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Calculate Cohen's d, eta squared, Cramér's V, odds ratio & risk ratio with step-by-step solutions and Python code.
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Effect Size Benchmarks:
Jacob Cohen (1988) proposed: d = 0.2 (small), d = 0.5 (medium), d = 0.8 (large). These are rough guidelines, not rigid rules. In some fields (e.g., education), d = 0.3 may be practically important. Always interpret in context.
Hedges' g applies a correction factor for small sample bias: g = d * (1 - 3/(4(n1+n2) - 9)). For n > 20 per group, the difference is negligible. Use Hedges' g for meta-analyses or when sample sizes are small (n < 20).
Yes. A d of 1.5 means the two group means are 1.5 pooled standard deviations apart. Values above 2.0 are rare in social sciences but common in medical or physical sciences.