Overview
This lecture explains the importance of reproducibility and replication in experimental design, focusing on controlling confounding factors and handling random variation to ensure robust scientific results.
Reproducibility and Replication
- Reproducibility means being able to repeat an experiment and get the same results.
- Replication is a fundamental principle of good research.
- Replicability helps validate scientific findings and ensures experiments are trustworthy.
Confounding Factors and Control
- Confounding factors (confounders) are variables besides the one studied that can affect results.
- Researchers control confounders by keeping conditions the same across groups.
- Complete control is difficult; unknown or uncontrollable confounders may remain.
Random Variation and Sample Size
- Random variation refers to natural differences among subjects, even under controlled conditions.
- Measuring only a few subjects increases the chance of random variation impacting results.
- Larger sample sizes make results more reliable by averaging out this variation.
Types of Replication
- Between experiment replication involves repeating entire experiments multiple times.
- Within experiment replication increases the number of subjects measured in each experiment.
- Normal distribution of results emerges as experiments and sample sizes increase.
Application in Animal and Human Research
- The need for replication and control of confounders applies to all research, including animal and human studies.
- More subjects and repeated experiments both help ensure findings reflect true effects, not random chance.
Review and Key Takeaways
- More replications across experiments reduce bias.
- More subjects within an experiment increase precision and reduce error variance.
- Combined approaches make scientific findings more robust and reproducible.
Key Terms & Definitions
- Reproducibility — Ability for an experiment to be repeated with the same results.
- Replication — Repeating experiments or measurements to verify findings.
- Confounding Factor (Confounder) — An outside variable that can affect experimental results.
- Random Variation — Natural differences that occur between subjects or measurements.
- Within Experiment Replication — Measuring more subjects in a single experiment.
- Between Experiment Replication — Repeating the entire experiment multiple times.
- Normal Distribution — A bell-shaped spread of data centered around the average result.
Action Items / Next Steps
- Review examples of replication in published research.
- Prepare to design experiments with controls for confounders and adequate replication.