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Study Design and Statistical Test Planner

This tool is designed to plan and evaluate your study for your HCI research. Enter your independent and dependent variables for study design proposals, sample and power estimation, as well as statistical analysis for R. This tool only offers tips and help for beginners for quick start and is not a substitute for extensive research or input of your supervisor.

Add your independent variables (IV)?*
IV design
with levels
    Add your dependent variables (DV)?*
      Mean difference between min. and max. measures (in %):
      20 %
      Pooled standard deviation (in % of the mean difference):
      50 %


      Subjects (N estimated by Lehr's "Rule of 16"):
      24
      Statistical Power and Effect Sizes:
      Instructions for your experimental design:
      Instructions for your statistical test(s):
      Example 2x3 Within-Subject Design Example 2x4 Mixed-Design Example Regression

      Prof. Dr. Valentin Schwind. University of Applied Sciences Frankfurt. No liability for external links, correctness, completeness and up-todateness of any content. Site visits might result in storing of anonymized data (date, time, page viewed). Utilization at the own risk of the user. Data can be stored on the computers to facilitate the user's website access. Contribute here.

      Find/cite the publication of the toolkit here:
      Valentin Schwind, Stefan Resch, and Jessica Sehrt. 2023. The HCI User Studies Toolkit: Supporting Study Designing and Planning for Undergraduates and Novice Researchers in Human-Computer Interaction. In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems (CHI EA '23), April 23-28, 2023, Hamburg, Germany. ACM, New York, NY, USA, 7 pages. https://doi.org/10.1145/3544549.3585890