Dr Peggy Kern's Capstone Statistics Series
Welcome to my intro to statistics series! As part of the MAPP (Masters of Applied Positive Psychology) programs, first at UPenn and then at UniMelb, I have taught an introductory statistics course in an online learning format. I enjoy making statistics a bit more interesting and digestible for students who might not like math or are scared of numbers. Building on that, this series is designed to cover an entire semester of introductory material, through bite sized 1015 minute videos. The first set of lectures focuses on descriptive statistics, in which we are describing a set of data, visually and through numbers. The second set of lectures focuses on inferential statistics, in which we use what we know about a sample to make inferences about the larger population. The series touches on important techniques, focusing on conceptual understanding and practical skills.
I am currently in the process of creating the whole series, and will be continually adding these, so check back frequently for updates.
I am currently in the process of creating the whole series, and will be continually adding these, so check back frequently for updates.
Lecture 1: Introduction
Introduction to the series, including what are statistics, a bit of historical background, why you should care.

Lecture 2: Frequencies
Descriptive statistics part 1, focusing on understanding frequencies and frequency distributions.

Lecture 3: Central Tendency
Descriptive statistics part 2, measures of central tendencies  ways of describing the middle of a set of data. Includes means, median, mode, and trimmed mean.

Lecture 4: Spread
Descriptive statistics part 3: describing the spread of the data, including minimum, maximum, range, quartiles, percentiles, and interquartile range.

Lecture 5: Variance
Descriptive statistics part 4: standard deviation and variance.

Lecture 6: Graphing Data
Descriptive statistics part 5: graphing and visualizing data, including histograms and bar charts, box plots, and more.

Lecture 7: Descriptive Summary

Lecture 8: Descriptives in Excel


Descriptive statistics part 6: how descriptive statistics come together and are reported in a paper, informing the methods and results sections.

In progress...

Lecture 9: Descriptives in SPSS 
Lecture 10: ZScores

In progress...

Zscores offer another type of descriptive statistic that move us toward inferential statistics. Introduction to the normal distribution, proportions, Z scores, and standization. See problem set 2 for practice.

Lecture 11: Correlations part 1

Lecture 12: Correlations part 2

Correlations part 1. Introduces the concept of correlation  the relationship between two variables, including the size and direction of such associations.

Correlations part 2. Here we consider how to calculate correlations, drawing on examples from my recent cycling adventures to illustrate. See below for practice problems.

Lecture 13: Sample & populations part 1Samples and populations, part 1. We shift toward inferential statistics, considering sampling decisions  who is included in the sample  and how these choices impact the generalizabilty of results.

Lecture 14: Samples & populations part 2Samples and populations part 2. We examine sampling distributions, and consider how to use data from a sample to approximate population values, with adjustments to our standard deviation and correlation formulas.

Stay tuned  more videos coming soon!!
Practice Problems
In my own learning journey, I have found that I learn statistics best by doing. I will be adding some practice problems corresponding with the material throughout the series. (Download the file and try to complete the problems before looking at the answer sheet.)
Practice Problems #1: Measures of central tendency and spread (lectures 35)
Problems Answer sheet
Practice Problems #2: The Normal distribution and z scores (lecture 10)
Problems Answer sheet
Practice Problems #3: Correlations (lectures 11 & 12)
Problems Answer sheet
Practice Problems #1: Measures of central tendency and spread (lectures 35)
Problems Answer sheet
Practice Problems #2: The Normal distribution and z scores (lecture 10)
Problems Answer sheet
Practice Problems #3: Correlations (lectures 11 & 12)
Problems Answer sheet