a researcher comparing the means of sample from two different populations, decided to test the same two-sided hypothesis using two

a researcher comparing the means of sample from two different populations, decided to test the same two-sided hypothesis using two different tests: a one-way anova f test, and a two-sample t test using the t statistic with pooled variance. the value of the pooled t statistic for the test is 1.2. this means that the value of the f statistic will be

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  1. The test’s pooled t statistic has a value of 1.2. This indicates that the f statistic’s value will be 1.44.

    Define the term two-sided hypothesis?

    As contrast to a one-sided hypothesis, that is always bounded either by above or below, a two-sided hypothesis is just an alternate hypothesis that is not bounded either by above or below.
    • Actually, the union of 2 one-sided hypotheses results in a two-sided hypothesis.
    • The difference between both the results of 2 independent populations with equal variances can be tested using the pooled t test.
    • The test’s name alludes to the fact that the test statistic is computed using the variance of a pooled sample.
    As the question stated-
    The same two-sided hypothesis was tested by a researcher comparing the sample means from two distinct populations using two different exams: a one-way anova f test and a two-sample t test using t statistic using pooled variance.
    Thus,
    f statistic’s value = 1.2² = 1.44
    Thus, the test’s pooled t statistic has a value of 1.2. This indicates that the f statistic’s value will be 1.44.
    To know more about the two-sided hypothesis, here
    #SPJ4

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