. A random sample of nine students is taken. We are interested in the number of business majors in the sample.

51.

In words, define the random variable X.

52.

X ~ _____(_____,_____)

53.

What values does X take on?

54.

Find the standard deviation.

55.

On average (μ), how many would you expect to be business majors?

4.6 Poisson Distribution

Use the following information to answer the next six exercises: On average, a clothing store gets 120 customers per day.

56.

Assume the event occurs independently in any given day. Define the random variable X.

57.

What values does X take on?

58.

What is the probability of getting 150 customers in one day?

59.

What is the probability of getting 35 customers in the first four hours? Assume the store is open 12 hours each day.

60.

What is the probability that the store will have more than 12 customers in the first hour?

61.

What is the probability that the store will have fewer than 12 customers in the first two hours?

62.

Which type of distribution can the Poisson model be used to approximate? When would you do this?


Use the following information to answer the next six exercises: On average, eight teens in the U.S. die from motor vehicle injuries per day. As a result, states across the country are debating raising the driving age.

63.

Assume the event occurs independently in any given day. In words, define the random variable X.

64.

X ~ _____(_____,_____)

65.

What values does X take on?

66.

For the given values of the random variable X, fill in the corresponding probabilities.

67.

Is it likely that there will be no teens killed from motor vehicle injuries on any given day in the U.S? Justify your answer numerically.

68.

Is it likely that there will be more than 20 teens killed from motor vehicle injuries on any given day in the U.S.? Justify your answer numerically.

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