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Obtain as much information as you can about the \(P\) -value for an upper-tailed \(F\) test in each of the following situations: a. \(\mathrm{df}_{1}=3, \mathrm{df}_{2}=15\), calculated \(F=4.23\) b. \(\mathrm{df}_{1}=4, \mathrm{df}_{2}=18\), calculated \(F=1.95\) c. \(\mathrm{df}_{1}=5, \mathrm{df}_{2}=20\), calculated \(F=4.10\) d. \(\mathrm{df}_{1}=4, \mathrm{df}_{2}=35\), calculated \(F=4.58\)

Short Answer

Expert verified
The exact P-values are dependent on the specifics of the F-table or statistics software employed. Nonetheless, for each scenario, the P-value represents the probability that the F-statistic is larger than the calculated value given the degrees of freedom. Always remember, a lower P-value suggests stronger statistical evidence against the null hypothesis.

Step by step solution

01

Understanding the F-statistic

For a given F-statistic and its degrees of freedom, we can obtain the respective P-value. The calculated F-statistic is derived from the variances of two independent samples. The degrees of freedom are given as \(\mathrm{df}_{1}\) and \(\mathrm{df}_{2}\).
02

Use an F-table or a statistics software to find P-value for \(\mathrm{df}_{1}=3, \mathrm{df}_{2}=15\), calculated \(F=4.23\)

The desired P-value is the probability that the F-statistic is larger than the calculated value of 4.23. This probability can be obtained from an F-table or a statistics software by inputting the degrees of freedom and the F-statistic. The exact value may not be found on an F-table, but a range can be estimated.
03

Repeat step 2 for each scenario

Repeat the same process to get the P-value for the other scenarios in b, c, d with different degrees of freedom and F-statistics. Recall that a lower P-value suggests a lower probability of the observed differences happening due to chance, hence stronger evidence against the null hypothesis.

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