Introduction to Statistics

1. Front Matter

   Pages i-xii

   PDF

2. Introduction: Why Study Statistics?

   • Gottfried E. Noether

   Pages 1-3

3. Organizing and Summarizing Data

   • Gottfried E. Noether

   Pages 5-28

4. Intuitive Inference

   • Gottfried E. Noether

   Pages 29-44

5. Probability

   • Gottfried E. Noether

   Pages 45-64

6. The Normal Distribution

   • Gottfried E. Noether

   Pages 65-85

7. Hypothesis Testing

   • Gottfried E. Noether

   Pages 87-101

8. The Wilcoxon Two-Sample Test

   • Gottfried E. Noether

   Pages 103-127

9. Nonparametric and Parametric Tests

   • Gottfried E. Noether

   Pages 129-142

10. Estimation: The Two-Sample Shift Model

    • Gottfried E. Noether

    Pages 143-163

11. Point Estimates, Confidence Intervals, and Tests of Hypotheses

    • Gottfried E. Noether

    Pages 165-172

12. The One-Sample Problem

    • Gottfried E. Noether

    Pages 173-199

13. The Two-Sample Problem: Paired Observations

    • Gottfried E. Noether

    Pages 201-219

14. The Analysis of Bivariate Data

    • Gottfried E. Noether

    Pages 221-249

15. Least Squares Regression and Correlation

    • Gottfried E. Noether

    Pages 251-271

16. Comparative Experiments:k-Samples

    • Gottfried E. Noether

    Pages 273-294

17. Analysis of Variance

    • Gottfried E. Noether

    Pages 295-301

18. The Analysis of Categorical Data

    • Gottfried E. Noether

    Pages 303-313

19. Chi-Square Tests for Two-Way Classifications

    • Gottfried E. Noether

    Pages 315-334

20. Binomial Probabilities

    • Gottfried E. Noether

    Pages 335-347

The introductory statistics course presents serious pedagogical problems to the instructor. For the great majority of students, the course represents the only formal contact with statistical thinking that he or she will have in college. Students come from many different fields of study, and a large number suffer from math anxiety. Thus, an instructor who is willing to settle for some limited objectives will have a much better chance of success than an instructor who aims for a broad exposure to statistics. Many statisticians agree that the primary objective of the introductory statistics course is to introduce students to variability and uncertainty and how to cope with them when drawing inferences from observed data. Addi­ tionally, the introductory COurse should enable students to handle a limited number of useful statistical techniques. The present text, which is the successor to the author's Introduction to Statistics: A Nonparametric Approach (Houghton Mifflin Company, Boston, 1976), tries to meet these objectives by introducing the student to the ba­ sic ideas of estimation and hypothesis testing early in the course after a rather brief introduction to data organization and some simple ideas about probability. Estimation and hypothesis testing are discussed in terms of the two-sample problem, which is both conceptually simpler and more realistic than the one-sample problem that customarily serves as the basis for the discussion of statistical inference.

• Boxplot
• Fitting
• Minitab
• Normal distribution
• Variance
• analysis of variance
• best fit
• classification
• correlation
• linear regression
• statistics

"The text is well-written and provides some unique approaches ÄwhichÜ will be appreciated by the students."
(Journal of Quality Technology)

• Department of Statistics, University of Connecticut, Storrs, USA

  Gottfried E. Noether

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