Academic Catalog 2018-2019 
    
    Oct 17, 2019  
Academic Catalog 2018-2019 [ARCHIVED CATALOG]

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PSY-716A Statistical Methods

4 semester credits
For our PhD students, this is a pre-requisite for PSY-717 . Course covers basic concepts and measures in descriptive and inferential statistics, including the statistical tests, one and two sample t-tests, one-way ANOVA, bivariate correlation and regression analysis, familiarity with non-parametric alternatives to parametric tests and the chi-square test and related measures of association, power analysis, and effect size and confidence interval analysis.  This course may not be taken as pass/fail. By special arrangement, PhD students can test out of this course via a proctored exam.
Delivery Method: Distance/Electronically Mediated
Grading Default: Letter Only
Learning Outcome(s):  

  1. Understand basic concepts and methods of univariate descriptive statistics, including levels of measurement, z-scores, measures of central tendency and dispersion, types of distributions, independent and dependent variables.
  2. Understand basic concepts and methods of bivariate descriptive statistics, including cross-tabulations, scatterplots, cell and marginal frequencies, linear relationships, regression models, residuals, and measures such as gamma, phi, slope, Y intercept, coefficient of determination, Pearson’s r, and eta.
  3. Be familiar with univariate and bivariate graphing approaches, including bar charts, histograms, stem and leaf diagrams, pie charts, boxplots, scatterplots, regression lines, and bivariate data display with bar charts.
  4. Understand basic concepts of statistical inference, including sampling distribution, sampling error, standard error, null and alternative hypothesis, one and two tailed tests, Type I and Type II error, rejection region, alpha level, level of significance, rejection of null hypothesis, rejection region (critical region), central limit theorem, confidence interval, general logic of inference, relationship of confidence interval to hypothesis test, meaning of Z, t, F and chi-square distributions.
  5. Know the theory behind null hypothesis significance testing (NHST) and criticisms to the theory.
  6. Be able to 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, oneway analysis of variance (oneway ANOVA), bivariate regression and correlation analysis.
  7. Know the meaning of statistical power and the relationship between power, effect size, sample size, and Type I and II error.



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