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Paul [167]
3 years ago
8

Determine the next three terms in the following sentence 2, 3, 5, 8, _, _, _

Mathematics
2 answers:
Molodets [167]3 years ago
4 0
It would be 12,17,23 hope this helps you.
Veronika [31]3 years ago
3 0
12,16,21 it adds a number
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Whats the product of (-3x+2y)(4x-y)
oee [108]

Answer:

-12x^2 + 11xy - 2y^2

Step-by-step explanation:

5 0
3 years ago
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a carpet cost $15 per square foot. ( When calculating the price, any fraction of a square foot is counting as a whole square foo
gregori [183]
300 dollars, 15x20 because they count any fraction as a foot, so is like you are going to buy 20 foot of carpet.
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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
If the level of significance (alpha) is 0.05, it means that the probability of rejecting the null hypothesis, when it is false,
Kaylis [27]

Answer: The probability of rejecting the null hypothesis, when it is true, is 5%.

Step-by-step explanation:

We know that the level of significance ( denoted as \alpha ) is generally the probability of rejecting the null hypothesis when it is true.

Therefore , If the level of significance (\alpha[/tex] ) 0.05, then it means that it is the probability of rejecting the null hypothesis when it is true.

i.e. The probability of rejecting the null hypothesis when it is true= 0.05

In percent : 0.05=5\%

Hence, the correct option is : The probability of rejecting the null hypothesis when it is true is 5%.

4 0
3 years ago
Which is true regarding the graphed function f(x)
KiRa [710]

Answer:

Step-by-step explanation:

f(0) = 3

of(5) = -1

f(3) = 2

5

-3 -2 -14

1

2

3

4

5

f(2)= -2

5 0
2 years ago
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