Independent t-Test: Unequal Sample Sets, 30 Samples Each

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The discussion centers on performing an independent samples t-test with unequal sample sets, specifically with 30 samples in each group. The calculated t statistic is 7.81 with 43 degrees of freedom and a p-value of less than 0.001, indicating a statistically significant difference between the averages of the two groups. The low p-value confirms the validity of the results, suggesting that the null hypothesis can be rejected. The necessity of a confidence interval alongside the p-value was also questioned, highlighting its importance in statistical analysis.

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I need to perform an independent samples t-test with unequal variables on these two sample sets. There are 30 samples in each. So far, I've come up with the following information.

t(43) = 7.81, p < 0.001

degrees of freedom = 43
t statistic = 7.81
p statistic = <0.001

I need confirmation if that's correct. Also, what does this say about the statistics? Is it valid enough? I'm trying to show that the difference between the averages of the two groups is statistically significant. Thanks if you can help.


Set 01

1.073
0.598
0.876
1.434
0.636
0.705
0.524
0.561
0.401
0.516
0.916
1.243
0.628
0.615
0.537
1.166
0.635
0.615
0.909
0.728
1.180
1.223
0.582
0.833
0.964
1.038
0.636
1.077
0.427
0.602


Set 02

0.244
0.283
0.516
0.237
0.427
0.413
0.457
0.293
0.365
0.152
0.500
0.232
0.343
0.335
0.476
0.329
0.523
0.192
0.478
0.523
0.293
0.198
0.304
0.679
0.241
0.314
0.246
0.109
0.276
0.617
 
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with a p-value that low, its obvius that the difference is statistically significant.

as for if you have all the t-values, I am not sure if its correct, do you have a confidence interval?
 
The Ippster said:
with a p-value that low, its obvius that the difference is statistically significant.

as for if you have all the t-values, I am not sure if its correct, do you have a confidence interval?

Is a confidence interval necessary if I have a p-value instead?