How do you know if a t-test is significant?

How do you know if a t-test is significant?

How do you know if a t-test is significant?

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 is a matched pairs t-test?

A matched-pairs t-test is used to test whether there is a significant mean difference between two sets of paired data. Specify significance level. Often, researchers choose significance levels equal to 0.01, 0.05, or 0.10; but any value between 0 and 1 can be used.

What are the assumptions of at 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 is a significant t test?

A t-test asks the question, “Is the difference between the means of two samples different (significant) enough to say that some other characteristic (teaching method, teacher, gender, etc.) could have caused it?”

What is the difference between an independent t-test and a dependent t-test?

Dependent samples are paired measurements for one set of items. Independent samples are measurements made on two different sets of items. When you conduct a hypothesis test using two random samples, you must choose the type of test based on whether the samples are dependent or independent.

What is the difference between a matched pairs t-test and a 2 sample 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. However, if we have n matched pairs, the actual sample size is n (pairs) although we may have data from 2n different subjects.

What are the assumptions for a two-sample t-test?

Two-sample t-test assumptions Data in each group must be obtained via a random sample from the population. Data in each group are normally distributed. Data values are continuous. The variances for the two independent groups are equal.