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Ymorist [56]
3 years ago
12

What does the factor is 3 that both 3x and 18 have in common.

Mathematics
1 answer:
Arlecino [84]3 years ago
4 0
3 goes into both 3x and 18

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P(x) --->p(x+6)+3 ? what would the graph look like?
Setler79 [48]
<span>given that P(x) --->p(x+6)+3
</span>
∴ x will become x+6
and P(x+6) will become P(x+6)+3
<span />
So, The graph of [p(x+6)+3] will be the same as the graph of [p(x)] but shifted 6 units to the left then shifted 3 units up
OR by another words, we need to make axis translations from (0,0) to (-6,3)

5 0
3 years ago
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
Please help&gt;&gt;&gt;&gt;&gt;&gt;&gt;&gt;&gt;&gt;&gt;&gt;&gt;&gt;&gt;&gt;
Annette [7]

Answer:

The answer is B, -5 is a rational number and integer! :)

Step-by-step explanation:

6 0
2 years ago
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solniwko [45]

Answer: The answer is 62.32

Step-by-step explanation:

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6 0
3 years ago
Find the perimeter of the figure to the nearest hundredth.
MariettaO [177]

Answer:

Step-by-step explanation:

7 0
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