During my searches I realized that there are several other programs that are arguably better for data analysis (Python, Matlab, SAS, SQL, etc.), but for the sake of simplicity, this blog will only dive into Excel and R. Based on the popularity of both programs, it seemed worthwhile to investigate other data analysts’ perspectives and why they may use R over Excel.

I decided to cruise some blogs on the debate between Excel and R for data analysis. Image Credit: The Debate Between Excel and R for Data Analysis Data analysis had never looked so shiny and new. I got a (rough) intro into source code writing and programming language and realized how much more quickly R can perform functions than the complex Excel formulas I had been playing with for years. I used R to create all kinds of statistical models including linear regressions, histograms, cluster analyses, and prediction methods to analyze data in ways that I had never done in Excel. Over the summer I took an R programming class that took me out of my Excel comfort zone and showed me just how differently data analysis can be when applied in different programs. Until recently, you couldn’t tell me I should use anything else. Excel has shown me I can turn almost anything into data that can be analyzed and played with in a Pivot Table. I use it every day, for both my job and my private life to help me understand MFP-Copier data pricing and specifications, and mapping out my finances to create a budget. After half a dozen years in data entry and analysis I can tell you that I love Excel.

Running a statistical analysis in excel