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Introduction to Probability and Data with R
  • Level Foundation
  • Duration 14 hours
  • Course by Duke University
  • Offered by

About

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.

Modules

Course Overview

    • 1 Videos
    • 1 Readings
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1 Videos

  • Introduction to Statistics with R

1 Readings

  • More about Introduction to Probability and Data

Designing Studies

    • 6 Videos
    • 1 Readings
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6 Videos

  • Introduction
  • Data Basics
  • Observational Studies & Experiments
  • Sampling and sources of bias
  • Experimental Design
  • (Spotlight) Random Sample Assignment

1 Readings

  • Lesson Learning Objectives

Strengthen Your Understanding

    • 1 Readings
    • 2 Assignment
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2 Assignment

  • Week 1 Practice Quiz
  • Week 1 Quiz

1 Readings

  • Suggested Readings and Practice

Learning R

    • 2 Readings
    • 1 Assignment
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1 Assignment

  • Week 1 Lab: Introduction to R and RStudio

2 Readings

  • About Lab Choices (Read Before Selection)
  • Week 1 Lab Instructions (RStudio)

Exploring Numerical Data

    • 5 Videos
    • 1 Readings
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5 Videos

  • Visualizing Numerical Data
  • Measures of Center
  • Measures of Spread
  • Robust Statistics
  • Transforming Data

1 Readings

  • Lesson Learning Objectives

Exploring Categorical Data and Introduction to Inference

    • 2 Videos
    • 1 Readings
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2 Videos

  • Exploring Categorical Variables
  • Introduction to Inference

1 Readings

  • Lesson Learning Objectives

Strengthen Your Understanding

    • 1 Readings
    • 2 Assignment
Show info about module content

2 Assignment

  • Week 2 Practice Quiz
  • Week 2 Quiz

1 Readings

  • Suggested Readings and Practice

Learning R

    • 2 Readings
    • 1 Assignment
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1 Assignment

  • Week 2 Lab: Introduction to Data

2 Readings

  • Week 2 Lab Instructions (RStudio)
  • Week 2 Lab Instructions (RStudio Cloud)

Defining Probability

    • 5 Videos
    • 1 Readings
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5 Videos

  • Introduction
  • Disjoint Events + General Addition Rule
  • Independence
  • Probability Examples
  • (Spotlight) Disjoint vs. Independent

1 Readings

  • Lesson Learning Objectives

Conditional Probability

    • 4 Videos
    • 1 Readings
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4 Videos

  • Conditional Probability
  • Probability Trees
  • Bayesian Inference
  • Examples of Bayesian Inference

1 Readings

  • Lesson Learning Objectives

Strengthen Your Understanding

    • 1 Readings
    • 2 Assignment
Show info about module content

2 Assignment

  • Week 3 Practice Quiz
  • Week 3 Quiz

1 Readings

  • Suggested Readings and Practice

Learning R

    • 2 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Week 3 Lab: Probability

2 Readings

  • Week 3 Lab Instructions (RStudio)
  • Week 3 Lab Instructions (RStudio Cloud)

The Normal Distribution

    • 3 Videos
    • 1 Readings
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3 Videos

  • Normal Distribution
  • Evaluating the Normal Distribution
  • Working with the Normal Distribution

1 Readings

  • Lesson Learning Objectives

Binomial Distribution

    • 3 Videos
    • 1 Readings
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3 Videos

  • Binomial Distribution
  • Normal Approximation to Binomial
  • Working with the Binomial Distribution

1 Readings

  • Lesson Learning Objectives

Strengthen Your Understanding

    • 1 Readings
    • 2 Assignment
Show info about module content

2 Assignment

  • Week 4 Practice Quiz
  • Week 4 Quiz

1 Readings

  • Suggested Readings and Practice

Data Analysis Project

    • 1 Readings
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1 Readings

  • Project Instructions, Data Files, and Checklist

Auto Summary

Discover the foundations of data science with "Introduction to Probability and Data with R" on Coursera. Led by expert instructors, this 840-minute course covers sampling, probability theory, Bayes' rule, and exploratory data analysis using R and RStudio. Ideal for beginners, it paves the way for advanced inference and modeling courses. Subscribe to the Starter plan and kickstart your data science journey today!

Mine Çetinkaya-Rundel
Instructor

Mine Çetinkaya-Rundel