Suppose you conduct a test and your p-value turns out to be

Which of the following are assumptions for the Significance Test for the Proportion?
1) Data is Categorical.
2) Data is from a convenience sample.
3) ${\displaystyle n{p}_0}$ and ${\displaystyle (1-p_0)}$ are both greater than 15
4) Data is Quantitative
5) Data is from a Normal Distribution
6) Data is from a random sample
7) ${\displaystyle \widehat{np}}$ and ${\displaystyle n(1-\hat{p})}$ are both greater than 15

If you are already certain that a null hypothesis is false, then:
Significance testing provides no useful information since all it does is reject a null hypothesis.
Significance testing is informative because you still need to know whether an effect is significant even if you know the null hypothesis is false.
When a difference is significant you can draw a confident conclusion about the direction of the effect.

A local pizza store knows the mean amount of time it takes them to deliver an order is 45 minutes arter the order is placed. The manager has a new system for processing delivery orders, and they want to test ifit changes the mean delivery time. They take a sample of delivery orders and find their mean delivery time is 48 minutes.
Let ${\displaystyle \mu }$ represent the mean delivery time under the new system.
What are appropriate hypotheses for their signifhcance test?
a)${\displaystyle H_0:\mu }$= 45 minutes
${\displaystyle H_a:\mu }$ ${\displaystyle \ne }$45 minutes
b)${\displaystyle H_0:\mu }$ =45 minutes
${\displaystyle H_a:\mu }$ ${\displaystyle \ne }$48 minutes
c)${\displaystyle H_0:\mu }$ p= 48 minutes
${\displaystyle H_a:\mu }$ ${\displaystyle \ne }$45 minutes
d)${\displaystyle H_0:\mu }$ = 48 minutes
${\displaystyle H_a:\mu }$ ${\displaystyle \ne }$48 minutes

Based on a small sample, a significance test may not yield a statisticallysignificant outcome even if the true value is considerably different fromthe null value. This outcome is also known as?
- significance level
- type I error
- type ll error
- power of the test

Interpret your conclusion in the context of the application.

To state:The null and alternative hypotheses.

The level of signifñicance (usually.05) associated with a significance test is the probability,
A. That the alternative hypothesis is true.
B. That the null hypothesis is true.
C. Of not rejecting a true null hypothesis.
D. Of rejecting a true null hypothesis.