One sample T hypothesis test: \( \mu \) : Mean of variable \[ \begin{array}{l} \mathrm{H}_{0}: \mu=98 \\ \mathrm{H}_{\mathrm{A}}: \mu \neq 98 \end{array} \] Hypothesis test results: \begin{tabular}{|c|c|c|c|c|c|} \hline Variable - & Sample Mean \( \hat{\sim} \) & & & & \\ \hline BODY TEMP & 98.44 & 0.2550907 & 29 & 1.7248767 & 0.0952 \\ \hline HEART RATE & 76 & 1.131574 & 29 & -19.441945 & \( <0.0001 \) \\ \hline \end{tabular}
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- The alternative hypothesis (\(H_A\)) suggests that the mean (\(\mu\)) of the variable is not equal to 98. This is a two-tailed test because we are looking for differences in both directions (higher or lower than 98). Show more…
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Madhur L.
Sample mean, sample size, and population standard deviation are given. Use the one-sample z-test to perform the required hypothesis test at the given significance level. Use the P-value approach. Sample mean = 41, n = 26, σ = 6, α = 0.05. H0: μ = 44. Ha: μ ≠ 44. z = -2.55; P-value = 0.01085; RHO. z = -2.55; P-value = 0.01085; FTRHO. z = -2.55; P-value = 0.0054; RHO. z = -2.55; P-value = 0.0054; FTRHO. None of these.
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Use technology to find the P-value for the hypothesis test described below. The claim is that for 12 AM body temperatures, the mean is μ > 98.6°F. The sample size is n = 9 and the test statistic is t = 2.262.
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