Chapter 1 Differentiate between a sample and a population. Identify independent and dependent variables. Differentiate between descriptive and inferential statistics. Identify correlational vs. experimental research design. Classify variables by scales of measurement (nominal, ordinal, interval, ratio, continuous, discrete). Chapter 2 Compute and interpret frequency and relative frequency. Apply graphs for different purposes (bar graphs, histograms). Identify various distribution shapes (normal, skewed, multimodal). Interpret percentile. Chapter 3 Compute and interpret measures of central tendency (mean, median, mode). Chapter 4 Compute and interpret measures of variability (range, standard deviation). Chapter 5 Describe the purpose/use of z-scores. Compute a z-score for a single score. Compute a raw score from a given z-score. Identify characteristics of a z-distribution (mean, standard deviation, shape, etc.).

Chapter 6 Interpret basic probabilities. Describe random sampling, sampling error, and probability of error. Identify the region of rejection. Use a critical value to determine statistical significance of a z-score. Apply gambler's fallacy. Chapter 7 Differentiate the need for one-tailed or two-tailed tests. Identify null and alternative hypotheses for z-tests. Interpret significant and nonsignificant z-test results. Differentiate Type I and Type II errors. Report significant and nonsignificant results in the research literature. Describe factors that influence power. Identify assumptions of parametric statistics.