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LenaWriter [7]
3 years ago
13

HELPPP im running out of time hjhjhdkw

Mathematics
2 answers:
Eduardwww [97]3 years ago
6 0
It’ll be the bottom left
Anon25 [30]3 years ago
4 0

Answer:

lol put more points 8 too little bit

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If anyone needs help I Can help you
Nadya [2.5K]

I'll help. I love helping people

8 0
3 years ago
Which of the fractions below is closest to 7?
svetoff [14.1K]

Answer:

I think that the awnser is A because I think it is

6 0
2 years ago
Sam has three identical tennis balls with a diameter of 2.7 inches. Determine the volume of all three tennis balls?
melamori03 [73]

Answer:

They are 30.93 in³ altogether.

Step-by-step explanation: V = 4/3 π r³

r = 2.7/2 = 1.35

π x 1.35 x 1.35 x 4/3 = 10.31 in³

10.31 x 3 = 30.93

3 0
3 years ago
Five friends each knit one part of a scarf that is 11 yards long. 12 Which shows the fractions of the scarf each friend could ha
kotegsom [21]

Answer:

2/12 + 3/12 + 3/12 + 2/12 + 5/12

Step-by-step explanation:

I hope I'm right

3 0
3 years ago
Suppose a certain type of fertilizer has an expected yield per acre of mu 1 with variance sigma 2, whereas the expected yield fo
mart [117]

Answer:

See the proof below.

Step-by-step explanation:

For this case we just need to apply properties of expected value. We know that the estimator is given by:

S^2_p= \frac{(n_1 -1) S^2_1 +(n_2 -1) S^2_2}{n_1 +n_2 -2}

And we want to proof that E(S^2_p)= \sigma^2

So we can begin with this:

E(S^2_p)= E(\frac{(n_1 -1) S^2_1 +(n_2 -1) S^2_2}{n_1 +n_2 -2})

And we can distribute the expected value into the temrs like this:

E(S^2_p)= \frac{(n_1 -1) E(S^2_1) +(n_2 -1) E(S^2_2)}{n_1 +n_2 -2}

And we know that the expected value for the estimator of the variance s is \sigma, or in other way E(s) = \sigma so if we apply this property here we have:

E(S^2_p)= \frac{(n_1 -1 )\sigma^2_1 +(n_2 -1) \sigma^2_2}{n_1 +n_2 -2}

And we know that \sigma^2_1 = \sigma^2_2 = \sigma^2 so using this we can take common factor like this:

E(S^2_p)= \frac{(n_1 -1) +(n_2 -1)}{n_1 +n_2 -2} \sigma^2 =\sigma^2

And then we see that the pooled variance is an unbiased estimator for the population variance when we have two population with the same variance.

8 0
3 years ago
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