Experimental Design in R

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5

(3)

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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

Only experimental design can make data analysis possible. This is true for any industry, regardless of whether it's tech, health, or business. If you want to collect data, you must design an experiment. This course will cover the fundamentals of experimental design. This course will teach you about factorial and block designs, as well as common statistical tests such as ANOVAs and T-tests. You will also use R data, real-world data such as the CDC NHANES survey or SAT Scores from NY Public Schools. After the course, you will be able to create and analyze your experiments.

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

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Case Studies, Captstone Projects

Skills You Will Gain

Prerequisites/Requirements

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Introduction to the Tidyverse

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Introduction to Statistics in R

What You Will Learn

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In this course you'll learn about basic experimental design, a crucial part of any data analysis

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In this course you will learn about basic experimental design, including block and factorial designs, and commonly used statistical tests, such as the t-tests and ANOVAs

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You will use built-in R data and real world datasets including the CDC NHANES survey, SAT Scores from NY Public Schools, and Lending Club Loan Data

Course Instructors

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kaelen medeiros

Data Scientist

Kaelen is a data scientist and an admin for the R-Ladies Global community. Kaelen received a MS in Biostatistics from Louisiana State University Health Sciences Center, where they worked at the Louis...

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