Designed to help readers avoid "statistics anxiety," this introduction to basic statistics uses simplified language and presents concepts in a logical progression that allows readers to master simple tasks as they build the skills necessary to tackle more complex concepts. Includes, for each concept, Research Scenarios, familiar illustrations of the concept, formulas that define or demonstrate the concept, computational formulas, worked examples, and applications, and limitations of the concept. Incorporates computer examples (SPSS) throughout. Covers frequency distributions and graphical methods; central tendency; variability; the normal curve; sampling theory for hypothesis testing; correlation; prediction and regression; the significance of the difference between means; decision making, power, and effect size; one-way analysis of variance; two-way analysis of variance; and nonparametric statistical tests. For those in the education and the behavioral sciences who need an introduction to statistics.
The Selected Papers of E. S. Pearson
Continuing its proven approach, the Seventh Edition has been updated with new examples, exercises, and content for an even stronger presentation of the material.
This classic text retains its outstanding features and continues to provide students with excellent background in the mathematics of statistics. Extensively revised with three new chapters.
Statistics
Techniques are introduced through examples, showing how statistics has helped to solve major problems in political science, psychology, genetics, medicine, and other fields.
Noted for its integration of real-world data and case studies, this text offers sound coverage of the theoretical aspects of mathematical statistics.
"A high school book written to help students make sense of the world with statistics."--
This Pearson Original edition is published for Macquarie University.
... the student should be able to : • draw a scatter diagram and a line of best fit • distinguish between positive and negative correlation • calculate covariance • calculate Pearson's product moment correlation coefficient calculate ...
The revision of this well-respected text presents a balanced approach of the classical and Bayesian methods and now includes a chapter on simulation (including Markov chain Monte Carlo and the Bootstrap), coverage of residual analysis in ...