Answer:
f(2) = -40
Step-by-step explanation:
Just substitute x=2 into the function:
f(x) = 2x³ - 3x² - 18x - 8
f(2) = 2(2)³ - 3(2)² - 18(2) - 8
f(2) = 2(8) - 3(4) - 36 - 8
f(2) = 16 - 12 - 44
f(2) = 4 - 44
f(2) = -40
Answer:
<h2>7.4inches</h2>
Step-by-step explanation:
Check the attachment for the diagram. Sine rule will be used to get the unknown side of the triangle.
According to the rule;

Given w = 3 in, ∠W=23° and ∠U=73°, on substituting into the equation above to get u we have;

The length of u is 7.4inches to nearest 10th of an inch
Answer:
was there more
Step-by-step explanation:
(i will edit answer)
The length of AC is congruent to WY
d = 10
Answer:
Let X the random variable that represent the number of children per fammili of a population, and for this case we know the following info:
Where
and
We select a sample of n =64 >30 and we can apply the central limit theorem. From the central limit theorem we know that the distribution for the sample mean
is given by:
And for this case the standard error would be:

Step-by-step explanation:
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".
Solution to the problem
Let X the random variable that represent the number of children per fammili of a population, and for this case we know the following info:
Where
and
We select a sample of n =64 >30 and we can apply the central limit theorem. From the central limit theorem we know that the distribution for the sample mean
is given by:
And for this case the standard error would be:
