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Season 1 Episode
- Season 1 What Is Statistics
- Season 1 Mathematical Thinking
- Season 1 Mean, Median, and Mode: Measures of Central Tendency
- Season 1 Measures of Spread
- Season 1 Charts Are Like Pasta - Data Visualization Part 1
- Season 1 Plots, Outliers, and Justin Timberlake: Data Visualization Part 2
- Season 1 The Shape of Data: Distributions
- Season 1 Correlation Doesn’t Equal Causation
- Season 1 Controlled Experiments
- Season 1 Sampling Methods and Bias with Surveys
- Season 1 Science Journalism
- Season 1 Henrietta Lacks, the Tuskegee Experiment, and Ethical Data Collection
- Season 1 Probability Part 1: Rules and Patterns
- Season 1 Probability Part 2: Updating Your Beliefs with Bayes
- Season 1 The Binomial Distribution
- Season 1 Geometric Distributions and The Birthday Paradox
- Season 1 Randomness
- Season 1 Z-Scores and Percentiles
- Season 1 The Normal Distribution
- Season 1 Confidence Intervals
- Season 1 How P-Values Help Us Test Hypotheses
- Season 1 P-Value Problems
- Season 1 Playing with Power: P-Values Pt 3
- Season 1 You Know I’m All About that Bayes
- Season 1 Bayes in Science and Everyday Life
- Season 1 Test Statistics
- Season 1 T-Tests: A Matched Pair Made in Heaven
- Season 1 Degrees of Freedom and Effect Sizes
- Season 1 Chi-Square Tests
- Season 1 P-Hacking
- Season 1 The Replication Crisis
- Season 1 Regression
- Season 1 ANOVA
- Season 1 ANOVA Part 2: Dealing with Intersectional Groups
- Season 1 Fitting Models Is like Tetris
- Season 1 Supervised Machine Learning
- Season 1 Unsupervised Machine Learning
- Season 1 Intro to Big Data
- Season 1 Big Data Problems
- Season 1 Statistics in the Courts
- Season 1 Neural Networks
- Season 1 War
- Season 1 When Predictions Fail
- Season 1 When Predictions Succeed
Crash Course Statistics - Season 1 Episode 7 The Shape of Data: Distributions
2.00 13 minutes When collecting data to make observations about the world it usually just isn't possible to collect ALL THE DATA. So instead of asking every single person about student loan debt for instance we take a sample of the population, and then use the shape of our samples to make inferences about the true underlying distribution our data. It turns out we can learn a lot about how something occurs, even if we don't know the underlying process that causes it. Today, we’ll also introduce the normal (or bell) curve and talk about how we can learn some really useful things from a sample's shape - like if an exam was particularly difficult, how often old faithful erupts, or if there are two types of runners that participate in marathons!
