Course: Introduction to Statistics
Modules:
Course Welcome, Meet Guenther Walther, Introduction, Pie Chart, Bar Graph, and Histograms, Box-and-Whisker Plot and Scatter Plot, Providing Context is Key for Statistical Analyses, Pitfalls when Visualizing Information, Mean and Median, Percentiles, the Five Number Summary, and Standard Deviation, [EXTRA] Industry Insight: Introduction to Andrew Radin
Introduction, Simple Random Sampling and Stratified Random Sampling, Bias and Chance Error, Observation vs. Experiment, Confounding, and the Placebo Effect, The Logic of Randomized Controlled Experiments, [EXTRA] Industry Insights: Filing a Patent for twoXAR
The Interpretation of Probability, Complement, Equally Likely Outcomes, Addition, and Multiplication, Four Rules Example: How to Deal with "At Least One", Solving Problems by Total Enumeration, Bayes' Rule, Bayesian Analysis, Warner's Randomized Response Model, [EXTRA] Industry Insights: Drug Discovery at twoXAR
The Normal Curve, The Empirical Rule, Standardizing Data and the Standard Normal Curve, Normal Approximation, Computing Percentiles with the Normal Approximation, The Binomial Setting and Binomial Coefficient, The Binomial Formula, Random Variables and Probability Histograms, Normal Approximation to the Binomial; Sampling Without Replacement, [EXTRA] Industry Insights: Opportunities in Life Sciences
Parameter and Statistic, Expected Value and Standard Error, EV and SE of Sum, Percentages, and When Simulating, The Square Root Law, The Sampling Distribution, Three Histograms, The Law of Large Numbers, The Central Limit Theorem, When does the Central Limit Theorem Apply?
Prediction is a Key Task of Statistics, The Correlation Coefficient, Correlation Measures Linear Association, Regression Line and the Method of Least Squares, Regression to the Mean, The Regression Fallacy, Predicting y from x and x from y, Normal Approximation Given x, Residual Plots, Heteroscedasticity, and Transformations, Outliers and Influential Points, [EXTRA] Industry Insights: Challenges to Using Data Science in Medicine
Interpretation of a Confidence Interval, Using the Central Limit Theorem to Find a Confidence Interval, Estimating the Standard Error with the Bootstrap Principle, More About Confidence Intervals
The Idea Behind Testing Hypotheses, Setting Up a Test Statistic, p-values as Measures of Evidence, Distinguishing Coke and Pepsi by Taste, The t-test, Statistical Significance vs. Importance, The Two-Sample z-test, Matched Pairs, [EXTRA] Industry Insights: Hiring Data Science Talent
Using Computer Simulations in Place of Calculations, Using the Law of Large Numbers to Approximate Quantities of Interest, Plug-in Principle, The Parametric Bootstrap and Bootstrap Confidence Intervals, Bootstrapping in Regression
Relationships Between Two Categorical Variables, The Color Proportions of M&Ms, The Chi-Square Test for Homogeneity and Independence
Comparing Several Means, The Idea of Analysis of Variance, Using the F Distribution to Evaluate ANOVA, More on ANOVA, [EXTRA] Industry Insights: Starting Your Career in Data Science
Data Snooping and the Multiple Testing Fallacy, Reproducibility and Replicability, Bonferroni Correction, False Discovery Rate, and Data Splitting, Summary