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Independent Samples T-Test. One sample T-Test. Paired Samples T-Test. One way Analysis of Variance (ANOVA).
Calculate the sample means. Find the difference between the two sample means: Calculate the standard error using the following equation: Divide your result from Step 2 by your result from Step 3. Look up your test statistic on the standard normal (Z-) distribution (see the below Z-table) and calculate the p-value.
A point estimate for the difference in two population means is simply the difference in the corresponding sample means. In the context of estimating or testing hypotheses concerning two population means, large samples means that both samples are large.
Independent Samples T-Test. One sample T-Test. Paired Samples T-Test. One way Analysis of Variance (ANOVA).
One of the most common tests in statistics, the t-test, is used to determine whether the means of two groups are equal to each other. The assumption for the test is that both groups are sampled from normal distributions with equal variances.
As discussed above, these two tests should be used for different data structures. Two-sample t-test is used when the data of two samples are statistically independent, while the paired t-test is used when data is in the form of matched pairs. There are also some technical differences between them.
Often, researchers choose significance levels equal to 0.01, 0.05, or 0.10. But any value between 0 and 1 can be used. Test method. Use the two-sample t-test to determine whether the difference between means found in the sample is significantly different from the hypothesized difference between means.
Calculate the sample means. Find the difference between the two sample means: Calculate the standard error using the following equation: Divide your result from Step 2 by your result from Step 3. Look up your test statistic on the standard normal (Z-) distribution (see the below Z-table) and calculate the p-value.
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