What is the difference between equal variance and unequal variance in t test?

The Two-Sample assuming Equal Variances test is used when you know (either through the question or you have analyzed the variance in the data) that the variances are the same. The Two-Sample assuming UNequal Variances test is used when either: You do not know if the variances are the same or not.

Should I use equal or unequal variance?

Shall you use the test for equal or unequal variances? If you have equal numbers of data points, or the numbers are nearly the same, then you should be able to safely use the two-sample test for equal variances.

What is the difference between the t test for two independent samples and the t test for two dependent samples eg matched pairs t test?)?

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.

What is the main difference between an independent samples t test and a single sample t test?

The single-sample t-test compares the mean of the sample to a given number (which you supply). The independent samples t-test compares the difference in the means from the two groups to a given value (usually 0). In other words, it tests whether the difference in the means is 0.

What does unequal variance mean in t-test?

For the unequal variance t test, the null hypothesis is that the two population means are the same but the two population variances may differ. The unequal variance t test reports a confidence interval for the difference between two means that is usable even if the standard deviations differ.

What is the difference between a paired and unpaired t-test?

A paired t-test is designed to compare the means of the same group or item under two separate scenarios. An unpaired t-test compares the means of two independent or unrelated groups. In an unpaired t-test, the variance between groups is assumed to be equal.

What is unequal variance t-test?

The unequal variance t test reports a confidence interval for the difference between two means that is usable even if the standard deviations differ. Both t tests report both a P value and confidence interval. The calculations differ in two ways: Calculation of the standard error of the difference between means.

What does equal variance mean in t-test?

When running a two-sample equal-variance t-test, the basic assumptions are that the distributions of the two populations are normal, and that the variances of the two distributions are the same.

What is the difference between independent t-test and paired t-test?

An Independent Samples t-test compares the means for two groups. A Paired sample t-test compares means from the same group at different times (say, one year apart). A One sample t-test tests the mean of a single group against a known mean.

What is the difference between independent and paired samples?

Paired-samples t tests compare scores on two different variables but for the same group of cases; independent-samples t tests compare scores on the same variable but for two different groups of cases.

What does equal variance mean?

homoscedasticity
Equal variances (homoscedasticity) is when the variances are approximately the same across the samples. If you are comparing two or more sample means, as in the 2-Sample t-test and ANOVA, a significantly different variance could overshadow the differences between means and lead to incorrect conclusions.

What is the t-test for unequal variances?

The t-test for unequal variances uses the Welch-Satterthwaite correction. When the variances are equal it gives essentially the same results as the equal variance test, so a common view is always to use the unequal variance option or always to use the unequal variance version if the results differ.

What is the test statistic for an independent samples t test?

The test statistic for an Independent Samples t Test is denoted t. There are actually two forms of the test statistic for this test, depending on whether or not equal variances are assumed. SPSS produces both forms of the test, so both forms of the test are described here.

How do you test the difference between sample means?

Observation: This theorem can be used to test the difference between sample means even when the population variances are unknown and unequal. The resulting test, called, Welch’s t-test, will have a lower number of degrees of freedom than (nx – 1) + (ny – 1), which was sufficient for the case where the variances were equal.

Do the samples have equal variances?

HA: The samples do not have equal variances. where s12 and s22 are the sample variances. If the p-value that corresponds to the test statistic is less than some significance level (like 0.05), then we have sufficient evidence to say that the samples do not have equal variances.