Answer:
(a) 0.0855
(b) 0.0268
(c) 0.0319
Step-by-step explanation:
The <em>p</em>-value is well defined as per the probability, [under the null hypothesis (H₀)], of attaining a result equivalent to or greater than what was truly observed.
A small <em>p</em>-value (typically <em>p</em> ≤ 0.05) specifies sturdy proof against the null hypothesis (H₀), so we discard H₀. A large <em>p</em>-value (<em>p</em> > 0.05) specifies fragile proof against the H₀, so we fail to discard H₀.
(a)
Use the Excel function "=T.DIST.RT(1.465,11)" to compute the right-tailed <em>p</em>-value for a test statistic of, <em>t</em> = 1.465 and s degrees of freedom of, <em>df</em> = 11.
<em>p</em>-value = 0.0855
(b)
Use the Excel function "=T.DIST.2T(2.522,12)" to compute the two-tailed <em>p</em>-value for a test statistic of, <em>t</em> = 2.522 and s degrees of freedom of, <em>df</em> = 12.
<em>p</em>-value = 0.0268
(c)
Use the Excel function "=T.DIST(-1.952,22,TRUE)" to compute the left-tailed <em>p</em>-value for a test statistic of, <em>t</em> = -1.952 and s degrees of freedom of, <em>df</em> = 22.
<em>p</em>-value = 0.0319