Statistical Methods in Psychology Graduate Certificate

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Missouri University of Science and Technology Statistical Methods in Psychology Graduate Certificate Offered by the Departments of Psychological Science and Mathematics & Statistics ______Overview This certificate program is designed to provide formalized education in the area of statistics as it is applied to the analysis of psychological data. Students will complete a four course sequence of classes designed to develop basic graduate level skills in psychological data analysis. These courses will develop an understanding of basic graduate level statistical concepts including probability, t-tests, ANOVAs, regression, as well as non-parametric tests. Students will engage in projects which include measure development and refinement procedures.

Graduate Certificate in Psychometrics – Curriculum The following two Psychology courses are required. Psychology 5202 – Applied Psychological Data Analysis Psychology 5201 – Psychometrics

And an additional two from these four:* Statistics 5346 – Regression Analysis Statistics 5353 – Statistical Data Analysis Statistics 5643 – Probability and Statistics Statistics 6344 – Design and Analysis of Experiments

* Students should have a sufficient math background to successfully complete these courses.

Students who do not have all of the prerequisite courses necessary to take a course in the certificate program will be allowed to take “bridge” courses at either the graduate or undergraduate level to prepare for the formal Certificate Courses. Other courses approved by the Program Advisor may be substituted for any of the above listed courses on a case by case basis.

Entrance into the M.S. Graduate Program: The Statistical Methods in Psychology Graduate Certificate Program is open to all persons holding a Bachelors, Masters, or Ph.D. degree and who have the required pre-requisites for the courses offered. Once admitted to the program, the student must take two psychology courses (see above) and an additional two courses from the second group of four statistics courses (see above) . In order to receive a Graduate Certificate, the student must have an average cumulative grade of 3.0 or better in the certificate courses. Students admitted to the Certificate program will have a non-matriculated status as a graduate student; however, if they complete the courses with a grade of B or better in each course they may be admitted to the Missouri S&T M.S. in Industrial-Organizational Psychology or Mathematics and Statistics without taking the GRE. Students must still apply and be accepted following through the application process. Other course and program prerequisites still apply. At the discretion of other graduate programs, these courses may also be transferred as graduate credit to those programs.

Curriculum is subject to change. Updated: 3/16/17

Missouri University of Science & Technology Department of Psychological Science th 136 Humanities- Social Sciences, 500 W 14 St., Rolla, MO 65409-1560 Phone: 573-341-4937 | Email: [email protected] | Web: psych.mst.edu

Missouri University of Science and Technology Statistical Methods in Psychology Graduate Certificate Offered by the Departments of Psychological Science and Mathematics & Statistics ______

Statistical Methods in Psychology Graduate Certificate Courses

Psychology 5201: Psychometrics An examination of statistical methods used to develop and refine measures of human performance, aptitudes, and personality. Topics include reliability and validity, data reduction, measuring inter-relationships among variables (e.g., factor analysis, multiple regression), and testing group differences. Prerequisites: Psych 5202

Psychology 5202: Applied Psychological Data Analysis This course will focus on those statistical methods most useful for advanced research in psychology. We will learn to use R, a powerful, open-source statistical programming platform, and work through examples with psychological data sets including such techniques as correlation, ANOVAs, regression, and chi-squared. . Prerequisites: Graduate Standing

Statistics 5346: Regression Analysis Simple linear regression, multiple regression, regression diagnostics, multicollinearity, measures of influence and leverage, model selection techniques, polynomial models, regression with autocorrelated errors, introduction to non-linear regression. Prerequisites: Math 2222 and one of Stat 3111, 3113, 3115, 3117, or 5643. (Co-listed with Comp Sci 5204).

Statistics 5353: Statistical Data Analysis Introduction to methods for analyzing statistical data from experiments and Introduction to methods for analyzing statistical data from experiments and surveys. Analysis of variance, correlation, introduction to regression techniques, contingency tables, non-parametric techniques and introduction to modern statistical software. Prerequisites: Math 2222 and one of Stat 1115, 3113, 3115 and 3117.

Statistics 5643: Probability and Statistics Introduction to the theory of probability and its applications, sample spaces, random variables, binomial, Poisson, normal distributions, derived distributions, and moment generating functions. Prerequisites: Math 2222

Statistics 6344: Design and Analysis of Experiments Experimental designs and their statistical analysis. Includes completely randomized designs, complete and incomplete blocking designs, factorial and fractional factorial experiments, multiple comparisons, response surface analysis. Prerequisites: One of Stat 5353, Eng Mgt 5715 and one of Stat 3111, 3113, 3115, 3117, 5643; or Stat 5643 and one of Stat 3111, 3113, 3115, 3117.

Curriculum is subject to change. Updated: 3/16/17