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Anastaziya [24]
2 years ago
12

Find the product. (a-6)^2=

Mathematics
1 answer:
gavmur [86]2 years ago
8 0

Answer:

a^2-12a+36

Step-by-step explanation:

;)

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lung cancer kills about 3,000 people per day. if 90% of the deaths from luung cancer are attributted to smoking, what is the rat
defon

Answer:

2700!

Step-by-step explanation:

hope that helped <3

5 0
3 years ago
Whích best describes the range of the function f(x) = } 6)* after it has been reflected over the x-axis?
soldier1979 [14.2K]

Answer: The third One

Step-by-step explanation:

3 0
2 years ago
Read 2 more answers
If both diagonals of a quadrilateral bisect each other when is the quadrilateral a parallelogram?
slamgirl [31]
It is more than just a quadrilateral. In fact it is going to be hard to pick.

These facts suit a square,  a rectangle, a rhombus, and a parallelogram. And the above statement is true, but maybe a little harder to prove than the converse of the statement, which is the usual one you find.

The converse is "If you have a parallelagram, the diagonals bisect each other."

You might think a trapezoid deserves some mention. The diagonals of a trapezoid do not bisect each other.
6 0
2 years ago
If anyone can help with number 4
Klio2033 [76]
If you do 27-12 (which is 15) you add 15 to 13 and 20
3 0
3 years ago
How does the sample size affect the validity of an empirical​ argument? A. The larger the sample size the better. B. The smaller
astra-53 [7]

Answer:

A. The larger the sample size the better.

Step-by-step explanation:

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1-p)}{n}}

In this question:

We have to look at the standard error, which is:

s = \frac{\sigma}{\sqrt{n}}

This means that an increase in the sample size reduces the standard error, and thus, the larger the sample size the better, and the correct answer is given by option a.

7 0
3 years ago
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