Calculating Effect SizeComparison of Two Means

1X 2Xn df SD1 SD2 t

p value

30 28 4.6 4.1 2.3 2.3 0.60 0.56

60 58 4.6 4.1 2.3 2.3 0.84 0.4

100 98 4.6 4.1 2.3 2.3 1.09 0.28

500 498 4.6 4.1 2.3 2.3 2.43 0.02*

1000 998 4.6 4.1 2.3 2.3 3.44 0.00*

Criticism on NHST

• 1. NHST does not provide the information which the researcher wants to obtain

• 2. Logical problems derived from the probabilistic nature of NHST.

• 3. NHST does not enable psychological theories to be tested.

• 4. The fallacy of replication. • 5. NHST fails to provide useful information because

H0 is always false. • 6. Problems associated with the dichotomous

decision to reject/not reject the H0. • 7. NHST impedes the advance of knowledge.

Effect Size

• Cohen (1988) defines the effect size as the extent to which the phenomenon is found within the population or, in the context of statistical significance testing, the degree to which the H0 is false.

• Snyder and Lawson (1993) argue that the effect size indicates the extent to which the dependent variable can be controlled, predicted and explained by the independent variable(s).

Effect Size Measures• Effect size measures of Two In/dependent

Groups– Cohen’s d– Hedges g– Glass Delta

• Correlation Measure of Effect Size– r– χ2 ►Φ; t ► r; F ► r; d ► r

• Effect size for Analysis of Variance– Eta Squared– Omega Square Index of Strength– Intercalss correlation

22

21

2

21

ssMMd

2

22

1

12

21

ns

ns

MMt

Cohen’s d Formulat-test for independent Means Formula

ComputationA research compared first year public and

private school students in their study habits. Study habits was measured using the Survey of Study Habits. The t-test for two independent samples was used to determine the significant difference between the students in the public and private school in the four factors of study habits. The following statistical output was obtained: