R Studio - A Crash Course

The ultimate guide for importing, editing & analyzing real-world data files
What you'll learn
Work fast and accurately with R Studio
Perform essential data editing and analysis skills in R
Screen data files for common issues and correct these if necessary
Create nicely detailed tables for frequencies, descriptives, correlations and more
Create decent bar charts, histogram, scatterplots and more
Requirements
You don't need any prior knowledge. However, minimal statistics (measurement levels, standard deviation, ...) is helpful for some of the lectures.
Description
If you start analyzing real-world data, which steps should you take in which order?And what's a simple but solid way to perform these in R Studio?This course teaches you exactly that with a minimal time investment.We start off with a quick tour through the R Studio interface. Next up, we jump straight into a real-world data file. You'll learn a minimal, step-by-step data screening routine that includesinspecting variable distributions with bar charts and histograms,checking for undesired Chr (string) variables,counting NA (missing) valuesand way more...We'll then walk you through some fundamental data analyses such as frequency tables with frequencies & column percentages,descriptive statistics over all observations & subgroups separately,contingency tables with frequencies and column percentages &Pearson correlations with listwise & pairwise exclusion of missing values.Next up, you'll learn how to import & export various file types into & from R Studio such as .R, .RData, .RDS, Excel, .CSV, .SAV & .PNG.Finally, we'll round off with some extra data editing skills. These include reordering and removing variables (columns) or observations (rows) and counting NA (missing) values within observations. Last but not least, we'll cover computing means and sums over variables with & without NA values.In short, you'll learn exactly what you need for working with real-life data in R Studio. Just do it.Happy coding ;-)
Who this course is for
This course is for professionals who want to thoroughly master practical data analysis in R with a minimal time investment.
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