Answer:
D. 30
Step-by-step explanation:
Having a population that doesn't follow normal distribution (skewed) can still have sampling distribution that is completely normal. This fact is presented in the Central Limit Theorem.
Central Limit Theorem: states that we can have a normal distribution of sample means even if the original population doesn't follow normal distribution, we just need to take a large sample.
So how much sample size do we need?
There is no straight forward answer to this rather we have to analyse the situation closely!
1. If the population distribution is already normal then a smaller sample size would be enough to ensure normal distribution.
2. If the population distribution is very skewed than a larger number of sample size is needed to ensure normal distribution. The rule of thumb is to take sample size equal to or more than 30 to be on safer side. This is the case in this problem hence option D fits the best.
-4u=16
U=16÷(-4)
U= -4 To check -4(-4)=16
16=16
Answer:
x= −1/ 240
Step-by-step explanation:
hope this helps!!
To find the end behavior of a function, we find it's limits as x approaches infinity, getting the correct option as:
As x approaches plus-or-minus infinity = limit of StartFraction 4 Over x Superscript 5 EndFraction as x approaches plus-or-minus infinity, so as x approaches infinity, g (x) approaches 0.
Function:
The function given is:

Limit as x goes to infinity:
To find the limit of a function as x goes to infinity, we consider the term with the highest exponent in the numerator and in the denominator. So

The graphic of the function, given at the end of this answer, corroborates the answer.
Thus, the correct option is:
As x approaches plus-or-minus infinity = limit of StartFraction 4 Over x Superscript 5 EndFraction as x approaches plus-or-minus infinity, so as x approaches infinity, g (x) approaches 0.
For more on limits as x approaches infinity, you can check brainly.com/question/12207599.
I think the answer would be negative 124 NOT SURE