Programming
Guidance for data analysis in Excel, R, and Stata
Guidance for data analysis in Excel, R, and Stata
This webpage provides an introduction to three commonly used software packages in business and economics -- Microsoft Excel, R, and Stata.
After years of teaching statistics and mentoring numerous undergraduate research projects it became clear that students often struggle to retain knowledge of various of topics in data analysis across courses. In search of scale economies, I have organized a detailed guide to this content here. My students in ECO 203 (Business Statistics), COR 388 (Baseball Analytics), ECO 360 (Industrial Organization), or ECO 499 (Undergraduate Research) will find this content to be particularly helpful and are expected to utilize this as a reference for the software relevant to their course.
No background knowledge is assumed. Content spans exploratory data analysis, introductory statistics, data visualizations, and programming applications for econometrics.
I. Introduction
II. Data Exploration
III. Probability
IV. Tests & Linear Regression
V. Advanced Topics
Getting set up.
Interacting with the software. Entering and modifying data. Executing basic operations. Getting help.
Understanding directories. Recognizing file extensions. Saving work for later.
Adding Toolboxes. Installing and Loading Packages. Adding .ado files.
Copy/Paste. Sorting. Re-Ordering. Merging. Appending. Re-Shaping.
Copy/Paste. Sorting. Re-Ordering. Merging. Appending. Re-Shaping.
Lines. Scatters. Pies. Bars. Histogram/Density.
Lines. Scatters. Pies. Bars. Histogram/Density.
I. Introduction
II. Data Exploration
III. Probability
IV. Tests & Linear Regression
V. Advanced Topics