For the same data, null hypothesis, and level of significance, is it possible that a one-tailed test results in the conclusion to reject Hg while a two tilled test results in the conclusion to fail to reject Ho? Explain.

Question
Significance tests
asked 2020-12-30
For the same data, null hypothesis, and level of significance, is it possible that a one-tailed test results in the conclusion to reject Hg while a two tilled test results in the conclusion to fail to reject Ho? Explain.

Answers (1)

2020-12-31
For the same data, null hypothesis and level of significance \(\alpha\), the P-value of a one-tailed test is smaller than that of a two-tailed test and the P-value for two-tailed is twice the one-tailed. So the P-value for a one-tailed test might be smaller than \(\alpha\), while the P-value for a two-tailed test could be larger than a. Therefore, It is possible that a one-tailed test results in the conclusion to reject \(H_{0}\) while a two-tailed test results in the conclusion to fail to reject \(H_{0}\).
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Relevant Questions

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For the same data, null hypothesis, and level of significance, if the conclusion is to reject \(H_{0}\) based on a two-tailed test, do you also reject Ho based on a one-tailed test? Explain.
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In there a relationship between confidence intervals and two-tailed hypothesis tests? The answer is yes. Let c be the level of confidence used to construct a confidence interval from sample data. Let * be the level of significance for a two-tailed hypothesis test. The following statement applies to hypothesis tests of the mean:
For a two-tailed hypothesis test with level of significance a and null hypothesis \(H_{0} : \mu = k\) we reject Ho whenever k falls outside the \(c = 1 — \alpha\) confidence interval for \(\mu\) based on the sample data. When A falls within the \(c = 1 — \alpha\) confidence interval. we do reject \(H_{0}\).
For a one-tailed hypothesis test with level of significance Ho : \(\mu = k\) and null hypothesiswe reject Ho whenever A falls outsidethe \(c = 1 — 2\alpha\) confidence interval for p based on the sample data. When A falls within the \(c = 1 — 2\alpha\) confidence interval, we do not reject \(H_{0}\).
A corresponding relationship between confidence intervals and two-tailed hypothesis tests is also valid for other parameters, such as p, \(\mu1 — \mu_2,\ and\ p_{1}, - p_{2}\).
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State the null and alternate hypotheses.
\(H0:?_{1}^{2}=?_{2}^{2},H1:?_{1}^{2}>?_{2}^{2}H0:?_{1}^{2}=?_{2}^{2},H1:?_{1}^{2}\neq?_{2}^{2}H0:?_{1}^{2}=?_{2}^{2},H1:?_{1}^{2}?_{2}^{2},H1:?_{1}^{2}=?_{2}^{2}\)
(b) Find the value of the sample F statistic. (Round your answer to two decimal places.)
What are the degrees of freedom?
\(df_{N} = ?\)
\(df_{D} = ?\)
What assumptions are you making about the original distribution?
The populations follow independent normal distributions. We have random samples from each population.The populations follow dependent normal distributions. We have random samples from each population.The populations follow independent normal distributions.The populations follow independent chi-square distributions. We have random samples from each population.
(c) Find or estimate the P-value of the sample test statistic. (Round your answer to four decimal places.)
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At the ? = 0.05 level, we fail to reject the null hypothesis and conclude the data are not statistically significant.At the ? = 0.05 level, we fail to reject the null hypothesis and conclude the data are statistically significant. At the ? = 0.05 level, we reject the null hypothesis and conclude the data are not statistically significant.At the ? = 0.05 level, we reject the null hypothesis and conclude the data are statistically significant.
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Reject the null hypothesis, there is sufficient evidence that the population variance is larger in the old thermostat temperature readings.Fail to reject the null hypothesis, there is sufficient evidence that the population variance is larger in the old thermostat temperature readings. Fail to reject the null hypothesis, there is insufficient evidence that the population variance is larger in the old thermostat temperature readings.Reject the null hypothesis, there is insufficient evidence that the population variance is larger in the old thermostat temperature readings.
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Find \(\displaystyleΣ{x},Σ{y},Σ{x}^{2},Σ{y}^{2},Σ{x}{y},{\quad\text{and}\quad}{r}\). (Round r to three decimal places.)
\(\displaystyleΣ{x}=\)
\(\displaystyleΣ{y}=\)
\(\displaystyleΣ{x}^{2}=\)
\(\displaystyleΣ{y}^{2}=\)
\(\displaystyleΣ{x}{y}=\)
\(\displaystyle{r}=\)
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Use a \(1\%\) level of significance to test the claim that \(\displaystyle\rho<{0}\). (Round your answers to two decimal places.)
\(\displaystyle{t}=\)
critical \(\displaystyle{t}=\)
Conclusion
Reject the null hypothesis. There is sufficient evidence that \(\displaystyle\rho<{0}\).Reject the null hypothesis. There is insufficient evidence that \(\displaystyle\rho<{0}\).
Fail to reject the null hypothesis. There is sufficient evidence that \(\displaystyle\rho<{0}\).Fail to reject the null hypothesis. There is insufficient evidence that \(\displaystyle\rho<{0}.\)
(c)
Find \(\displaystyle{S}_{{e}},{a},{\quad\text{and}\quad}{b}\). (Round your answers to four decimal places.)
\(\displaystyle{S}_{{e}}=\)
\(\displaystyle{a}=\)
\(\displaystyle{b}=\)
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