EFR thesis workshop: STATA

Introducing the presenter and host

This is an introductory Stata workshop hosted by Topscriptie. Topscriptie is a thesis tutoring organization, which advices students from all kinds of disciplines and academic levels. Topscriptie has a highly diversified team of 56 advisors, who can help you out with many of the issues that typically come up during academic research or the thesis writing trajectory. For more information, please visit the website of Topscriptie.

The Stata workshop is presented by Herman Belgraver, who is one of the thesis advisors at Topscriptie. Herman advises students from business administration courses and helps them to meet the variety of challenges that are inherent to thesis research and data-analysis. He has over ten years’ experience working with SPSS and more than three years’ experience working with Stata. As thesis advisor, he has seven years of experience in advising, coaching and mentoring students. Moreover, he is an active academic researcher association. In his role as thesis advisor and academic researcher, he has accumulated a lot of knowledge and practical experience regarding both SPSS and Stata. Many of the challenges you are experiencing right now, he has struggled with himself and he hopes that, during this workshop, he can provide you with valuable tips and skills he learned along the way.

Compared to SPSS, Stata is a more challenging program, because it is mainly based on programming commands and requires a higher level of statistical and program specific knowledge. Therefore, we want to give you a basic understanding of Stata and help you on to a good start using the program. In the workshop we focus on the Ordinary Least Square (OLS) regression, because this is one of the most used analysis techniques. It is an intermediary analysis for the fixed or random effects regression and in its simplicity an OLS is ideal for instruction purposes. In addition, most of the problems students encounter during their analysis, can be traced back to forgetting to check the compliance with the assumptions of the test they conduct. An OLS is ideal for showing what will happen, if the test assumptions are violated. The methodological steps taught in this workshop are applicable to both Stata and SPSS, the only difference is that, in SPSS, the commands and way of working is different.

The requirements for this workshop

The requirements for this workshop are that you have at least some understandings of Stata. With this we mean that you have used Stata in the past and are familiar with the look and feel of the program. We don’t expect you to know Stata-commands by heart, but you should at least be familiar with the Stata screens, such as the command window, variable window, history window, output window and a do-file. Furthermore, we expect that you are familiar with the assumptions of a general Ordinary Least Square (OLS) regression. Lastly, it is strongly advisable that you have Stata installed on your own laptop so you can duplicate the actions of the instructor on your own laptop.

Workshop structure

The workshop is based on Bloom’s Taxonomy of learning and starts with a little refresher of the basics. Subsequently, we move on to a more practice-oriented part, during which we will focus on applying our knowledge to a sample dataset. It is strongly advised, therefore, that you have Stata installed and working on your own computer. The sample dataset will be made available on the day of the workshop.

The Learning Objectives of this workshop:

  • A short introduction on working with Stata
  • The basic precautions when working with Stata
  • The basic assumptions when you conduct a hypothesis test
  • Checking and cleaning the data
  • Checking and correcting the distribution of your variables
  • Selecting the appropriate regression technique
  • Checking the assumptions of an Ordinary Least Square regression
  • Correcting your data to comply with the assumptions of the test
  • Interpreting the results of your regression analysis
  • Some frequently encountered problems
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