Instructions: Click on the "Statistics Glossary" button in the bottom corner to reveal an alphanumeric index at the top of the page. Selecting a letter in that index will display the appropriate glossary terms to the right. To return to the main table of contents, click on the "Statistics Homepage" button.

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The complete Electronic Statistics Textbook can be downloaded for quick access from your local hard drive. Directions for correctly installing the textbook are also available.

This Electronic Statistics Textbook offers training in the understanding and application of statistics. The material was developed at the StatSoft R&D department based on many years of teaching undergraduate and graduate statistics courses and covers a wide variety of applications, including laboratory research (biomedical, agricultural, etc.), business statistics and forecasting, social science statistics and survey research, data mining, engineering and quality control applications, and many others.

The Electronic Textbook begins with an overview of the relevant elementary (pivotal) concepts and continues with a more in depth exploration of specific areas of statistics, organized by "modules," accessible by buttons, representing classes of analytic techniques. A glossary of statistical terms and a list of references for further study are included.

Proper citation: StatSoft, Inc. (1999). Electronic Statistics Textbook. Tulsa, OK: StatSoft. WEB: http://www.statsoft.com/textbook/stathome.html.

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Elementary Concepts in Statistics

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Overview of Elementary Concepts in Statistics. In this introduction, we will briefly discuss those elementary statistical concepts that provide the necessary foundations for more specialized expertise in any area of statistical data analysis. The selected topics illustrate the basic assumptions of most statistical methods and/or have been demonstrated in research to be necessary components of one's general understanding of the "quantitative nature" of reality (Nisbett, et al., 1987). Because of space limitations, we will focus mostly on the functional aspects of the concepts discussed and the presentation will be very short. Further information on each of those concepts can be found in the Introductory Overview and Examples sections of this manual and in statistical textbooks. Recommended introductory textbooks are: Kachigan (1986), and Runyon and Haber (1976); for a more advanced discussion of elementary theory and assumptions of statistics, see the classic books by Hays (1988), and Kendall and Stuart (1979).

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What are variables? Correlational vs. experimental research Dependent vs. independent variables Measurement scales Relations between variables Why relations between variables are important Two basic features of every relation between variables What is "statistical significance" (p-value) How to determine that a result is "really" significant Statistical significance and the number of analyses performed Strength vs. reliability of a relation between variables Why stronger relations between variables are more significant

Why significance of a relation between variables depends on the size of the sample Example: "Baby boys to baby girls ratio" Why small relations can be proven significant only in large samples Can "no relation" be a significant result? How to measure the magnitude (strength) of relations between variables Common "general format" of most statistical tests How the "level of statistical significance" is calculated Why the "Normal distribution" is important Illustration of how the normal distribution is used in statistical reasoning (induction) Are all test statistics normally distributed? How do we know the consequences of violating the normality assumption?

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