Coursera – Data Analysis and Statistical Inference (2014) [84 mp4]

Coursera – Data Analysis and Statistical Inference (2014) [84 mp4]
English | Size: 1.28 GB (1,376,028,414 bytes )
Category: Tutorial

This course introduces you to the discipline of statistics as a science of understanding and analyzing data. You will learn how to effectively make use of data in the face of uncertainty: how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena.

Instructor: Mine Çetinkaya-Rundel
Released: Sept. 1, 2014

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

Week 4: 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 5: 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 6: 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 7: 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

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