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# Statistics for Data Science

Mode via Udacity

### Overview

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.

### Syllabus

• Binomial Distribution
• Learn about binomial distribution where each observation represents one of two outcomes and derive the probability of a binomial distribution.
• Bayes Rule
• 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.
• Hypothesis Testing
• 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.
• Logistic Regression
• 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.

### Taught by

Josh Bernhard_color, Sebastian Thrun, Derek Steer, Juno Lee (color), Mike Yi, David Venturi and Sam Nelson

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