Designing Your Experiments for Reliable Results

Variables: Independent, Dependent, and Controlled

In any experiment, we manipulate one or more factors (independent variables) to observe their effect on another variable (dependent variable). Crucially, we must control extraneous variables – those that could influence the outcome but are not part of our investigation.

Randomization and Replication: Minimizing Bias

To reduce bias, it’s essential to randomly assign subjects or experimental units to different treatment groups. This helps ensure that any observed differences are due to the independent variable and not pre-existing variations. Replicating the experiment multiple times strengthens these findings.

Replication (n) increases statistical power.

Controls: Establishing a Baseline

A control group is essential for comparison. This group receives no treatment or a standard treatment, providing a baseline against which to measure the effects of your experimental manipulation. Accurate controls are fundamental to isolating the impact of the independent variable.

Control Group = Baseline Measurement

Blinding: Reducing Observer Bias

Blinding involves concealing information from participants or researchers about which treatment group they are assigned to. This helps prevent conscious or unconscious biases from influencing the results.

Frequently asked questions

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Everything above runs in your browser — open SPH Fluid and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.