d
paired t-test is more powerful because it utilizes information
Both are parametric test. The t-test uses a test statistic that is related to the sample mean(s) and is used to compare that with the mean of another sample or some population. The F-test uses a test statistic that is related to the sample variance and is used to compare that with the variance of another sample or some population. Both tests require identical independently distributed random variables. This ensures that the relevant test statistics are approximately normally distributed.
The"t" test, (called the "small 't' test, to distinguish it from the large 'T' test) is a test for deviation from a known norm, using a smaller sample set than the one required by the large T test. It is said to have been developed by the head of quality control at the Guinness Brewery in Ireland.
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d
normal, SRS, independent normal, SRS, independent
independent sample t test
paired t-test is more powerful because it utilizes information
Because under the null hypothesis of no difference, the appropriate test statistic can be shown to have a t-distribution with the relevant degrees of freedom. So you use the t-test to see how well the observed test statistic fits in with a t-distribution.
Both are parametric test. The t-test uses a test statistic that is related to the sample mean(s) and is used to compare that with the mean of another sample or some population. The F-test uses a test statistic that is related to the sample variance and is used to compare that with the variance of another sample or some population. Both tests require identical independently distributed random variables. This ensures that the relevant test statistics are approximately normally distributed.
The"t" test, (called the "small 't' test, to distinguish it from the large 'T' test) is a test for deviation from a known norm, using a smaller sample set than the one required by the large T test. It is said to have been developed by the head of quality control at the Guinness Brewery in Ireland.
erwtwertgrtewh
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.
t test is used when- a) variables are studied b)the size of sample is a small one.(n<30) chi square test is studied when a) attributes are studied
The assumptions of a two-sample t-test are: Each sample come from a normally distributed population. Both populations have equal variances. The data are sampled independently from each population.
The null hypothesis of the independent samples t-test is verbalized by either accepting or rejecting it due to the value of the t-test. If the value is less than 0.05 it is accepted and greater than 0.05 is rejecting it.