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Duke University

Statistics with R

Duke University via Coursera Specialization


In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis. You will produce a portfolio of data analysis projects from the Specialization that demonstrates mastery of statistical data analysis from exploratory analysis to inference to modeling, suitable for applying for statistical analysis or data scientist positions.


Course 1: Introduction to Probability and Data with R
- Offered by Duke University. This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. ... Enroll for free.

Course 2: Inferential Statistics
- Offered by Duke University. This course covers commonly used statistical inference methods for numerical and categorical data. You will ... Enroll for free.

Course 3: Linear Regression and Modeling
- Offered by Duke University. This course introduces simple and multiple linear regression models. These models allow you to assess the ... Enroll for free.

Course 4: Bayesian Statistics
- Offered by Duke University. This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated ... Enroll for free.

Course 5: Statistics with R Capstone
- Offered by Duke University. The capstone project will be an analysis using R that answers a specific scientific/business question provided ... Enroll for free.


Taught by

Colin Rundel , David Banks, Merlise A Clyde and Mine Çetinkaya-Rundel


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