Deepen your analytical skills with this beginner-friendly course in real-world statistics. This course will teach you the statistical concepts & techniques you need to conduct rigorous inferential analyses and draw accurate conclusions from data sets.
Examine a case study to learn about Simpson’s Paradox.
Learn about binomial distribution where each observation represents one of two outcomes and derive the probability of a binomial distribution.
Build on conditional probability principles to understand the Bayes rule and derive the Bayes theorem.
Sampling Distributions and Central Limit Theorem
Use normal distributions to compute probabilities and the Z-table to look up the proportions of observations above, below or in between values.
Use critical values to make decisions on whether or not a treatment has changed the value of a population parameter.
T-Tests and A/B Tests
Test the effect of a treatment or compare the difference in means for two groups when we have small sample sizes.
Use logistic regression results to make a prediction about the relationship between categorical dependent variables and predictors.
Course Project: Analyze A/B Test Results
In this project, you will be provided a dataset reflecting data collected from an experiment. You’ll use statistical techniques to answer questions about the data and report your conclusions and recommendations in a report.
Josh Bernhard_color, Sebastian Thrun, Derek Steer, Juno Lee (color), Mike Yi, David Venturi and Sam Nelson