Quantitative Research I: Statistical inference, causal inference, and basics of regression analysis

Schedule and location

Tuesday October 18th - Wednesday October 19th  9:00-16:00

University of Jyväskylä, Jyväskylä, Agora building (visiting address: Mattilanniemi 2)

Tuesday: room Lea Pulkkisen sali (4th floor)

Wednesday: Computer class Ag B112.1. (Africa)



Registration is open until October 11th .


Dr. Mikko Rönkkö, University of Jyväskylä, Finland.


Dr. Mikko Rönkkö, University of Jyväskylä, Finland.


Many researchers use quantitative research designs and statistical analysis tools without sufficient understanding on what these techniques are based on. This course is a part of a series of six courses where the goal is to develop an understanding of how multivariate statistical methods are used in information systems research and how results are usually presented in journal articles. The main goal of the course is to provide a foundation that enables independent self-study of quantitative research methods. Rather than addressing simply how the methods are used, we focus on why certain methods are used and how and why these methods work.

The course is designed for both those interested in just reading and understanding research done with statistical methods and for those who already use or plan to use statistical research methods in their own work.

During the course series we will go through six empirical papers published in leading IS and management journals, and analyze how these papers were done. The methods and research designs used in these papers cover a majority of methods and designs used in these journals. If you master all the methods and techniques presented during the course, you would be ideally capable to publish in these journals – if you have already a new theoretical insight and access to appropriate data.

In this first course, we cover the logic of supporting causal claims with quantitative analyses, simple hypothesis testing with linear regression analysis, and introduce you to statistical software. You can complete the course using either Stata, R, or SPSS.

The course has a pre-class readings package and a pre-class assignment that must be returned before the course and a post-class report that must be returned after the course. You should reserve at least two days for the pre-class assignment and at least a day for the post-class report.


Detailed Program


Day 1 – Morning

 Course logistics

  • Introduction of Instructor
  • Introductions of Students
  • Syllabus and assignments
  • Review of course information systems

Principles of quantitative research

  • Statistical estimation
  • Statistical inference
  • Causal inference
  • Research design

Day 1 – Afternoon

Linear regression model

  • Introduction
  • Post-estimation diagnostics
  • Effect size interpretation and reporting

The endogeneity problem

Discussion on the pre-class assignment

Day 2 – Morning (computer class)

Conducting Reproducible Research

Introduction to Statistical Software Stata, R, and SPSS

Review of the data-analysis assignment and post-class report

Day 2 – Afternoon (computer class)

Working on the data-analysis assignment and post-class report


Credit points

Doctoral students participating in the seminar can obtain 2 credit points. This requires participating on both days and returning the pre-class assignment and post-class report.

Registration fee

This seminar is free-of-charge for Inforte.fi member organization's staff and their PhD students. For others the participation fee is 400 €. The participation fee includes access to the event and the event materials. Lunch and dinner are not included.