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Part 1 Descriptive statistics: the study of statistics; why study statistics?; descriptive and inferential statistics; measurement; summation sign; frequency distributions and graphing; types of frequency distributions; constructing frequency distributions with class intervals; graphs of frequency distributions; stem-and-leaf displays; how distributions differ; characteristics of distributions; indicators of central tendency; indicators of variability; resistant indicators; populations and samples; a note on calculators and computers; indicators of relative standing; percentiles; changing the properties of scales; standard scores and the normal distribution; regression; linear relationships; regression constants and the regression line; standard error of estimate; correlation; the Pearson product-moment correlation coefficient; properties of the correlation coefficient; sampling factors that change the correlation coefficient; causality and correlation; computational procedures. Part 2 Inferential statistics: sampling, sampling distributions, and probability; methods of sampling; sampling distributions and sampling error; probability and its application to hypothesis testing; estimation; introduction to hypothesis testing - terminology and theory; statistical terminology; hypothesis testing when alpha x is estimated by sigma x; elementary techniques of hypothesis testing; inferences about the difference between means; inferences about correlation coefficients; a comparison of the difference between means and correlation; the interpretation of significance; statistics in the journals; simple analysis of variance; logic of the analysis of variance; computational procedures; comparisons between specific means; size of relationship. Part 3 Special topics: introduction to research design; scientific questions; operationalizing; data collection and data analysis; conclusions and interpretations; the research report; ethical considerations; topics in probability; set theory; simple classical probability; probability of complex events; methods of counting; two-factor analysis of variance; two-factor classification; logic of two-factor analysis of variance; computational procedures; nonparametric techniques; parametric and nonparametric tests; tests on independent samples.