Question

For an experiment comparing more than 2 treatment conditions, why should you use analysis of variance...

For an experiment comparing more than 2 treatment conditions, why should you use analysis of variance rather than separate t tests?

a. Separate t tests would require substantially more computations
b. A test based on variance is more sensitive than a test based on means
c. Conducting several t tests would inflate the risk of a Type 1 error

Math   Statistics-And-Probability   
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Answer #1

The experiment having more than two treatments conditions, will involve atleast more than two samples. If we use the t - test for any two samples, then there is a chance of occuring type - I error. Again If we use t - test for another two samples, there is another chance of occuring type - I error. So, there are chances of increasing type - I error. These are unacceptable errors. An ANOVA controls for these errors so that the type - I error remains the same. Hence, the correct answer is C. Conducting several t - tests would inflate the risk of a Type - I error.

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