# Duke University - Inferential Statistics

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## Inferential Statistics at Coursera Overview

 Duration 17 hours Start from Start Now Total fee Free Mode of learning Online Difficulty level Beginner Official Website Explore Free Course Credential Certificate

## Inferential Statistics at Coursera Highlights

• 24% started a new career after completing these courses.
• 17% got a tangible career benefit from this course.
• Earn a certificate from the Duke university upon completion of course.

## Inferential Statistics at Coursera Course details

Skills you will learn
• This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. 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 course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data

## Inferential Statistics at Coursera Curriculum

About the Specialization and the Course

Introduction

Sampling Variability and CLT

CLT (for the mean) examples

Confidence Interval (for a mean)

Accuracy vs. Precision

Required Sample Size for ME

CI (for the mean) examples

Lesson Learning Objectives

Lesson Learning Objectives

Week 1 Suggested Readings and Practice Exercises

Week 1 Lab Instructions (RStudio)

Week 1 Lab Instructions (RStudio Cloud)

Week 1 Practice Quiz

Week 1 Quiz

Week 1 Lab

Inference and Significance

Another Introduction to Inference

Hypothesis Testing (for a mean)

HT (for the mean) examples

Inference for Other Estimators

Decision Errors

Significance vs. Confidence Level

Statistical vs. Practical Significance

Lesson Learning Objectives

Lesson Learning Objectives

Week 2 Suggested Readings and Practice Exercises

Week 2 Lab Instructions (RStudio)

Week 2 Lab Instructions (RStudio Cloud)

Week 2 Practice Quiz

Week 2 Quiz

Week 2 Lab

Inference for Comparing Means

Introduction

t-distribution

Inference for a mean

Inference for comparing two independent means

Inference for comparing two paired means

Power

Comparing more than two means

ANOVA

Conditions for ANOVA

Multiple comparisons

Bootstrapping

Lesson Learning Objectives

Lesson Learning Objectives

Week 3 Suggested Readings and Practice Exercises

Week 3 Lab Instructions (RStudio)

Week 3 Lab Instructions (RStudio Cloud)

Week 3 Practice Quiz

Week 3 Quiz

Week 3 Lab

Inference for Proportions

Introduction

Sampling Variability and CLT for Proportions

Confidence Interval for a Proportion

Hypothesis Test for a Proportion

Estimating the Difference Between Two Proportions

Hypothesis Test for Comparing Two Proportions

Small Sample Proportions

Examples

Comparing Two Small Sample Proportions

Chi-Square GOF Test

The Chi-Square Independence Test

Lesson Learning Objectives

Lesson Learning Objectives

Week 4 Suggested Readings and Practice Exercises

Week 4 Lab Instructions (RStudio)

Week 4 Lab Instructions (RStudio Cloud)

Week 4 Practice Quiz

Week 4 Quiz

Week 4 Lab

Data Analysis Project

Project Information

## Important Dates

May 25, 2024
Course Commencement Date

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