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KiRa [710]
3 years ago
10

PLEASE help I will mark you BRAINLIEST!!! ​

Mathematics
1 answer:
koban [17]3 years ago
8 0

Answer:

Use shell method

And chose the cross section perpendicular to the x-axis

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In reciprocal is the denominator one unit
docker41 [41]
Not always if you're saying it will always be something like 1/2 becomes 2/1 with a unit of one. It's just flipped, so 2/6 will be 6/2, 4/5 becomes 5/4, 22/16 becomes 16/22 etc. That is all there is to it. Make sure you simplify your answers.
5 0
4 years ago
Pleaseeeeee help I’m so confused
SSSSS [86.1K]

Answer:

4747

Step-by-step explanation:

8 0
3 years ago
Read 2 more answers
A normally distributed random variable with mean 4.5 and standard deviation 7.6 is sampled to get two independent values, X1 and
mr Goodwill [35]

Answer:

Bias for the estimator = -0.56

Mean Square Error for the estimator = 6.6311

Step-by-step explanation:

Given - A normally distributed random variable with mean 4.5 and standard deviation 7.6 is sampled to get two independent values, X1 and X2. The mean is estimated using the formula (3X1 + 4X2)/8.

To find - Determine the bias and the mean squared error for this estimator of the mean.

Proof -

Let us denote

X be a random variable such that X ~ N(mean = 4.5, SD = 7.6)

Now,

An estimate of mean, μ is suggested as

\mu = \frac{3X_{1} + 4X_{2}  }{8}

Now

Bias for the estimator = E(μ bar) - μ

                                    = E( \frac{3X_{1} + 4X_{2}  }{8}) - 4.5

                                    = \frac{3E(X_{1}) + 4E(X_{2})}{8} - 4.5

                                    = \frac{3(4.5) + 4(4.5)}{8} - 4.5

                                    = \frac{13.5 + 18}{8} - 4.5

                                    = \frac{31.5}{8} - 4.5

                                    = 3.9375 - 4.5

                                    = - 0.5625 ≈ -0.56

∴ we get

Bias for the estimator = -0.56

Now,

Mean Square Error for the estimator = E[(μ bar - μ)²]

                                                             = Var(μ bar) + [Bias(μ bar, μ)]²

                                                             = Var( \frac{3X_{1} + 4X_{2}  }{8}) + 0.3136

                                                             = \frac{1}{64} Var( {3X_{1} + 4X_{2}  }) + 0.3136

                                                             = \frac{1}{64} ( [{3Var(X_{1}) + 4Var(X_{2})]  }) + 0.3136

                                                             = \frac{1}{64} [{3(57.76) + 4(57.76)}]  } + 0.3136

                                                             = \frac{1}{64} [7(57.76)}]  } + 0.3136

                                                             = \frac{1}{64} [404.32]  } + 0.3136

                                                             = 6.3175 + 0.3136

                                                              = 6.6311

∴ we get

Mean Square Error for the estimator = 6.6311

6 0
3 years ago
What is Cameron's error??????
pogonyaev

Answer

Cameron forgot to do the same thing to the 9. Instead of dividing 3 by 3 and 9 by 3 he only divided 3 by 3.

Step-by-step explanation:

3/7 × 4/9

You can divide the 3 and 9 by 3 so you get 1/7 × 4/3.

Then you do 4 × 1 and 7 × 3.

Correct answer is 4/21

6 0
2 years ago
Btw the answer has to be in fraction form if it’s a decimal then we will need to convert it into a fraction please help me
Misha Larkins [42]

Answer:

217 = 217/100 = 2.17

Step-by-step explanation:

6 0
3 years ago
Read 2 more answers
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