Stephen D. Short, Ph.D.

FYE 132: Solvable: Scientific Solutions for the Past, Present, and Future

 A quick glance at current affairs can quickly seem bleak with climate change, pandemics, increased prevalence of mental illness, decreased physical health, and denial of science. But, as the renowned scientist Carl Sagan notes, science can serve as a candle in the dark. Past, present and future scientific discoveries can provide us solvable solutions to many of today’s problems. In this course we’ll explore the history of science as a way of understanding the world, review past examples of pivotal scientific discoveries, and apply scientific thinking to many of today’s current issues including improving mental and physical health, addressing climate change, and decreasing science denial.  

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FYE 132: Evolution for Everyone

Now over 150 years old, Charles Darwin’s On the Origin of Species and his accompanying theory of evolution still face substantial criticism and denial from individuals across the western world, but in particular the United States. In this course, we will begin by reviewing the scientific method, the theory of evolution, and natural selection. Next, we will explore how evolutionary theory can be applied across a variety of fields with examples from areas such as medicine, anthropology, and psychology. We will then explore opposition to evolution and the potential costs of dismissing this powerful framework. Finally, students will use their new evolutionary perspective to explore topics of their own interest and share their findings with their peers.

 

PSYC 211: Psychological Statistics

In this course you will learn about the mathematical techniques that are used by researchers to organize, summarize, and interpret the results obtained from their research studies. Collectively, these techniques are called statistics. During the semester you will learn how to conduct different statistical procedures, understand the specific purpose of each procedure serves, and become knowledgeable about what research questions the procedure answers.

 

PSYC 250: Psychological Statistics and Research Methods

PSYC 250 is a special, 6-hour combination of PSYC 211 (Psychological Statistics) and PSYC 220 (Research Methods) in which you take both courses simultaneously. The combination class is taught in an integrated fashion, which means that we will move back-and-forth between texts and topics, and avoid some of the less desirable consequences that occur when the courses are taught separately (e.g., learning about methods of research separately from the data analysis tools for research; repeating basic statistical material in Methods that was learned a semester earlier in Statistics). A unique feature of PSYC 250 is that you will learn how to use SPSS (Statistical Package for the Social Sciences), a software data analysis tool that is used in our lab courses and by many professionals in the field of psychology.

 

PSYC 370: Tests and Measurements

The purpose of this course is to introduce the field of psychological assessment and testing. Throughout the course we will explore the history, roles, issues, and ethics involved in the field of psychological assessment. In particular, we will cover principles of psychometrics and statistics, the applications of assessment in various contexts, including a review of various types of psychological tests and measures. We will cover both theoretical principles involved in the field of testing, as well as an examination of particular tests, such as the WAIS, and MMPI. This course will require that you have some knowledge of statistics and quantitative methods and we will discuss how to psychometrically evaluate tests and measures as you learn how to create your own psychological scales to measure a construct of your interest.

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PSYC  390: Advanced Psychological Statistics

The goal of this course is to solidify your knowledge of introductory statistics by reviewing the material in an applied framework, as well as to introduce you to more advanced methodology popular in psychology and software for data analysis. 

First, we will discuss the core foundations of statistics.  You will learn to use the statistical software R to import and manage data, calculate descriptive statistics, and visualize data by creating plots.  Estimation and prediction are the goals I will focus on in this class, so to segue into our next topic we will discuss probability and estimation in the context of point estimates, standard errors, and confidence intervals (CIs), as well as hypothesis testing topics (z tests, statistical power, and Type I error).

In addition, you will learn about the general and generalized linear models, which are flexible types of algebraic equations that allow us to estimate good descriptions of the data and to make predictions about future data.  We will work with the algebraic equation, plugging in data to generate predicted values, and characterize how those predictions differ from the actual observed data.  From these general models, we will segue into special cases such as multiple regression, analysis of variance (ANOVA), and logistic regression.

Lastly, we will cover more advanced topics—including moderation and mediation analysis, nonparametric statistics, and introduce factor analysis.