The main output for this example is below, and we can obtain the effect size as Cohen's d =0.99 [0.78,1.21]. This represents a very large effect. Therefore, as well as being statistically significant, this effect is large and represents a substantive finding.
95% CI for Mean Difference | 95% CI for Cohen's d | ||||||||||||||||||||||||||
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Measure 1 | Measure 2 | t | df | p | Mean Difference | SE Difference | Lower | Upper | Cohen's d | SE Cohen's d | Lower | Upper | |||||||||||||||
day_1 | - | day_3 | 10.587 | 122 | < .001 | 0.675 | 0.064 | 0.549 | 0.801 | 0.994 | 0.115 | 0.776 | 1.208 | ||||||||||||||
Note. Cohen's d corrected for correlation between observations. | |||||||||||||||||||||||||||
Note. Student's t-test. |
N | Mean | SD | SE | Coefficient of variation | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|
day_1 | 810 | 1.793 | 0.944 | 0.033 | 0.527 | ||||||
day_3 | 123 | 0.977 | 0.710 | 0.064 | 0.727 | ||||||
On average, hygiene scores significantly decreased from day 1 (M = 1.793, SE = 0.033), to day 3 (M = 0.977, SE = 0.064) of the Download music festival, t(122) = 10.587, p < .001, Cohen's d =0.99 [0.78,1.21] .