Data Analysis and Statistical Inference

The Data Analytics and Statistical Inference course offered by Duke University via Coursera provides a comprehensive understanding of statistical data analysis using the R programming language. Here are the key aspects of this course:

Course Overview:
- This specialization focuses on mastering data analysis with R.
- Topics covered include basic data visualization, statistical testing and inference, and linear modeling.
Course Details:
- Introduction to Probability and Data with R (Course 1):
  - Learn about sampling, data exploration, probability theory, and Bayes’ rule.
  - Explore exploratory data analysis techniques, summary statistics, and basic data visualization.
- Statistical Inference for Data Science with R (Course 2):
  - Understand frequentist and Bayesian statistical inference.
  - Perform modeling to understand natural phenomena and make data-based decisions.
  - Communicate statistical results effectively without relying on jargon.
- Linear Regression and Modeling with R (Course 3):
  - Dive into linear regression models.
  - Learn about multiple regression, model selection, and diagnostics.
  - Apply regression techniques to real-world data.
Applied Learning Project:
- Build a portfolio of data analysis projects demonstrating mastery of statistical data analysis.
- Showcase your skills for statistical analysis or data scientist positions.

Whether you’re a beginner or looking to enhance your statistical expertise, this specialization provides valuable knowledge for data-driven decision-making. 📊🔍

For more details, you can explore the Data Analysis with R Specialization on Coursera ¹.