Full course description

Course Date:

Feb 27 - Apr 3, 2017


5 weeks


7-10 hrs/week


Microsoft Excel, basic math skills

Course Type:





This short course will provide an introductory, hands-on introduction to statistics used in educational research and evaluation. Participants will learn statistical concepts, principles, and procedures by building Excel spreadsheets from scratch in a guided learning approach using very short video-based tutorials. Examples of specific skills to be learned include scales or measurement, measures of central tendency, measures of variability, and the computation of the following: mean, mode, and median, standard deviation, z (standard) scores, Pearson product-moment correlation coefficient (r), dependent t test, and one-way analysis of variance (ANOVA). Read More.

The course is designed primarily for two audiences: 1) educational professionals who would like to be more informed about how to compute basic statistics and how to use them intelligently in their work; and 2) first-year doctoral students who want a short and friendly introduction (or brush up) to basic statistics before taking full graduate-level statistics courses. However, this course would be useful to anyone who wants a good short, hands-on, friendly, introduction to the most fundamental statistical ideas.


By the end of the course, you will know or be able to do the following:

Introduction to Statistics

  • Scales of measurement
  • Measures of Central Tendency: Mean, Median, & Mode
  • The Normal Distribution
  • How to compute a mean using Excel

Descriptive Statistics

  • Measures of variability: Standard deviation
  • Standard (z) scores
  • How to compute the standard deviation using Excel
  • How to compute a z score using Excel

Correlational Statistics

  • The difference between univariate and bivariate distributions
  • The concept of correlation and the difference between positive and negative correlations
  • How to compute a Pearson product-moment correlation coefficient (r) using Excel

Inferential Statistics

  • Hypothesis testing and the null hypothesis
  • Statistical significance
  • Independent and dependent variables
  • How to compute a t-test value for an independent-samples design using Excel
  • How to compute a t-test value for a correlated-samples design (i.e. dependent t test) using Excel
  • Testing for differences between more than two means: The F distribution
  • How to compute an analysis of variance (ANOVA) using Excel

Course is offered by Canvas Network.

Course Instructors

Lloyd P. Rieber

Lloyd P. Rieber, Ph.D.

Professor of Learning, Design, and Technology

Lloyd Rieber is a Professor of Learning, Design, and Technology at the University of Georgia. He is also the immediate-past Director of Innovation in Teaching and Technology for UGA's College of Education. His research focuses on using dynamic visualizations in the design of interactive learning environments, particularly microworlds, simulations, and games. He has designed and programmed numerous web-based and mobile digital learning environments using tools such as ASP, PHP, and LiveCode. He has two iOS native apps in Appleā€™s App Store and one app in the Mac App Store. He has received two outstanding practice awards for his work designing and programming online learning environments from the Division of Design & Development of the Association for Educational Communications and Technology (AECT). He recently received two awards from AECT's Division of Distance Learning for his design of this MOOC. (Note: This course is not affiliated in any way with the University of Georgia.)