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Product details:

  • ISBN-10 ‏ : ‎ 0134080211
  • ISBN-13 ‏ : ‎ 978-0134080215
  • Author: Dr. Jim McClave; Dr. Terry Sincich

A Contemporary Classic

Classic, yet contemporary; theoretical, yet applied–McClave & Sincich’s Statistics gives you the best of both worlds. This text offers a trusted, comprehensive introduction to statistics that emphasizes inference and integrates real data throughout. The authors stress the development of statistical thinking, the assessment of credibility, and value of the inferences made from data. This new edition is extensively revised with an eye on clearer, more concise language throughout the text and in the exercises.

Ideal for one- or two-semester courses in introductory statistics, this text assumes a mathematical background of basic algebra. Flexibility is built in for instructors who teach a more advanced course, with optional footnotes about calculus and the underlying theory.

Table Of Contents:

  1. Chapter 1 Statistics, Data, and Statistical Thinking
  2. 1.1 The Science of Statistics
  3. 1.2 Types of Statistical Applications
  4. 1.3 Fundamental Elements of Statistics
  5. 1.4 Types of Data
  6. 1.5 Collecting Data: Sampling and Related Issues
  7. 1.6 The Role of Statistics in Critical Thinking and Ethics
  8. Statistics in Action: Social Media Network Usage—Are You Linked In?
  9. Using Technology: MINITAB: Accessing and Listing Data
  10. Chapter 2 Methods for Describing Sets of Data
  11. 2.1 Describing Qualitative Data
  12. 2.2 Graphical Methods for Describing Quantitative Data
  13. 2.3 Numerical Measures of Central Tendency
  14. 2.4 Numerical Measures of Variability
  15. 2.5 Using the Mean and Standard Deviation to Describe Data
  16. 2.6 Numerical Measures of Relative Standing
  17. 2.7 Methods for Detecting Outliers: Box Plots and z-Scores
  18. 2.8 Graphing Bivariate Relationships (Optional)
  19. 2.9 Distorting the Truth with Descriptive Statistics
  20. Statistics in Action: Body Image Dissatisfaction: Real or Imagined?
  21. Using Technology: MINITAB: Describing Data
  22. TI-83/TI–84 Plus Graphing Calculator: Describing Data
  23. Chapter 3 Probability
  24. 3.1 Events, Sample Spaces, and Probability
  25. 3.2 Unions and Intersections
  26. 3.3 Complementary Events
  27. 3.4 The Additive Rule and Mutually Exclusive Events
  28. 3.5 Conditional Probability
  29. 3.6 The Multiplicative Rule and Independent Events
  30. 3.7 Some Additional Counting Rules (Optional)
  31. Bayes’s Rule (Optional)
  32. Statistics in Action: Lotto Buster! Can You Improve Your Chance of Winning?
  33. Using Technology: TI-83/TI-84 Plus Graphing Calculator: Combinations and Permutations
  34. Chapter 4 Discrete Random Variables
  35. 4.1 Two Types of Random Variables
  36. 4.2 Probability Distributions for Discrete Random Variables
  37. 4.3 Expected Values of Discrete Random Variables
  38. 4.4 The Binomial Random Variable
  39. 4.5 The Poisson Random Variable (Optional)
  40. 4.6 The Hypergeometric Random Variable (Optional)
  41. Statistics in Action: Probability in a Reverse Cocaine Sting: Was Cocaine Really Sold?
  42. Using Technology: MINITAB: Discrete probabilities
  43. TI-83/TI-84 Plus Graphing Calculator: Discrete Random Variables and Probabilities
  44. Chapter 5 Continuous Random Variables
  45. 5.1 Continuous Probability Distributions
  46. 5.2 The Uniform Distribution
  47. 5.3 The Normal Distribution
  48. 5.4 Descriptive Methods for Assessing Normality
  49. 5.5 Approximating a Binomial Distribution with a Normal Distribution (Optional)
  50. 5.6 The Exponential Distribution (Optional)
  51. Statistics in Action: Super Weapons Development—Is the Hit Ratio Optimized?
  52. Using Technology: MINITAB: Continuous Random Variable Probabilities and Normal Probability Plots
  53. TI–83/TI–84 Plus Graphing Calculator: Normal Random Variable and Normal Probability Plots
  54. Chapter 6 Sampling Distributions
  55. 6.1 The Concept of a Sampling Distribution
  56. 6.2 Properties of Sampling Distributions: Unbiasedness and Minimum Variance
  57. 6.3 The Sampling Distribution of x and the Central Limit Theorem
  58. 6.4 The Sampling Distribution of the Sample Proportion
  59. Statistics in Action: The Insomnia Pill: Is It Effective?
  60. Using Technology: MINITAB: Simulating a Sampling Distribution
  61. Chapter 7 Inferences Based on a Single Sample: Estimation with Confidence Intervals
  62. 7.1 Identifying and Estimating the Target Parameter
  63. 7.2 Confidence Interval for a Population Mean: Normal (z) Statistic
  64. 7.3 Confidence Interval for a Population Mean: Student’s t-Statistic
  65. 7.4 Large-Sample Confidence Interval for a Population Proportion
  66. 7.5 Determining the Sample Size
  67. 7.6 Confidence Interval for a Population Variance (Optional)
  68. Statistics in Action: Medicare Fraud Investigations
  69. Using Technology: MINITAB: Confidence Intervals
  70. TI-83/TI-84 Plus Graphing Calculator: Confidence Intervals
  71. Chapter 8 Inferences Based on a Single Sample: Tests of Hypothesis
  72. 8.1 The Elements of a Test of Hypothesis
  73. 8.2 Formulating Hypotheses and Setting Up the Rejection Region
  74. 8.3 Observed Significance Levels:p-Values
  75. 8.4 Test of Hypothesis about a Population Mean: Normal (z) Statistic
  76. 8.5 Test of Hypothesis about a Population Mean: Student’s t-Statistic
  77. 8.6 Large-Sample Test of Hypothesis about a Population Proportion
  78. 8.7 Calculating Type II Error Probabilities: More about β (Optional)
  79. 8.8 Test of Hypothesis about a Population Variance (Optional)

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