Beginner Statistics

A Hands-on Introduction to Statistics with R

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Andrew Conway

Taught by:

Andrew Conway

Andrew Conway is a Psychology Professor in the Division of Behavioral and Organizational Sciences at Claremont Graduate University in Claremont, California. He has been teaching introduction to statistics for undergraduate students and advanced statistics for graduate students for 20 years, at a variety of institutions, including the University of South Carolina, the University of Illinois in Chicago, and Princeton University.

Course Description

This selection of courses is designed to be a comprehensive yet friendly introduction to fundamental concepts in statistics. The focus is on statistics but you will make use of the statistical programming language R. For those new to R, an introduction to the R programming language is provided.

This course is, quite literally, for everyone. Whether you're new to statistics, need a refresher course, or a relatively advanced researcher or analyst.

Course One: Introduction

Not sure if this is the type of statistics course you’re looking for? Or perhaps not yet familiar with DataCamp’s interactive learning interface? By taking this free module, you can discover it yourself! Via a combination of videos and interactive coding challenges, this introductory module will introduce you to variables, plotting, and summary statistics like the mean and standard deviation. Enjoy learning-by-doing!

Course Two: Student's T-test

If you want to have a solid basic foundation in statistics, it is essential to understand the concepts and theories behind t-tests. This module covers both the intuition and the calculations behind dependent t-tests, independent t-tests and z-scores. Topics such as NHST, p-value and effect size are covered in detail.

Course Three: Analysis of Variance

Analysis of Variance is probably one of the most popular and most common used statistical procedures. In this module, professor Conway will cover the essentials of Analysis of Variance such as one-way between groups ANOVA, post-hoc tests, and repeated measures ANOVA.

Course Four: Repeated Measures Anova

The fourth module focuses on within-groups comparisons and repeated measures design. With the help of a working memory training experiment, one of the main research fields of professor Conway, it will be explained what the pro’s and con’s are of a repeated measure design and how to conduct the calculations in R yourself.