QUANTitative Analysis & Statistics

Playlists

Video counts include those showing how to do things in SPSS or JASP.

Flipped Classroom

1. Numbers and Variables (9)
2. Statistics Software (7)
3. Frequency (10)
4. Statistical Graphing (15)
5. Measures of Central Tendency (Mean, Median, Mode) (10)
6. Measures of Variability (11)
7. Sampling, Probability, & Inference (10)
8. Statistical Hypothesis Testing (NHST) (12)
9. Using z Scores and the z Test in Statistics (9)
10. One Sample t Tests (9)
11. Independent Sample t Tests and Paired t Tests (11)
12. One-Way ANOVA (8)
13. Correlation (9)
14. Linear Regression (7)
15. Chi-Square & Non-Parametric Alternatives (10)

Basic Business Statistics (QBA 237)

1. From Numbers to Variables to Data (5)
2. Forming Variables for Statistics & Statistical Software (4)
3. Describing Data with Descriptive Statistics (15)
4. Data Visualization for Variables (12)
5. Central Tendency and Variability (16)
6. Depicting Distributions from Boxplots to z-Scores (14)
7. Correlation And Regression (7)
8. Basic Probability (14)
9. Discrete Probability Distributions (10)
10. Continuous Probability Distributions (6)
11. Sampling And Populations (5)
12. Sampling Distributions (9)
13. Estimating Intervals, Point Estimators, and Confidence Intervals (10)
14. Hypothesis Testing and Research Designs Introduction (12)
15. Single-Sample Hypothesis Tests (z, t, p) (6)
16. Assumptions, Significance,& Effect Size Wrap-Up (11)

Other Videos

• Levels of Measurement with Puppies ~6 min
• NUMBERS Can Do Three Jobs - Levels of Measurement NOIR ~17 min
• Comparison of ANOVA and Linear Regression in SPSS ~10.5 min
• Can We COMPARE Significance? A Tale of Two Studies ~10 min
• Business Statistics Lectures (FA2020, QBA337 @ MSU) - 22 videos, uses JASP

Particularly good for Regression / GLM , or anybody wanting really slow. His background is Business, including Accounting and Finance, and even has some Time Series. He starts each video with a positive message that you can learn this!

• His Website with downloads as well

Playlists

• 01. Data and Statistics (1)
• 02. Descriptive Statistics I (10)
• 03. Descriptive Statistics II (8)
• 04. Introduction to Probability (14)
• 05. Discrete Probability Distributions (13)
• 06. Continuous Probability Distributions (5)
• 07. Sampling and Sampling Distributions (6)
• 08. Confidence Interval Estimation (4)
• 09. Hypothesis Testing (14)
• 10. Z-tests and T-tests for Two Populations (3)
• 11. Inferences about Population Variances (5)
• 12. Goodness of Fit and Independence Tests (3)
• 13. ANOVA (ANalysis Of VAriance) (10)
• 14. Simple Linear Regression (12)
• 15. Multiple Linear Regression (17)
• 16. Logistic Regression (6)
• 17. ANCOVA (ANalysis of COVAriance) (3)
• 18. Nonlinear Regression (4)
• 19. Nonparametric Methods (9)
• 20. Model Building and the General Linear Model (GLM) (7)
• 21. Variable Transformations (6)

• Statistics 101. Regression for Beginners Problem Walkthrough Videos (13)
• Statistics 101. Saturday Chat LIVE (65)
• Statistics TL;DR 🔊 Audiocasts. Quick Topic Overviews (13)
• Introduction to Statistical Learning TL;DR 🔊 Audiocasts. Quick Topic Overviews (13)

• Time Series PL01. The Very Basics (6)
• Time Series PL02. Forecast Accuracy (6)
• Time Series PL03. Moving Averages, Trends, and Smoothing (6)

Each unit has a video with transcript, and downloadable (pdf) Student and Faculty guides.

• 1 What Is Statistics?

Univariate Statistics

• 2 Stemplots
• 3 Histograms
• 4 Measures of Center
• 5 Boxplots
• 6 Standard Deviation
• 7 Normal Curves
• 8 Normal Calculations
• 9 Checking Assumption of Normality

Bivariate Relationships

• 10 Scatterplots
• 11 Fitting Lines to Data
• 12 Correlation
• 13 Two-Way Tables

Methodology

• 14 The Question of Causation
• 15 Designing Experiments
• 16 Census and Sampling
• 17 Sample and Surveys

Probability

• 18 Introduction to Probability
• 19 Probability Models
• 20 Random Variables
• 21 Binomial Distributions
• 22 Sampling Distributions
• 23 Control Charts

Statistical Inference

• 24 Confidence Intervals
• 25 Tests of Significance
• 26 Small Sample Inference for One Mean
• 27 Comparing Two Means
• 28 Inference for Proportions
• 29 Inference for Two-Way Tables
• 30 Inference for Regression
• 31 One-Way ANOVA

Conclusion

• 32 Summary

Appendices

• 33 Glossary
• 34 Interactive: Stemplots
• 35 Interactive: Wafer Thickness
• 36 Interactive: Control Chart

Based on the AP Statistics Curriculum

• 1. What Is Statistics
• 2. Mathematical Thinking

Descriptive Statistics

• 3. Mean, Median, and Mode: Measures of Central Tendency
• 4. Measures of Spread
• 5. Charts Are Like Pasta - Data Visualization Part 1
• 6. Plots, Outliers, and Justin Timberlake: Data Visualization Part 2
• 7. The Shape of Data: Distributions

Methodology

• 8. Correlation Doesn't Equal Causation
• 9. Controlled Experiments
• 10. Sampling Methods and Bias with Surveys
• 11. Science Journalism
• 12. Henrietta Lacks, the Tuskegee Experiment, and Ethical Data Collection

Probability

• 13. Probability Part 1: Rules and Patterns
• 14. Probability Part 2: Updating Your Beliefs with Bayes
• 15. The Binomial Distribution
• 16. Geometric Distributions and The Birthday Paradox

Statistical Inference

• 17. Randomness
• 18. Z-Scores and Percentiles
• 19. The Normal Distribution
• 20. Confidence Intervals
• 21. How P-Values Help Us Test Hypotheses
• 22. P-Value Problems
• 23. Playing with Power: P-Values Pt 3

Bayesan Statistics

• 24. You Know I'm All About that Bayes
• 25. Bayes in Science and Everyday Life

Hypothesis Tests

• 26. Test Statistics
• 27. T-Tests: A Matched Pair Made in Heaven
• 28. Degrees of Freedom and Effect Sizes
• 29. Chi-Square Tests
• 30. P-Hacking
• 31. The Replication Crisis
• 32. Regression
• 33. ANOVA
• 34. ANOVA Part 2: Dealing with Intersectional Groups
• 35. Fitting Models Is like Tetris

Other Topics

• 36. Supervised Machine Learning
• 37. Unsupervised Machine Learning
• 38. Intro to Big Data
• 39. Big Data Problems

Applied Statistics

• 40. Statistics in the Courts
• 41. Neural Networks
• 42. War
• 43. When Predictions Fail
• 44. When Predictions Succeed

Study Hall: Data Literacy

Crash Course & Arizona State University

• 1. What are Data and Data Literacy
• 2. Misconceptions in Data Analysis
• 3. Visualizing Data
• 4. How to Collect Data
• 5. Data in the News
• 6. Data in Sports
• 7. Election Data
• 8. Health Data
• 9. Social Media Data
• 10. Data Privacy
• 11. Securing Data
• 12. Credible Research
• 13. Data Mistakes
• 14. Data Context - Why It Matters
• 15. Finding Your Own Data

Videos targeted to high school, early college, and adult learners using friendly examples and graphics. This is only a small collection of some of the most relevant videos. See the link above for many more videos, including probability and examples using Excel.

• Descriptive Statistics
  • Types of Data: Nominal, Ordinal, Interval/Ratio ~6.5 min / Practice ~4.5 min
  • Summary statistics: Mean, Median, Mode ~5 min
  • Standard deviation and measures of spread ~5 min
  • Statistical Graphs ~6 min
  • The Normal Distribution ~8 min / The Central Limit Theorem ~7 min
• Statistical Inference
  • Statistical Inference ~7 min / Evidence ~3.5 min
  • Confidence Intervals ~ 4 min / quiz ~6 min /  Confidence levels ~4 min
  • Sampling error and variation ~6.5 min / Illustration with Box-plots ~6 min / Comparing two samples ~7.5 min
  • P-values ~5 min / quiz ~6.5 min /  calculations ~6.5 min / Statistical Significance ~3.5 min
  • Type 1 and Type 2 errors ~4 min
• Statistical Testing
  • Hypothesis testing: step-by-step, p-value, t-test for difference of two means ~8 min
  • Paired samples and independent samples ~5 min
  • Statistical Tests: Choosing ~10 min / practice ~10 min
  • Multiple Regression - Interpreting coefficients ~8 min / Predictions ~10 min / Dummy variables ~8 min
• Methodology
  • Experiments ~8.5 min
  • Time Series Analysis ~3 min
• Creating Surveys
  • Designing a Questionnaire or Survey (~5.5 min) - 5 steps
    • Define the problem, plan how it will be administered, write the questionnaire, desk check, pilot survey.
  • Writing Good Survey Questions (~3.5 min)
    • Open-Ended vs Closed-Ended Questions. Easy to answer, Short, Correct Spelling and Grammar, Appropriate language, Specific, Realistic, Define your terms, One idea, Positive if possible, No double negative, Alternatives, Avoid overlap, Provide all alternatives, Avoid bias, Neutral questions, Pilot test

The videos are grouped by label, but not in playlists. Here are the categories:  

• 1. Descriptive Statistics (1.1-1.7) 2-8 min each
  • The Five Number Summary, Boxplots, and Outliers (1.6) ~5.5 min
• 2. Correlation & Regression (2.1-2.4) 3-8 min each
• 3. Research Methods (3.1-4.2) - 2-7 min each
• 5. Normal Distributions (5.1-5.3) - 7-10 min each
  • Density Curves and their Properties (5.1),
  • The Normal Distribution and the 68-95-99.7 Rule (5.2),
  • Z-Scores, Standardization, and the Standard Normal Distribution  (5.3)
• 7. Sampling Distributions  (7.2) ~11 min

A medium collection of videos on specific confusing terms both basic and advanced (his favorites). Includes both the basics as well as concepts needed by graduate-level students. Prefers to avoid math, but does teach the understanding of formulas where relevant. Uses the chapters function in YouTube to allow you to skip straight to the parts you need.

• No Math
  • Statistics (~30 min + bonus) - How sampling and hypothesis testing all fit together.
  • Hypothesis Testing (~13 min) - An introduction with no math.
  • Regression Assumptions (~47 min) - bonus videos on Heteroskedasticity, Multi-collinearity, and Autocorrelation.
  • p-values (~26 min) - First ~9 min is intuitive explanation. The rest covers history, 1 vs 2-tailed, and reporting.
• General Explainers of Formulas and Calculations
  • Hypothesis testing (~70 min) - explains all the formulas,
  • Regression (~40 min) - Just Simple, explains SSR, SSE, SST, R2, df, etc.
  • Regression Output (~33 min) -> explains what everything means. Includes a recap of regression basics
• Playlists
  • Descriptive Statistics - 13 videos, usually 10-15 min. Terminology about one variable (e.g., Median, Skewness)
  • Hypothesis Testing - 15-40 min on advanced topics (e.g., Wald Test, Log Likelihood)
  • Regression - 3 additional advanced  videos: Logarithms, Categorical X variables, Interactions, and Logit Models.
  • Health Stats IQ  - 6 videos 15-25 min each

 ... Clearly Explained!!!

• The Normal Distribution (~5 min) and Histograms (~4 min)
• Central Limit Theorem (~8 min) and Sampling (~4 min)
• Confidence Intervals (~7 min) and Population Parameters (~15 min)
• Standard Error (~12 min) and Standard Deviation vs Standard Error (~3 min)
• Null Hypothesis (~15 min) and Alternative Hypotheses (~10 min)
• p-values (~12 min) and One or Two Tailed P-Values (~7 min)
• Statistical Power (~8 min) and Power Analysis (~17 min)
• Linear Regression (~27.5 min) and R-squared (~11 min)
• Multiple Regression (~5.5 min)
• and more

Playlists

• Statistics Fundamentals (60)
• Linear Regression and Linear Models (10)
• Logistic Regression (7)
• Statistics and Machine Learning in R (9)
• Classification and Regression Trees (5)
• Random Forests (3)
• and more