Temporary Help Answer
The answer is limited due to the lack of questions, so I'll give you some answers related.
State appropriate Hypothesis for performing a significance test. Be sure to define the parameter of interest. (u = mu)
[tex]H_{null}:u=17 \\H_{a}:u<17[/tex] Where mu = the true mean of almonds in each bar of candy.
Calculate the test statistic and the P-Value.
mu = 17
x-bar = 14
[tex]S_{x} = 8[/tex]
[tex]n = 30[/tex]
Use the T-Test (STAT) if you have a Graphing Calculator.
Interpret the P-Value in context.
Assuming the mean number of almonds in each candy bar is 17, there is a [P-Value] probability of getting a sample mean of 14 by chance alone.
What is the decision at the given significance level?
P-val of [P-Value] is (> or <?) to the alpha level [[tex]a[/tex]], so you must (fail to reject or reject?) the Null Hypothesis.
What do you conclude? (If P-val is smaller than the alpha level, reject the null hypothesis, meaning there is significant evidence.)
Because the P-Value of [P-Value] is (less/greater) than [tex]a = (?)[/tex], the observed result (is or is not?) statistically significant. There (is or is not?) significant evidence to conclude that the chocolate almond bars contain fewer almonds than they've previously contained.
