You will gain the skills you need to use this flexible and multi-purpose platform for your own research.
By the end of this course you will:
Have a good understanding of how R works
Be able to perform a wide range of data management tasks, with a focus on solving day-to-day conundrums that we all face as social scientists
Have the knowledge and skills to apply an extensive set of data exploratory and visualization techniques
Be able to use R to perform some of the most common statistical techniques used in the social sciences, namely a dimension reduction technique and OLS regression with interactions
You will be introduced to R and RStudio and will learn how R can help you as a social scientist.
You will be introduced to essential R programming terminology and help functions, and gain confidence in setting working directories and using the R workspace. You will also be introduced to an R tool for reproducibility.
You will learn how to prepare your data for analysis, going beyond the basics of data management to employ specific packages that you can use in your own projects.
You will be introduced to data exploration and data visualization tools in R.
You will expand your statistical testing vocabulary by exploring relationships between multiple variables in R using summated scales.
You will learn how to run Ordinary Least Squares regressions in R, one of the most commonly used methods in the social sciences.
You will have a short taster session on accessing big data using R and big data modelling options available in R.
No previous knowledge of R or other statistical software is necessary. However, an understanding of social research methods (such as reliability analysis for summated scales) is important. If you are not entirely familiar with the method, you can still benefit from learning how to implement it in R but the course will not cover the research method itself.
You will need to download and install R and RStudio. The course instructor will guide you through installing R and RStudio.
No, they are either open source or have community (free) versions.
A computer or laptop with the suggested software and a modern browser e.g. Internet Explorer 10+ or the latest versions of Chrome and Firefox.
You will have access to the course for 3 months.
The course is broken down into 6 modules and is designed to be completed sequentially, as each module builds upon the topics covered in the previous one.
All of our courses offer a certificate of completion signed by your instructor. You will be able to download this certificate, from the Learning Platform, when you complete the course.
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