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T-test
Options consider:
Effect Sizes
Mean 1: 13.98
Mean 2: 9.087
N1: 25
N2: 25
Std Dev.1: 10.4796
Std Dev.2: 6.31

t (0.025) for 95% CI= 2.0491
declare p larger than alpha=0.05 not significant.

mean1 eq: 13.98 (var1= 109.822) (se= 2.096)
mean2 eq: 9.087 (var2= 39.816) (se= 1.262)

Probability that var1<var2
p=0.00797 (left: 0.992; double: 0.016)

Difference between means:
M1-M2=13.98-9.087=4.893
sd=13.445; se=2.4465
95% CI of difference:
-0.1203 <4.893< 9.9063 (Wald)
t-difference: 2
df-t: 29.7; p= 0.9723
(left p: 0.0277; two sided: 0.0554)

Difference not significant at 5%
study sample size

Effect size:
Cohen's D: 0.5657; s.e: 0.2884
This seems a medium effect size.
95% CI: -0.025 <0.5657< 1.157
-  pooled SD= 8.6498
Cohen's/Pearson's R: 0.2722
95% CI: -0.02 <0.2722< 0.521

Glass D: 0.4669; s.e: 0.066
95% CI: 0.312 <0.4669< 0.622
-  control/expected SD= 10.4796

Hedges's G: 0.5568; s.e: 0.2883
Eta-sq: 0.0741; s.e: 0.0384
Adjusted R-square: 0.0347; s.e: 0.0173
Omega: 0.0566; s.e: 0.0283
Epsilon: 0.0548; s.e: 0.0274

For help go to SISA
More:

Calculate the minimum Sample
Size required to see if the
difference between 13.98 and 9.09
is statistically significant

Calculate CI
around Mean1= 13.98.

Calculate CI
around Mean2= 9.087.