Two sample t-test is used to check whether the means of two groups are significantly different from each other. For example, if you want to see if mean weight of males and females have statistically significant difference between them.
Independent T-test assumes that the two samples have equal variances. Welch's t-test is used if you have unequal variances.
Either enter raw data or summary information to calculate two sample t-test. You can directly paste data from MS Excel.
Enter Raw Data
Sample 1 | Sample 2 | |
1 | 310 | 360 |
2 | 398 | 343 |
3 | 276 | 253 |
4 | 286 | 242 |
5 | ||
6 | ||
7 | ||
8 | ||
9 | ||
10 |
Enter Summary Data
Result
t = 0.437940
p-value (One-tailed) = 0.338378
p-value (Two-tailed) = 0.676756
Degree of freedom = 6
Means for two groups are not significantly different from each other at 5% significance level(One-tailed)
Means for two groups are not significantly different from each other at 5% significance level(Two-tailed)
p-value (One-tailed) = 0.338378
p-value (Two-tailed) = 0.676756
Degree of freedom = 6
Means for two groups are not significantly different from each other at 5% significance level(One-tailed)
Means for two groups are not significantly different from each other at 5% significance level(Two-tailed)
Assumptions of Two Sample t-test
- Scores are normally distributed within each of the two groups
- Each score is sampled independently and randomly.
- Data must be continuous
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