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Inference for Linear Regression in R

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$12

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Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

You've already learned the basics about linear modeling and statistical inference. It is now time to combine them. This course will help you understand how different samples can produce different linear models. This course is designed to help you understand the basic population model. The course will teach you how to estimate intervals and calculate the significance of the effect of the estimated linear model. Comparisons will be made between the prediction intervals of the response variable as well as the estimates for the average response. For cleaning up models, you can use ggplot2, dplyr and the broom packages. These three tools are vital in data science.

Course Overview

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Virtual Labs

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International Faculty

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Post Course Interactions

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Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

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Foundations of Inference

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Intermediate Regression in R

What You Will Learn

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You will learn how to create interval estimates for the effect size as well as how to determine if the effect is significant

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Throughout the course, you'll gain more practice with the dplyr and ggplot2 packages, and you will learn about the broom package for tidying models; all three packages are invaluable in data science

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In the first chapter, you will understand how and why to perform inferential (instead of descriptive only) analysis on a regression model

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In this chapter you will learn about the ideas of the sampling distribution using simulation methods for regression models

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In this chapter you will learn about how to use the t-distribution to perform inference in linear regression models

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Additionally, you will consider the technical conditions that are important when using linear models to make claims about a larger population

Course Instructors

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Jo Hardin

Professor at Pomona College

Jo Hardin is a professor of mathematics and statistics at Pomona College. Her statistical research focuses on developing new robust methods for high throughput data. Recently, she has also worked clo...

Course Reviews

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5.0

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Course Cover

$12

$6

49% OFF

Visit Course

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