This course is designed to provide a hybrid experience, including both face-to-face and online activities. In this course you will develop a basic understanding of descriptive and inferential statistics. Fundamentals of statistics provide the quantitative tools for decision-making and develop the ability to interpret statistical results in professional literature as well as the media. This course is intended to accommodate every student who needs an introductory statistics course, regardless of the subject in which one plans to major (psychology, business, education, social science, engineering, everyday life). The course will have about 15 lectures and it will take about 60 hours to complete.

Introduces basic statistics used in the social and behavioral sciences. Covers the following topics: Introduction to statistics, frequency distributions, central tendency, variability, z-scores, sampling distributions, hypothesis testing, one-way ANOVA and non-parametric statistics.



This course is designed to provide a hybrid experience, including both face-to-face and online activities. In this course you will develop a basic understanding of descriptive and inferential statistics. Fundamentals of statistics provide the quantitative tools for decision-making and develop the ability to interpret statistical results in professional literature as well as the media. This course is intended to accommodate every student who needs an introductory statistics course, regardless of the subject in which one plans to major (psychology, business, education, social science, engineering, everyday life). The course will have about 15 lectures and it will take about 60 hours to complete.

Introduces basic statistics used in the social and behavioral sciences. Covers the following topics: Introduction to statistics, frequency distributions, central tendency, variability, z-scores, sampling distributions, hypothesis testing, one-way ANOVA and non-parametric statistics.



This course is designed to provide a hybrid experience, including both face-to-face and online activities. In this course you will develop a basic understanding of descriptive and inferential statistics. Fundamentals of statistics provide the quantitative tools for decision-making and develop the ability to interpret statistical results in professional literature as well as the media. This course is intended to accommodate every student who needs an introductory statistics course, regardless of the subject in which one plans to major (psychology, business, education, social science, engineering, everyday life). The course will have about 15 lectures and it will take about 60 hours to complete.

Introduces basic statistics used in the social and behavioral sciences. Covers the following topics: Introduction to statistics, frequency distributions, central tendency, variability, z-scores, sampling distributions, hypothesis testing, one-way ANOVA and non-parametric statistics.


Applying the principles and methods of scientific psychology in the work place. This course will introduce you to the major concepts of and debates surrounding industrial and organizational psychology. Industrial and organizational psychology is the application of psychological research and theory to human interaction (both with other humans and with human factors, or machines and computers) in the workplace. The phrase “industrial and organizational psychology” (sometimes referred to as “I/O”) may be somewhat misleading, as the field deals less with actual organizations and/or industries and more with the people in these areas. As mentioned above, “I/O” is an applied psychological science, which means that it takes research findings and theories that may have originally been used to explain a general phenomenon of human behavior and applies them to human behavior in a specific setting (here, the workplace). Consider, for example, the fact that many jobs require applicants to take a personality test. Psychologists originally developed this test to detect and diagnose abnormal personalities; they are now frequently used to determine whether a given applicant will be a good “fit” for a position or the dynamic of a company’s staff. In this case, we are applying traditional psychology research to the workplace. Or consider the traditional job interview. Everything from the interaction between interviewer and interviewee to the nature of the Q&A can be examined from a psychological standpoint. While these quick examples pertain to only one area of human workplace interaction (the employee selection area), there are a number of additional areas that we will learn about in this course. We will begin by taking a look at how we evaluate jobs and candidates for jobs (employees) before exploring how we evaluate and motivate employees, noting what encourages versus discourages employee job commitment. We will then study leadership and group influences in the workplace and conclude with units on working conditions and humans factors. In addition, performance management and work teams will be discussed. Leadership interaction and the leadership theories are also covered. Note: Because this is an applied psychological science, you should have a strong background in theory and have taken an Introduction to Psychology course prior to taking this course. Retrieve lecture units here.

This course will introduce you to the major statistical techniques in the field of psychology.  Covers the use of large and small samples for statistical inference, linear and multiple regression, time series models and forecasting, nonparametric methods, the chi square test for cell probabilities, and contingency tables.  Statistical packages for the social sciences will be studied in depth.

This course is designed for the applied social science researchers at the advanced undergraduate or beginning graduate level. It is assumed that you have had a one semester course in introductory statistics that covered measures of central tendency, measures of variability, standard scores (z, T, stanines, etc.), correlation, and inferential statistics, including at least the t tests for independent and dependent samples. In unit 1, we review briefly some descriptive statistics, summation notation, and testing for a “significant” difference. This unit is not intended to thoroughly teach this material again, but to refresh your memory.

The emphasis in the course is on conceptual understanding of the statistical techniques, learning how to effectively use statistical software to run the analyses, and learning how to interpret the computer printout that results from such runs. One major statistical package, SPSS (Statistical Package for the Social Sciences), is an integral part of this course. Details on SPSS are given in IBM SPSS Statistics 22.