If the values in one sample affect the values in the other sample, then the samples are dependent.
If the values in one sample reveal no information about those of the
other sample, then the samples are independent.
What is the difference between a test of independent means and a test of dependent means and when is each appropriate?
what is the difference between a test for independent means and a test for dependent means, and when is each appropriate?
A t-test for independent means test two distinct groups of participants, each group is tested once
. -A test for dependent means tests one group of participants, and each participant is tested twice.
What is a dependent t-test?
The t-test for dependent means
compares the mean difference between sample scores that are linked by the study design to an expectation about the difference in the population
. … In t-tests, we estimate the population variances/standard deviations from sample data (S).
What is the difference between t-test and independent t-test?
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 is an example of an independent t-test?
For example, you could use an independent t-test to
understand whether first year graduate salaries differed based on gender
(i.e., your dependent variable would be “first year graduate salaries” and your independent variable would be “gender”, which has two groups: “male” and “female”).
What are the 3 types of t tests?
- One sample t-test.
- Independent two-sample t-test.
- Paired sample t-test.
What is the use of independent t-test?
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. This test is also known as: Independent t Test.
What is a two independent sample t-test?
The two-sample t-test (also known as the independent samples t-test) is
a method used to test whether the unknown population means of two groups are equal or not.
What is another name for a Dependant samples t-test?
The dependent t-test (also called
the paired t-test or paired-samples t-test
) compares the means of two related groups to determine whether there is a statistically significant difference between these means.
What are the assumptions of 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.
Which t-test should I use?
If you are studying one group, use a
paired t-test
to compare the group mean over time or after an intervention, or use a one-sample t-test to compare the group mean to a standard value. If you are studying two groups, use a two-sample t-test. If you want to know only whether a difference exists, use a two-tailed test.
How do you know if data is independent?
Events A and B are independent if the
equation P(A∩B) = P(A) · P(B) holds
true. You can use the equation to check if events are independent; multiply the probabilities of the two events together to see if they equal the probability of them both happening together.
What is the null and alternative hypothesis for an independent t-test?
The null hypothesis for an independent samples t-test is
that two populations have equal means on some metric variable
. … However, very different sample means suggest that the population means weren't equal after all. A t-test tells us if a sample difference is big enough to draw this conclusion.
How do you know if variance is equal or unequal?
- Use the Variance Rule of Thumb. As a rule of thumb, if the ratio of the larger variance to the smaller variance is less than 4 then we can assume the variances are approximately equal and use the Student's t-test. …
- Perform an F-test.
