This introductory tutorial guides viewers through the foundational steps of performing data analysis using R and RStudio. Beginning with basic console arithmetic and variable assignments, the guide explains how to transition to R scripts for executing multi-line programs. Viewers learn how to import a CSV sales dataset into a structured data frame, inspect its structural data types, and generate statistical summaries. The tutorial then demonstrates data manipulation by calculating total sales revenue using a custom formula that factors in units sold, unit price, and discount percentages, alongside data cleaning techniques like converting characters into formal date objects.
The second half of the lesson elevates the analysis by moving from rudimentary base R plots to advanced data visualizations using the ggplot2 library. It details how to map variables to chart aesthetics to build dynamic line and bar charts aggregated by date, geographical region, and product category. Additionally, the guide introduces data filtering techniques, showing how to subset a data frame to isolate specific criteria—such as sales with discounts greater than zero—which effectively slices the rows for targeted analysis. The tutorial concludes as a comprehensive, entry-level stepping stone for anyone looking to kickstart their journey in statistical programming.
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