![]() For relatively small datasets and simple estimators, you can maybe scrape by with Excel. To the latter point: if you plan to work in an economics-related field after you graduate, be it in academia or in the private sector, you will need to work with data. You may also be wondering why we even need a programming language for economics at all! Most of you come from one of the following backgrounds: i) you have no programming experience, ii) you’re familiar with Stata (or another statistical software like SAS or SPSS), iii) you’ve used other general programming languages before, or iv) you already know R! Except for those of you in iv), the rest may be wondering why we choose to use R for this course rather than (the default) Stata or something else. Statistical estimators are usually released in R before they make their way to other statistical software. It has a large user community that is continuously adding to its collection of external libraries and expanding the base functionality of R. Owing to its foundations in statistics, it has many useful capabilities out-of-the-box. R is an open-source programming language with a focus on statistical computing. 1.1 Importance of this Guide for the Course (and the Exam!). ![]()
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