Editing Experimental Design (section)

== <span style="color: #FFFFFF;">Applying</span> ==
'''Modeling the 'Placebo Effect' and 'Treatment Effect':'''
<syntaxhighlight lang="python">
import numpy as np

def run_experiment(n_per_group, true_effect_size):
    """
    Simulates an experiment with a Control (Placebo) 
    and an Experimental (Treatment) group.
    """
    # Placebo effect (everyone gets a bit better just by being in a study)
    placebo_mean = 5 
    
    # Generate data with random noise
    control = np.random.normal(placebo_mean, 2, n_per_group)
    experimental = np.random.normal(placebo_mean + true_effect_size, 2, n_per_group)
    
    # Calculate observed difference
    observed_diff = np.mean(experimental) - np.mean(control)
    return observed_diff

# Is the medicine effective? (Effect size = 3)
n = 50 # Sample size
observed = run_experiment(n, 3)
print(f"Observed Treatment Effect (N={n}): {observed:.2f}")
# If N is small, the 'noise' might make the effect look like 0 or 10. 
# Increasing N 'averages out' the noise.
</syntaxhighlight>

; Design Types
: '''Cross-over Design''' → Each participant receives both treatments at different times (they act as their own control).
: '''Quasi-Experiment''' → An experiment where randomization is not possible (e.g., comparing two different classrooms).
: '''Natural Experiment''' → Using a "random" event in the real world (like a lottery or a sudden policy change) as if it were an experiment.
: '''A/B/n Testing''' → Testing multiple versions (A, B, C, D) of a product at once.
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