Basic Statistics Lectures Page

Basic Statistics Lectures Page

I retired on January 1, 2022

This page has all the statistics lectures I have done so far. I have no ideas for how many lectures will be recorded, and hence please check back frequently.

The purpose of making these lectures is to help MTU MS and PhD students who are (or may be) doing pedagogical study, user study, or any study that requires a numerical evaluation/assessment component (e.g., visualization, HCI, etc.). Computer science students may only learn basic probability and statistics in their junior or even sophomore years and rarely equipped with the needed knowledge and skills to perform the works mentioned above. This series of video lectures is my offer to help them.

Throughout the years when I was doing visualization research, designing pedagogical visualization tools, and conducting computer science education work, I acquired many important statistical skills which were used in all my papers. In this series of video lectures, I will try my best to put together what I have learned in the past and will learn in the future in a not-so-rigorous way. My point is that students who may need these skills are not researchers in the field of statistics. Instead, they are just users! Consequently, understanding the concepts and being able to use them properly is crucial. Therefore, you will not see proofs; however, you will encounter many real examples and case studies drawn from my own research.

Please do keep in mind that more than a decade ago when I went up for the full professor rank, I was labeled as someone who was a poor teacher and whose research was declining. Yes, this was on my promotion record. As a result, whether you trust my way of teaching in these video lectures and/or my research on statistics related to pedagogical study, user study, etc. is worth your time, is your decision. Anyway, good luck!

The following table shows the current available video lectures. By the way, all of these video lectures are available on YouTube, but the slides in PDF format and datasets in Excel format are available here at MTU’s local site. My YouTube channel is non-commercvial, which means I receive nothing from YouTube. However, a big "like" is very much appreciated.

Thank you!

Course Topics Slides No. of Slides Total Slides Dataset Videos (YouTube)
Descriptive Statistics Intro-1.pdf 103 103 Intro-1-data.xlsx
  1. Lecture 1: Population, Sample, Point Estimation, Mean, Median, Mode, Variance, Skewness, Kurtosis, Quartiles, Outliers, etc.
  2. Lecture 2: Interval Estimation, Confidence Interval (for Mean and Median), the Central Limit Theorem (CLT) and the Anderson-Darling normality test
  3. Lecture 3: Visualization Basics, Visualization Channel Ranking, the Box-Whisker (or Box) plot, etc.