Duke University

Inferential Statistics

This course is part of Data Analysis with R Specialization

Taught in English

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Course

Gain insight into a topic and learn the fundamentals

4.8

(2,624 reviews)

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93%

Beginner level
No prior experience required
16 hours (approximately)
Flexible schedule
Learn at your own pace

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Assessments

12 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.8

(2,624 reviews)

|

93%

Beginner level
No prior experience required
16 hours (approximately)
Flexible schedule
Learn at your own pace

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This course is part of the Data Analysis with R Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 5 modules in this course

This short module introduces basics about Coursera specializations and courses in general, this specialization: Statistics with R, and this course: Inferential Statistics. Please take several minutes to browse them through. Thanks for joining us in this course!

What's included

2 readings

Welcome to Inferential Statistics! In this course we will discuss Foundations for Inference. Check out the learning objectives, start watching the videos, and finally work on the quiz and the labs of this week. In addition to videos that introduce new concepts, you will also see a few videos that walk you through application examples related to the week's topics. In the first week we will introduce Central Limit Theorem (CLT) and confidence interval.

What's included

7 videos6 readings3 quizzes

Welcome to Week Two! This week we will discuss formal hypothesis testing and relate testing procedures back to estimation via confidence intervals. These topics will be introduced within the context of working with a population mean, however we will also give you a brief peek at what's to come in the next two weeks by discussing how the methods we're learning can be extended to other estimators. We will also discuss crucial considerations like decision errors and statistical vs. practical significance. The labs for this week will illustrate concepts of sampling distributions and confidence levels.

What's included

7 videos5 readings3 quizzes

Welcome to Week Three of the course! This week we will introduce the t-distribution and comparing means as well as a simulation based method for creating a confidence interval: bootstrapping. If you have questions or discussions, please use this week's forum to ask/discuss with peers.

What's included

11 videos5 readings3 quizzes

Welcome to Week Four of our course! In this unit, we’ll discuss inference for categorical data. We use methods introduced this week to answer questions like “What proportion of the American public approves of the job of the Supreme Court is doing?” Also in this week you will use the data set provided to complete and report on a data analysis question. Please read the project instructions to complete this self-assessment.

What's included

11 videos6 readings3 quizzes

Instructor

Instructor ratings
4.8 (286 ratings)
Mine Çetinkaya-Rundel
Duke University
7 Courses385,652 learners

Offered by

Duke University

Recommended if you're interested in Probability and Statistics

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