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Inference for Linear Regression in R

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Certification

Inference for Linear Regression in R

This course will show you how to infer using linear model.

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Description

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Features

This course includes

Duration

4 hours
Video Content
4 hours
Level
Intermediate
Instruction Type
Self Paced
Delivery Method
Online
Available on
Mobile, Desktop, Laptop
Accessibility
Limited Access
Language
English
Subtitles
English

Skills

Data ModelingLinear RegressionStatistical AnalysisInferential Statistics

Learning Goals

You will learn how to create interval estimates for the effect size as well as how to determine if the effect is significant
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
In the first chapter, you will understand how and why to perform inferential (instead of descriptive only) analysis on a regression model
In this chapter you will learn about the ideas of the sampling distribution using simulation methods for regression models
In this chapter you will learn about how to use the t-distribution to perform inference in linear regression models
Additionally, you will consider the technical conditions that are important when using linear models to make claims about a larger population

Course Content

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Prerequisites/Requirements

Foundations of Inference
Intermediate Regression in R

Instructors

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Jo Hardin

Professor at Pomona College

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Course Overview

Hands-On Training, Instructor-Moderated Discussions

Post course interactions

Virtual labs

International faculty

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