Duke University - Introduction to Probability and Data with R
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Introduction to Probability and Data with R at Coursera Overview
Duration | 14 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Introduction to Probability and Data with R at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 1 of 5 in the Statistics with R Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Beginner Level
- Approx. 14 hours to complete
- English Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English, Spanish
Introduction to Probability and Data with R at Coursera Course details
- This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The concepts and techniques in this course will serve as building blocks for the inference and modeling courses in the Specialization.
Introduction to Probability and Data with R at Coursera Curriculum
About Introduction to Probability and Data
Introduction to Statistics with R
More about Introduction to Probability and Data
Introduction
Data Basics
Observational Studies & Experiments
Sampling and sources of bias
Experimental Design
(Spotlight) Random Sample Assignment
Lesson Learning Objectives
Suggested Readings and Practice
Week 1 Practice Quiz
Week 1 Quiz
About Lab Choices (Read Before Selection)
Week 1 Lab Instructions (RStudio)
Week 1 Lab: Introduction to R and RStudio
Exploratory Data Analysis and Introduction to Inference
Visualizing Numerical Data
Measures of Center
Measures of Spread
Robust Statistics
Transforming Data
Exploring Categorical Variables
Introduction to Inference
Lesson Learning Objectives
Lesson Learning Objectives
Suggested Readings and Practice
Week 2 Practice Quiz
Week 2 Quiz
Week 2 Lab Instructions (RStudio)
Week 2 Lab Instructions (RStudio Cloud)
Week 2 Lab: Introduction to Data
Introduction to Probability
Introduction
Disjoint Events + General Addition Rule
Independence
Probability Examples
(Spotlight) Disjoint vs. Independent
Conditional Probability
Probability Trees
Bayesian Inference
Examples of Bayesian Inference
Lesson Learning Objectives
Lesson Learning Objectives
Suggested Readings and Practice
Week 3 Practice Quiz
Week 3 Quiz
Week 3 Lab Instructions (RStudio)
Week 3 Lab Instructions (RStudio Cloud)
Week 3 Lab: Probability
Probability Distributions
Normal Distribution
Evaluating the Normal Distribution
Working with the Normal Distribution
Binomial Distribution
Normal Approximation to Binomial
Working with the Binomial Distribution
Lesson Learning Objectives
Lesson Learning Objectives
Suggested Readings and Practice
Data Analysis Project Example
Week 4 Practice Quiz
Week 4 Quiz
Data Analysis Project
Project Information
Introduction to Probability and Data with R at Coursera Admission Process
Important Dates
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