R for Researchers: Statistics, Graphs and Data Analysis

Learn R from scratch – data handling, statistics, publication-quality graphs, reports and deep learning

Description

A short, practical start in R – built around what research actually asks of you.

Most researchers do not need to become R developers. They need to import a dataset, run the right test, produce a figure a journal will accept, and be able to do it again next month when the data changes. That is what this course covers, in under two focused hours.

You will install R and RStudio, set a working directory, and get to grips with functions and packages. Then into data handling – types, importing, preparing and downloading annual weather data, exporting and manipulating.

The statistics

• Descriptive statistics

• Correlation analysis

• ANOVA

• Student’s t-test

• Multiple linear regression

The figures and reports

• Basic plots in R

• Advanced and animated graphs

• Wind rose plots across different time periods, with a homework exercise using Heathrow station data

• Generating research reports directly from R

There is also an introduction to deep learning in R across two lectures, and a lecture on the errors that most often stop beginners – what they mean and how to fix them.

Before you enrol

No programming experience is needed; R is taught from installation onwards. R and RStudio are free and run on Windows, macOS and Linux. Basic familiarity with statistical concepts helps, but each test is explained as it is used. This is a compact course – it will get you working in R quickly rather than cover every corner of the language.

Taught by Dr. Azad Rasul, Assistant Professor of Remote Sensing, with a PhD in Geography, over 12 years of programming in research, and more than 150,000 students enrolled across his Udemy courses.

Enrol now and run your next analysis in code you can re-run.

Reminder – Rate this 100% off Udemy Course on Udemy that you got for FREEE!!

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