PSY-716A Statistical Methods

1. Apply basic concepts and methods of univariate descriptive statistics to analyze data, including levels of measurement, z-scores, measures of central tendency and dispersion, types of distributions, and independent and dependent variables.
2. Apply basic concepts and methods of bivariate descriptive statistics to analyze data, including linear relationships, regression models, residuals, and measures such as slope, Y intercept, coefficient of determination, Pearson’s r, eta, gamma, and phi.
3. Utilize univariate and bivariate graphing approaches, including bar charts, histograms, stem and leaf diagrams, pie charts, boxplots, scatterplots, and regression lines.
4. Apply basic concepts of statistical inference to analyze data, including sampling distribution, sampling error, standard error, null, and alternative hypotheses, one and two tailed tests, Type I and Type II error, rejection region, alpha level, level of significance, rejection of null hypothesis, central limit theorem, effect sizes, confidence intervals, general logic of inference, relationship of confidence interval to hypothesis test, and meaning of z, t, F, and chi-square distributions.
5. Discuss theory behind null hypothesis significance testing (NHST) and criticisms of, and alternatives to, this approach.
6. Conduct the following statistical tests: chi-square test, one and two sample t-test (both independent and correlated group designs for two sample t-test), confidence intervals for proportions and means, power analysis, one way analysis of variance (one way ANOVA), bivariate regression and correlation analysis.
7. Describe statistical power and the relationship between power, effect size, sample size, and Type I and II error.