Modern Elementary Statistics

John E. Freund / Benjamin M. Perles  
Total pages
November 2013
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This book is intended for use in a first course in Statistics. There is a systematic academic approach in 'Modern Elementary Statistics'. Its emphasis is on introduction to meaningful, well-established statistical techniques. The future would be medical doctor, business executive, scientist, teacher, or other professional specialist must comprehend and be skillful in the application of baisc statistical tools and methodology. The student's knowledge is greatly enhanced by repeated exposure to statistical exercises.


  • Great variety and number of both exercises and examples that have been tested and fine-tuned over many editions.
    • Gives students a lot of opportunity to practice what they have learned.
  • Coverage of p-values (chapters 11-14)
    • Provides students with an alternative technique for performing tests of hypothesis.
  • Emphasis upon stating assumptions rquired for problems of statistical inference.
    • provides students with a section on normal probablity plots.
  • Analysis of Variance (chapter 15): Introduces students to 2 way ANOVA with interactions.
  • Very wide range of applications are represented within the exercises.
    • Provides students with relevant reference to their chosen area of study.
  • Output from different statistical packages (Excel, MINITAB, etc) are represented to expose students to those statistical packages that they may see in later courses or in the workplace. Optional exercises in which statistical packages are to be used are marked with special 'technology' icons.
    • Familiarizes students with a range of statistical packages.
  • Checklist of Key Terms and References concludes each chapter.
    • Provides students' with a valuable pedagogical study aid that faciliates learning.

New to this Edition

  • EXERCISES: Many of the more than 1200 exercises are new or updated. Among the new exercises in this edition, there are essentially two kinds. First, there is the conceptual kind that makes one think rather than devote one's time to procedures and calculations. The second kind serves to check whether a set of data satisfies the conditions required by a particular statistical procedure.
    • An increased emphasis upon conceptual understanding exercises.
  • Computer output throughout (MINITAB and TI) have been updated to reflect recent releases.
  • Sourced data and applications have been updated.
  • Introduction of new mathematical and statistical techniques to reflect current trends in industry.
  • Responding to reviewer and user feedback, the author has clarified, where possible, textual explanations to make it yet more concise and more clear for students in this introductory statistics course.

Table of Contents


Chapter 1: Introduction

1.1   The Growth of Modern Statistics

1.2   Sources of Statistical Data

1.3   The Nature of Statistical Data


Chapter 2: Summarizing Data: Listing and Grouping

2.1   Listing Numerical Data

2.2   Stem-and-Leaf Displays

2.3   Frequency Distribution

2.4   Graphical Presentations

2.5   Summarizing Two-Variable Data


Chapter 3: Summarizing Data: Measures of Location

3.1   Population and Samples

3.2   The Mean

3.3   The Weighted Mean

3.4   The Median

3.5   Other Fractiles

3.6   The Mode

3.7   The Description of Grouped Data

3.8   Technical Note (Summations)


Chapter 4: Summarizing Data: Measures of Variation

4.1   The Range

4.2   The Standard Deviation and the Variance

4.3   Applications of the Standard Deviation

4.4   The Description of Grouped Data

4.5   Some Further Descriptions


Chapter 5: Possibilities and Probabilities

5.1   Counting

5.2   Permutations

5.3   Combinations

5.4   Probability


Chapter 6: Some Rules of Probability

6.1   Samples Spaces and Events

6.2   The Postulates of Probability

6.3   Probabilities and Odds

6.4   Addition Rules

6.5   Conditional Probability

6.6   Multiplication Rules

6.7   Bayes’ Theorem


Chapter 7: Expectations and Decisions

7.1   Mathematical Expectation

7.2   Decision Making

7.3   Statistical Decision Problems


Chapter 8: Probability Distributions

8.1   Random Variables

8.2   Probability Distributions

8.3   The Binomial Distribution

8.4   The Hypergeometric Distribution

8.5   The Poisson Distribution

8.6   The Multinomial Distribution

8.7   The Mean of a Probability Distribution

8.8   The Standard Deviation of a Probability Distribution


Chapter 9: The Normal Distribution

9.1   Continuous Distributions

9.2   The Normal Distribution

9.3   A Check for Normality

9.4   Applications of the Normal Distribution

9.5   The Normal Approximation to the Binomial


Chapter 10: Sampling and Sampling Distributions

10.1 Random Sampling

10.2 Sample Designs

10.3 Systematic Sampling

10.4 Stratified Sampling

10.5 Cluster Sampling

10.6 Sampling Distributions

10.7 The Standard Error of the Mean

10.8 The Central Limit Theorem

10.9 Some Further Considerations

10.10    Technical Note (Simulation)


Chapter 11: Problems of Estimation

11.1 The Estimation of Means

11.2 The Estimation of Means

11.3 The Estimation of Standard Deviations

11.4 The Estimation of Proportions


Chapter 12: Tests of Hypotheses: Means

12.1 Tests of Hypotheses

12.2 Significance Tests

12.3 Tests Concerning Means

12.4 Tests Concerning Means ( unknown)

12.5 Differences Between Means

12.6 Differences Between Means ( unknown)

12.7 Difference Between Means (Paired data)


Chapter 13: Tests of Hypotheses: Standard Deviations

13.1 Tests Concerning Standard Deviations

13.2 Tests Concerning Two Standard Deviations


Chapter 14: Tests of Hypotheses Based on Count Data

14.1 Tests Concerning Proportions

14.2 Tests Concerning Proportions (Large Samples)

14.3 Differences Between Proportions

14.4 The Analysis of r x c Table

14.5 Goodness of Fit


Chapter 15: Analysis of Vari