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  7. Statistiek I voor de bedrijfseconomische wetenschappen

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Summary Module 9: Experiments
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  • Course
  • Statistiek I voor de bedrijfseconomische wetenschappen
  • Institution
  • Vrije Universiteit Brussel (VUB)

short summary of the experiments section that is not developed in the lectures but is familiar. Only available up to and including part 9.2 (just read the rest). short summary of the experiments section that is not elaborated in the lectures but are to be known. Only knowable up to section 9.2 (...

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  • July 13, 2024
  • 2
  • 2023/2024
  • Summary

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  • statistics i
  • statistics
  • summary
  • summary
  • statistics
  • statistics i

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  • Vrije Universiteit Brussel (VUB)
  • Handelsingenieur
  • Statistiek I voor de bedrijfseconomische wetenschappen
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Summary of Chapter 9: Experiments in Statistics

9.1 Randomized, Comparative Experiments

• Definition: Experiments involve manipulating one or more factors (independent
variables) and observing the effect on a response variable (dependent variable).
• Purpose: To establish causal relationships by controlling and randomly
assigning treatments to subjects.

9.2 The Four Principles of Experimental Design

1. Control:
o Control external variables to isolate the effect of the treatment.
o Use control groups to provide a baseline for comparison.
2. Randomize:
o Randomly assign subjects to treatments to balance unknown variables.
o Ensures groups are comparable and results are unbiased.
3. Replicate:
o Make multiple observations or repeat experiments to estimate variability.
o Replication increases the reliability and generalizability of the results.
4. Block:
o Group similar subjects together and randomize within these blocks to
reduce variability.
o Helps control the effect of confounding variables.

9.3 Experimental Designs

One Factor Designs

• Single Factor Experiment: Also known as A/B tests, bucket tests, or split-run
tests.
o Example: Comparing two versions of a webpage (Design A vs. Design B) to
see which one performs better.
o Control Group: One group sees the current version (Design A).
o Test Group: Another group sees the new version (Design B).
o Completely Randomized Design: Participants are randomly assigned to
either group, ensuring unbiased results.

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