Statistics by CrashCourse

In 44 episodes, Adriene Hill teaches you Statistics! This course is based on the 2018 AP Statistics curriculum and introduces everything from basic descriptive statistics to data collection to hot topics in data analysis like Big Data and neural networks. By the end of the course, you will be able to:

• Identify questions that can be answered using statistics
• Describe patterns, trends, associations, and relationships in data both numerically and graphically
• Justify a conclusion using evidence from data, definitions, or statistical inference
• Apply statistical models to make inferences and predictions from data sets
• Understand how statistics are used broadly in the world and interpret their meaning, like in newspapers or scientific studies

Crash Course Statistics Preview.
What Is Statistics: Crash Course Statistics #1.
Mathematical Thinking: Crash Course Statistics #2.
Mean, Median, and Mode: Measures of Central Tendency: Crash Course Statistics #3.
Measures of Spread: Crash Course Statistics #4.
Charts Are Like Pasta - Data Visualization Part 1: Crash Course Statistics #5.
Plots, Outliers, and Justin Timberlake: Data Visualization Part 2: Crash Course Statistics #6.
The Shape of Data: Distributions: Crash Course Statistics #7.
Correlation Doesn’t Equal Causation: Crash Course Statistics #8.
Controlled Experiments: Crash Course Statistics #9.
Sampling Methods and Bias with Surveys: Crash Course Statistics #10.
Science Journalism: Crash Course Statistics #11.
Henrietta Lacks, the Tuskegee Experiment, and Ethical Data Collection: Crash Course Statistics #12.
Probability Part 1: Rules and Patterns: Crash Course Statistics #13.
Probability Part 2: Updating Your Beliefs with Bayes: Crash Course Statistics #14.
The Binomial Distribution: Crash Course Statistics #15.
Geometric Distributions and The Birthday Paradox: Crash Course Statistics #16.
Randomness: Crash Course Statistics #17.
Z-Scores and Percentiles: Crash Course Statistics #18.
The Normal Distribution: Crash Course Statistics #19.
Confidence Intervals: Crash Course Statistics #20.
How P-Values Help Us Test Hypotheses: Crash Course Statistics #21.
P-Value Problems: Crash Course Statistics #22.
Playing with Power: P-Values Pt 3: Crash Course Statistics #23.
You Know I’m All About that Bayes: Crash Course Statistics #24.
Bayes in Science and Everyday Life: Crash Course Statistics #25.
Test Statistics: Crash Course Statistics #26.
T-Tests: A Matched Pair Made in Heaven: Crash Course Statistics #27.
Degrees of Freedom and Effect Sizes: Crash Course Statistics #28.
Chi-Square Tests: Crash Course Statistics #29.
P-Hacking: Crash Course Statistics #30.
The Replication Crisis: Crash Course Statistics #31.
Regression: Crash Course Statistics #32.
ANOVA: Crash Course Statistics #33.
ANOVA Part 2: Dealing with Intersectional Groups: Crash Course Statistics #34.
Fitting Models Is like Tetris: Crash Course Statistics #35.
Supervised Machine Learning: Crash Course Statistics #36.
Unsupervised Machine Learning: Crash Course Statistics #37.
Intro to Big Data: Crash Course Statistics #38.
Big Data Problems: Crash Course Statistics #39.
Statistics in the Courts: Crash Course Statistics #40.
Neural Networks: Crash Course Statistics #41.
War: Crash Course Statistics #42.
When Predictions Fail: Crash Course Statistics #43.
When Predictions Succeed: Crash Course Statistics #44.