Answer:
OA) 14
Step-by-step explanation:
2((7+1)-1)
2(8-1)
You could expand the brackets then simplify or just simplify now. It will be better to simplify now though but I will do both methods.
Simplifying first:
2(7) = 2 × 7 = 14
Our answer is 14 So answer is OA) 14
Expanding first then simplifying:
2(8-1) = 16-2 = 14
Our answer is 14 So answer is OA) 14
Answer:
Step-by-step explanation:
The general equation of a circle is , x² + y² + 2gx + 2fy + c = 0
Substituting the three points we get the following equations,
2g +14f +c=-50
14g - 2f + c =-50
16g +12f + c = -100
Solving these equations we get,
g =-4, f = -3, c = 0
Hence general equation of circle is,
x² + y² - 8x - 6y = 0
so, we have two 54x18 rectangles, so their perimeter is simply all those units added together, 54+54+54+54+18+18+18+18 = 288.
we know the circle's diameter is 1.5 times the width, well, the width is 18, so the diameter of the circle must be 1.5*18 = 27.
![\bf \stackrel{\textit{circumference of a circle}}{C=d\pi }~~ \begin{cases} d=diameter\\[-0.5em] \hrulefill\\ d=27 \end{cases}\implies C=27\pi \implies C=\stackrel{\pi =3.14}{84.78} \\\\[-0.35em] ~\dotfill\\\\ \stackrel{\textit{perimeter of the rectangles}}{288}~~~~+~~~~\stackrel{\textit{perimeter of the circle}}{84.78}~~~~=~~~~372.78](https://tex.z-dn.net/?f=%5Cbf%20%5Cstackrel%7B%5Ctextit%7Bcircumference%20of%20a%20circle%7D%7D%7BC%3Dd%5Cpi%20%7D~~%20%5Cbegin%7Bcases%7D%20d%3Ddiameter%5C%5C%5B-0.5em%5D%20%5Chrulefill%5C%5C%20d%3D27%20%5Cend%7Bcases%7D%5Cimplies%20C%3D27%5Cpi%20%5Cimplies%20C%3D%5Cstackrel%7B%5Cpi%20%3D3.14%7D%7B84.78%7D%20%5C%5C%5C%5C%5B-0.35em%5D%20~%5Cdotfill%5C%5C%5C%5C%20%5Cstackrel%7B%5Ctextit%7Bperimeter%20of%20the%20rectangles%7D%7D%7B288%7D~~~~%2B~~~~%5Cstackrel%7B%5Ctextit%7Bperimeter%20of%20the%20circle%7D%7D%7B84.78%7D~~~~%3D~~~~372.78)
Can the numbers be repeted!!!!!!!!!!!!!!!!!!!!!!!!!
Answer:
The distribution of the sample data will approach a normal distribution as the sample size increases.
Step-by-step explanation:
Central limit theorem states that the mean of all samples from the same population will be almost equal to the mean of the population, if the large sample size from a population, is given with a finite level of variance.
So, here Option C is not correct conclusion of central limit theorem -The distribution of the sample data will approach a normal distribution as the sample size increases.
We can say that the average of sample mean tends to be normal but not the sample data.
