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3 years ago

Radical expression of 4d 3/8

Mathematics

1 answer:

DanielleElmas [232]3 years ago

8 0

Answer:

$\boxed{4 \sqrt[8]{ {d}^{3} } }$

Step-by-step explanation:

$= > 4 {d}^{ \frac{3}{8} } \\ \\ = > 4({d}^{3 \times \frac{1}{8} }) \\ \\ = > 4( {d}^{3} \times {d}^{ \frac{1}{8} } ) \\ \\ = > 4( {d}^{3} \times \sqrt[8]{d} ) \\ \\ = > 4 \sqrt[8]{ {d}^{3} }$

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Consider the simple linear regression model Yi=β0+β1xi+ϵi, where ϵi's are independent N(0,σ2) random variables. Therefore, Yi is

Virty [35]

Answer:

See proof below.

Step-by-step explanation:

If we assume the following linear model:

$y = \beta_o + \beta_1 X +\epsilon$

And if we have n sets of paired observations $(x_i, y_i) , i =1,2,...,n$ the model can be written like this:

$y_i = \beta_o +\beta_1 x_i + \epsilon_i , i =1,2,...,n$

And using the least squares procedure gives to us the following least squares estimates $b_o$ for $\beta_o$ and $b_1$ for $\beta_1$ :

$b_o = \bar y - b_1 \bar x$

$b_1 = \frac{s_{xy}}{s_xx}$

Where:

$s_{xy} =\sum_{i=1}^n (x_i -\bar x) (y-\bar y)$

$s_{xx} =\sum_{i=1}^n (x_i -\bar x)^2$

Then $\beta_1$ is a random variable and the estimated value is $b_1$ . We can express this estimator like this:

$b_1 = \sum_{i=1}^n a_i y_i$

Where $a_i =\frac{(x_i -\bar x)}{s_{xx}}$ and if we see careful we notice that $\sum_{i=1}^n a_i =0$ and $\sum_{i=1}^n a_i x_i =1$

So then when we find the expected value we got:

$E(b_1) = \sum_{i=1}^n a_i E(y_i)$

$E(b_1) = \sum_{i=1}^n a_i (\beta_o +\beta_1 x_i)$

$E(b_1) = \sum_{i=1}^n a_i \beta_o + \beta_1 a_i x_i$

$E(b_1) = \beta_1 \sum_{i=1}^n a_i x_i = \beta_1$

And as we can see $b_1$ is an unbiased estimator for $\beta_1$

In order to find the variance for the estimator $b_1$ we have this:

$Var(b_1) = \sum_{i=1}^n a_i^2 Var(y_i) +\sum_i \sum_{j \neq i} a_i a_j Cov (y_i, y_j)$

And we can assume that $Cov(y_i,y_j) =0$ since the observations are assumed independent, then we have this:

$Var (b_1) =\sigma^2 \frac{\sum_{i=1}^n (x_i -\bar x)^2}{s^2_{xx}}$

And if we simplify we got:

$Var(b_1) = \frac{\sigma^2 s_{xx}}{s^2_{xx}} = \frac{\sigma^2}{s_{xx}}$

And with this we complete the proof required.

8 0

4 years ago

How many eighth notes do you need to total the amount of a half note

andrew11 [14]

Answer:

Four eighth notes

Four eighth notes equal one half note in duration and eight eighth notes equal one whole note.

Step-by-step explanation:

Hope this helps, If it did, then I would really appreciate it if you gave me Brainliest, I only need one more to rank up and it has taken forever to get to where I am currently. Thanks.

8 0

3 years ago

From stations A and B, the distance between which is 910 mi,

Firdavs [7]

Answer:

<em>The slowest train goes at 86 mph and the fastest train goes at 96 mph.</em>

Step-by-step explanation:

<u>Distance and Speed</u>

Assume x is the speed of the slowest train, therefore the speed of the fastest train is x+10.

The distance is calculated as:

d = vt

Where v is the speed and t is the time.