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svetlana [45]
3 years ago
5

What is the volume of this triangular prism?

Mathematics
1 answer:
Taya2010 [7]3 years ago
3 0

Answer:

243 because you need to multiply all those numbers then youll get your answer

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2x − 2) + (x + 1) + x + (x + 1) = (2x − 9) + (x + 1) + (x + 8) + x,
KengaRu [80]

Answer:

x=1

Step-by-step explanation:

5x=5x  x=1

4 0
3 years ago
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Marisha walks 8 miles in 5 days. If she walks at the same rate, how far
stiv31 [10]

Answer:

56 miles

Step-by-step explanation:

6 0
2 years ago
Three less than the product of 6 and a number is 45. What is the number?
strojnjashka [21]

Answer: 8

Step-by-step explanation:

6x-3=45

6x=48

x=8

5 0
2 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
Express in the form of p/q :<br><br> (i) 0.12▁3 (ii) 0. ▁621 (iii) 2.2▁18​
konstantin123 [22]

Answer:

1)0.123( bar on 3)

Let X = 0.123 ( bar on 3)

Then X = 0.1233 --------(1)

Multiply equation (1) by 100 we get,

100X = 12.33 --------(2)

Again multiply equation (2) by 10 we get,

1000X = 123.33 -------(3)

Subtract equation (2) from equation (3) we get,

1000X = 123.33

100X = 12.33

____________

900X = 111

X = 111/900

Hence,

0.123 ( bar on 3) is in the form of 111/900 which is in the form of P/Q.

6 0
3 years ago
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