Introduction to Data in R

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Free Online Course: Introduction to Data in R provided by DataCamp is a comprehensive online course, which lasts for 4 hours worth of material. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from DataCamp. Introduction to Data in R is taught by Mine Çetinkaya-Rundel.

Overview
  • Learn the language of data, study types, sampling strategies, and experimental design.

    Scientists seek to answer questions using rigorous methods and careful observations. These observations—collected from the likes of field notes, surveys, and experiments—form the backbone of a statistical investigation and are called data. Statistics is the study of how best to collect, analyze, and draw conclusions from data. It is helpful to put statistics in the context of a general process of investigation: 1) identify a question or problem; 2) collect relevant data on the topic; 3) analyze the data; and 4) form a conclusion. In this course, you'll focus on the first two steps of the process.

Syllabus
  • Language of data
    -This chapter introduces terminology of datasets and data frames in R.

    Study types and cautionary tales
    -In this chapter, you will learn about observational studies and experiments, scope of inference, and Simpson's paradox.

    Sampling strategies and experimental design
    -This chapter defines various sampling strategies and their benefits/drawbacks as well as principles of experimental design.

    Case study
    -Apply terminology, principles, and R code learned in the first three chapters of this course to a case study looking at how the physical appearance of instructors impacts their students' course evaluations.