A carpenter is making doors that are 2058 millimeters tall. If the doors are too long they must be trimmed, and if they are too short they cannot be used. A sample of 11 doors is taken, and it is found that they have a mean of 2070 millimeters with a variance of 400 . Assume the population is normally distributed. Is there evidence at the 0.05 level that the doors are too long and need to be trimmed? Step 5 of 6 : Identify the level of significance for the hypothesis test.

Here are the test scores of a class of learners: \( 100,100,99,98,92,91,91,90,88,87,87,85,85,85,80,79,76,72,67,66,45 \) a) What is the average score (mean) of the class for this test?

\( n = 5 \quad p ( \overline { x } > 500 ) \)

Bila diberikan sebuah sebaran normal dengan \( \mu=40 \) dan \( \sigma=6 \), hitunglah: a. Luas daerah di bawah 32 b. Luas daerah di atas 27 c. Luas daerah di antara 42 dan 51 d. Nilai x yang luas daerah di bawahnya \( 45 \% \) e. Nilai \( x \) yang luas daerah di atasnya \( 13 \% \)

A national food brand wants to launch a new chip flavor. They run a test study and offer 3 new flavors in select stores around the country.What's the best measure for determining which flavor to launch?Total revenue before and after offering the new flavorsSocial media surveysSales data and frequency of repeat purchases for the new flavorsDiscussions with customers in the stores offering the new flavorsTotal sales for stores offering the new chips against those that are not

Question 2 ( 0.25 points) Retake question Choose the correct interpretation of a p-value. If the test is right-tailed, the \( p \)-value is the probability of observing a sample proportion as small as we saw in our sample, if the null hypothesis were true. If the test is right-tailed, the \( p \)-value is the probability of observing a sample proportion as large as we saw in our sample, if the null hypothesis were true. If the test is right-tailed, the \( p \)-value is the probability of observing a sample proportion as large as we saw in our sample. If the test is two-tailed, the \( p \)-value is the probability of observing a sample proportion as far away from the null value as what was observed in the current data set.