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we conduct a t-test to see if the means of two different populations are statistically different from each other.
A t-test is an assessment of whether the means of two groups are statistically different from one another (running a t-test is appropriate when you want to compare the means of two groups). A t-test tell you the probability that those two sets of values come from different groups.
You use the t-test when the population standard deviation is not known and estimated by the sample standard deviation. (1) To test hypothesis about the population mean (2) To test whether the means of two independent samples are different. (3) To test whether the means of two dependent samples are different. (4) To construct a confidence interval for the population mean.
In a general t-test, there is no relationship between the members of one sample and the other. In a paired t-test they are connected in some way so that they are likely to give similar outcomes. This means that more of the difference between them can be attributed to the "treatment".
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t-test
Analysis of Variance (ANOVA) compares 3 or more means. The t-test would only compare 2 means.
No, don't use a single t-test to compare the means of 3 or more groups. Use ANOVA.
Yes, it is. The one sample t-test is a study of the parameter population-mean. You can also use the t-test to test for the difference between two population means (both parameters).
Test.
C- Control T- means test Line under the C - Negative Line under C and T- positive :)
You can test data using T-Test in SPSS. Click Analyze > Compare Means > Independent-Samples T-Test to run an Independent Samples T-Test in SPSS. In the Independent-Samples T-Test window, you specify the variables to be analyzed. On the left side of the screen, you will see a list of all variables in your dataset.