Answer:
No
It could be purely due to chance.
Step-by-step explanation:
A population is defined as the whole group which has the same characteristics. For example a population of the college belongs to the same college . But a sample may be an element of a population.
So it is not necessary for a population to have the same characteristics as the sample.
But it is essential for the sample to have at least one same characteristics as the population.
So we would not be correct in inferring that such a relationship also exists in the population.
It is a hypothesis which can be true or false due to certain conditions or limitations as the case maybe.
For example in a population of smokers some may be in the habit of taking cocaine. But a sample of cocaine users does not mean the whole population uses it.
It could be purely due to chance if we find out that there is a relationship between parents’ and children’s party identification in the population.
The linear equation to model the company's monthly expenses is y = 2.5x + 3650
<em><u>Solution:</u></em>
Let "x" be the units produced in a month
It costs ABC electronics company $2.50 per unit to produce a part used in a popular brand of desktop computers.
Cost per unit = $ 2.50
The company has monthly operating expenses of $350 for utilities and $3300 for salaries
We have to write the linear equation
The linear equation to model the company's monthly expenses in the form of:
y = mx + b
Cost per unit = $ 2.50
Monthly Expenses = $ 350 for utilities and $ 3300 for salaries
Let "y" be the total monthly expenses per month
Then,
Total expenses = Cost per unit(number of units) + Monthly Expenses
Thus the linear equation to model the company's monthly expenses is y = 2.5x + 3650
Answer: I need a picture off the pool and measurements.
Step-by-step explanation: I need this in order to figure out the problem and give you a helpful answer.
Answer:
0.108
Step-by-step explanation:
Using the poisson probability process :
Where :
P(x =x) = (e^-λ * λ^x) ÷ x!
Given that :
Each batch of bread = 3 loaves
Each loaf = 15 slices
Total slice per batch = 15 * 3 = 45 slices
Number of raising added = 100
Average number of raisin per slice, λ = 100/45 = 20/9
Hence,
Probability that a randomly chosen slice has no raising :
P(x = 0) = (e^-λ * λ^x) ÷ x!
P(x = 0) = (e^-(100/45) * (100/45)^0) ÷ 0!
P(x = 0) = (0.1083680 * 1) / 1
P(x = 0) = 0.108
Answer:
A
Step-by-step explanation:
(2m-n) is a factor of 4(2m-n)
