Data analysis and interpretation in the behavioral sciences
Zechmeister and Posavac's unique, progressive pedagogical framework presents students with a model of analysis and interpretation called "I-D-E-A". This cutting edge model leads students through the processes of data inspection (I), description (D), estimating (E) confidence in their results, and announcing (A) their findings. Their friendly writing style and systematic approach to statistics involves the student in the topics presented. The authors stress the important first stage of data inspection and also demonstrate how both confidence intervals and effect sizes are complementary to traditional null hypothesis testing. Throughout the book, the authors emphasize the understanding and interpretation of statistics and place less emphasis on computation, acknowledging and encouraging computer-assisted data analysis.Concrete examples at the beginning of each chapter illustrate the kinds of questions and data that will be considered in that section. Having this variety of examples increases the likelihood that a student will relate to at least one of them. Scenarios presented at the beginning of the chapter, which are referred to throughout the chapter so students can see how an example is affected by different stages of analysis and interpretation.
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a z score Analyzing and Interpreting ANOVA answer asked behavioral calculate central tendency chapter column confidence interval correlation data points data set degrees of freedom describe discarded distribution of means effect size effect sizes equal Equation estimate example experiment Figure formula frequency polygon graph grouped frequency distribution happiness height histogram independent variable inspection Katie klinkers levels measures of central median midpoint negatively skewed NHST nondirectional normal curve normal distribution null hypothesis obtained outliers population mean population standard deviation positively skewed predict probability procedure proportion of scores PSAS scores random sample randomly range real limits regression reject the null relationship relative frequency represent sample mean sampling distribution sampling error scale scatterplot shows skewed distribution square root standard error standard normal table statistically significant stem-and-leaf display stem-and-leaf plot stems Table test scores therapy tion transformation Type II error values variance zero