The general idea behind all of these t-tests is that you are: comparing between
ID: 3295004 • Letter: T
Question
The general idea behind all of these t-tests is that you are:
comparing between variation to within variation by dividing the systematic difference between two samples, or between a sample and a population, by the chance variation within the samples.
only comparing the sample means to the population means, since you don't know the true variance in the sample or in the population, and the variance doesn't matter as long as the sample means are different.
comparing within variation to between variation by dividing the chance variation within the samples by the systematic difference between two samples (or between a sample and a population).
comparing sample variation to population variation by dividing one by the other
a.comparing between variation to within variation by dividing the systematic difference between two samples, or between a sample and a population, by the chance variation within the samples.
b.only comparing the sample means to the population means, since you don't know the true variance in the sample or in the population, and the variance doesn't matter as long as the sample means are different.
c.comparing within variation to between variation by dividing the chance variation within the samples by the systematic difference between two samples (or between a sample and a population).
d.comparing sample variation to population variation by dividing one by the other
Explanation / Answer
The general idea behind all of these t-tests is that you are:
only comparing the sample means to the population means, since you don't know the true variance in the sample or in the population, and the variance doesn't matter as long as the sample means are different.
The rest of the options correspond to F-tests, where we take the ratio of the variances.
b.only comparing the sample means to the population means, since you don't know the true variance in the sample or in the population, and the variance doesn't matter as long as the sample means are different.
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