hackr.de

Coursera: Data Analysis and Statistical Inference

29. April 2014

Data Analysis and Statistical Inference
Instructor: Mine Çetinkaya-Rundel, Duke University
Zeitraum: Februar – April 2014
Status: habe ich gemacht, inkl. Exams und Zertifikat

Anmerkung: sehr gut gemachter Kurs.

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Course Syllabus

Week 1: Unit 1 – Introduction to data

Part 1 – Designing studies Part 2 – Exploratory data analysis Part 3 – Introduction to inference via simulation

Week 2: Unit 2 – Probability and distributions

Part 1 – Defining probability Part 2 – Conditional probability Part 3 – Normal distribution Part 4 – Binomial distribution

Week 3: Unit 3 – Foundations for inference

Part 1 – Variability in estimates and the Central Limit Theorem Part 2 – Confidence intervals Part 3 – Hypothesis tests

Week 4: Finish up Unit 3 + Midterm

Part 4 – Inference for other estimators Part 5 – Decision errors, significance, and confidence

Week 5: Unit 4 – Inference for numerical variables

Part 1 – Comparing two means Part 2 – Bootstrapping Part 3 – Inference with the t-distribution Part 4 – Comparing three or more means (ANOVA)

Week 6: Unit 5 – Inference for categorical variables

Part 1 – Single proportion Part 2 – Comparing two proportions Part 3 – Inference for proportions via simulation Part 4 – Comparing three or more proportions (Chi-square)

Week 7: Unit 6 – Introduction to linear regression

Part 1 – Relationship between two numerical variables Part 2 – Linear regression with a single predictor Part 3 – Outliers in linear regression Part 4 – Inference for linear regression

Week 8: Unit 7 – Multiple linear regression

Part 1 – Regression with multiple predictors Part 2 – Inference for multiple linear regression Part 3 – Model selection Part 4 – Model diagnostics

Week 9: Review / catch-up week

Bayesian vs. frequentist inference

Week 10: Final exam