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Introduction to Statistical Modeling in R

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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

Beginner

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

Introduction to Statistical Modeling in R is a multi-part course. It will take you through the most important and powerful methods of statistical modeling in R.

This introduction will cover what statistical modeling is and how it works. It also explains the R tools that can help you build models. We will also talk about prediction and prediction as well as how to account for multiple variables. This course is only for DataCamp users. Machine learning and computing make it possible to skip many of the esoteric or marginal topics covered in traditional regression courses. This intermediate course will get you up to speed with the most important and powerful methods in statistics.

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

Introduction to R

Introduction to the Tidyverse

What You Will Learn

This chapter explores what a statistical model is, R objects which build models, and the basic R notation, called formulas used for models

In this chapter, you'll start building models: specifying what variables models should relate to one another and training models on the available data

You'll also provide new inputs to models to generate the corresponding outputs

You'll use cross validation to compare different models

You'll see how the recursive partitioning model architecture, which has an internal logic for selecting explanatory variables, can be used to explore potentially complex relationships among variables

Course Instructors

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Daniel Kaplan

DeWitt Wallace Professor at Macalester College

Danny is the DeWitt Wallace Professor of Mathematics, Statistics, and Computer Science at Macalester College in Saint Paul, Minnesota. At Macalester, he has developed the introductory sequence in cal...

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