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Introduction to Statistical Modeling in R

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Certification

Introduction to Statistical Modeling in R

This course will bring you up to speed with the most important and powerful statistics methods.

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Description

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Features

This course includes

Duration

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

Skills

Predictive ModellingData ModelingR ProgrammingStatistical Analysis

Learning Goals

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 Content

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Prerequisites/Requirements

Introduction to R
Introduction to the Tidyverse

Instructors

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Daniel Kaplan

DeWitt Wallace Professor at Macalester College

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Course Overview

Hands-On Training, Instructor-Moderated Discussions

Post course interactions

Virtual labs

International faculty

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Course Cover

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