What is an independent sample t test used for?
The Independent Samples t Test compares the means of two independent groups in order to determine whether there is statistical evidence that the associated population means are significantly different. The Independent Samples t Test is a parametric test.
What is the formula for t test of independent samples?
Usually, the degrees of freedom are the sample size minus one (N – 1 = df). In the case of a t-test, there are two samples, so the degrees of freedom are N1 + N2 – 2 = df.
How do you manually calculate an independent t test?
Independent Samples t-Test
- The sum of the column.
- The sum of the squared values of the column (square each score and then sum it).
- The sample size for the column.
- The mean for the column (sum divided by the sample size).
- The sum of squares (SS) for the column.
What is an example of paired data?
An example of paired data would be a before-after drug test. The researcher might record the blood pressure of each subject in the study, before and after a drug is administered. These measurements would be paired data, since each “before” measure is related only to the “after” measure from the same subject.
What is the difference between one sample t test and paired t test?
As we saw above, a 1-sample t-test compares one sample mean to a null hypothesis value. A paired t-test simply calculates the difference between paired observations (e.g., before and after) and then performs a 1-sample t-test on the differences.
What is the difference between paired and independent 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.
Why do we use t test?
A t-test is a type of inferential statistic used to determine if there is a significant difference between the means of two groups, which may be related in certain features. A t-test is used as a hypothesis testing tool, which allows testing of an assumption applicable to a population.
What is the meaning of T in T test?
the calculated difference represented
How do you interpret a t test?
Compare the P-value to the α significance level stated earlier. If it is less than α, reject the null hypothesis. If the result is greater than α, fail to reject the null hypothesis. If you reject the null hypothesis, this implies that your alternative hypothesis is correct, and that the data is significant.
What are the assumptions for an independent t test?
The common assumptions made when doing a t-test include those regarding the scale of measurement, random sampling, normality of data distribution, adequacy of sample size and equality of variance in standard deviation.
What are we stating if we reject the null hypothesis for the independent samples t test?
What can we conclude if we reject the null hypothesis in an independent samples t-test? The difference between our sample means is unlikely to be representing zero difference in the population means. The sample mean difference represents a difference between two population µs that is not zero.
How do you know if variances are equal or unequal?
An F-test (Snedecor and Cochran, 1983) is used to test if the variances of two populations are equal. This test can be a two-tailed test or a one-tailed test. The two-tailed version tests against the alternative that the variances are not equal.
Which test is the alternative to the Student t test if the Homoscedasticity assumption is violated?
If the test of the equality of variances is significant, Welch’s t-test should be used instead of Student’s t-test because the assumption of equal variances is violated.
What does a 0 p value mean?
should reject the null hypothesis