Answer:
144
Step-by-step explanation:
x = ((n-2)π / n) radians = (((n-2)/n) x 180° ) degrees
Answer:
18 minutes
Step-by-step explanation:
5 mins = 10 pages
10 mins = 20 pages
15 mins = 30 pages
20 mins = 40 pages
Just keep adding 5 to the minutes and 10 to the pages. then if you divide 10 by 5 (10÷5) you get 2.
2 is the amount of pages you read in 1 minute.
so 1 minute = 2 pages
Since you only need to read 36 pages, you know that it would at least take you 15 mintes to read 30.
then you start adding 1 minute until you get to 36 pages.
15 minutes = 30 pages
16 minutes = 32 pages
17 minutes = 34 pages
18 minutes = 36 pages
Therefore, it should take 18 minutes to read all 36 pages.
(A shorter way of doing this would be doing 10÷5=2, then just dividing 36 by 2 (36÷2) and you would get 18 which would be the minutes it would take you to read all 36 pages if you read at 2 pages per minute.)
Answer:
Factors of 78: 1, 2, 3, 6, 13, 26, 39, and 78.
Prime Factorization of 78: 78 = 2 × 3 × 13.
Step-by-step explanation:
Answer:
a. The sampling distribution for the sample mean will be skewed to the left centered at the average u, and standard deviation will be ∅
b. The sample distribution will be normal in shape and will be centered at the average u, . standard deviation will be ∅
1
c. As the size of the sample increases, the sample distribution should draw near and resemble the distribution of the population
Step-by-step explanation:
A sample is chosen randomly from a population that was strongly skewed to the left. a) Describe the sampling distribution model for the sample mean if the sample size is small. b) If we make the sample larger, what happens to the sampling distribution model’s shape, center, and spread? c) As we make the sample larger, what happens to the expected distribution of the data in the sample?
The following answers will march the questions above:
a. The sampling distribution for the sample mean will be skewed to the left centered at the average u, and standard deviation will be ∅
b. The sample distribution will be normal in shape and will be centered at the average u, . standard deviation will be ∅
1
c. As the size of the sample increases, the sample distribution should draw near and resemble the distribution of the population