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2 years ago

Pls help me i really am behind

Mathematics

1 answer:

Lemur [1.5K]2 years ago

5 0

Answer:

Step-by-step explanation:

(8-3^2)*9-6

8-9*9-6

-1*9-6

-9-6

-15

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Help me answer this question please

enot [183]

Figure D could be formed from the net.

(bottom right)

-Because-

The net says that the middle shape (the bottom face) is 14 long, and it is 8 tall. So the only option that makes sense is the bottom right!

<em>feel free to mark brainliest! :)</em>

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3 years ago

Geometry: The Expression 15×x×6 represents the volume of a rectangular prism with a length of 15, a width of x, and a height of

ziro4ka [17]

Step-by-step explanation:

$15 \times x \times 6 \\ \ \\ = 15 \times 6 \times x = 90x$

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3 years ago

If your car travels 270 miles and uses 9.2 gallons, how many miles per gallon did you get? (Round your answer to three decimal p

leva [86]

270 miles divide by 9.2
29.348 miles per gallon

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3 years ago

Read 2 more answers

Let X1, X2, ... , Xn be a random sample from N(μ, σ2), where the mean θ = μ is such that −[infinity] < θ < [infinity] and

Sliva [168]

Answer:

$l'(\theta) = \frac{1}{\sigma^2} \sum_{i=1}^n (X_i -\theta)$

And then the maximum occurs when $l'(\theta) = 0$ , and that is only satisfied if and only if:

$\hat \theta = \bar X$

Step-by-step explanation:

For this case we have a random sample $X_1 ,X_2,...,X_n$ where $X_i \sim N(\mu=\theta, \sigma)$ where $\sigma$ is fixed. And we want to show that the maximum likehood estimator for $\theta = \bar X$ .

The first step is obtain the probability distribution function for the random variable X. For this case each $X_i , i=1,...n$ have the following density function:

$f(x_i | \theta,\sigma^2) = \frac{1}{\sqrt{2\pi}\sigma} exp^{-\frac{(x-\theta)^2}{2\sigma^2}} , -\infty \leq x \leq \infty$

The likehood function is given by:

$L(\theta) = \prod_{i=1}^n f(x_i)$

Assuming independence between the random sample, and replacing the density function we have this:

$L(\theta) = (\frac{1}{\sqrt{2\pi \sigma^2}})^n exp (-\frac{1}{2\sigma^2} \sum_{i=1}^n (X_i-\theta)^2)$

Taking the natural log on btoh sides we got:

$l(\theta) = -\frac{n}{2} ln(\sqrt{2\pi\sigma^2}) - \frac{1}{2\sigma^2} \sum_{i=1}^n (X_i -\theta)^2$

Now if we take the derivate respect $\theta$ we will see this:

$l'(\theta) = \frac{1}{\sigma^2} \sum_{i=1}^n (X_i -\theta)$

And then the maximum occurs when $l'(\theta) = 0$ , and that is only satisfied if and only if:

$\hat \theta = \bar X$

6 0

3 years ago

Which complex number has an absolute value of 5?

defon

The answer would be -5

5 0

3 years ago