Excel vs R for Data Analysis: When to Use What

When working in data analysis and with big datasets, it is vital to determine the tools that would be best for each job.

For most surface-level data analysis, Excel is the easier option to use. Many people use Excel functions in their daily lives. All parts of Excel are built to be as intuitive and user-friendly as possible, including its inbuilt visualization tools for graphs and charts. Organizations such as the American Psychological Association use Excel to format graphs, as it requires fewer steps than with other programs while staying accurate to the data.

For large datasets and more complex data analysis techniques, R is more effective. R is more powerful, capable of running machine learning algorithms, regressions with multiple variables, ANOVA, and visualization of thousands of data points. R is also harder to learn, being closer to a programming language than a user-friendly program like Excel.

Both R and Excel have their strengths and are better for different scenarios and types of data. Our data analysts at Data in Plain English are proficient in both Excel and R, making sure you find the best fit for your project.