The point (-3, 4) is translated 1 by the vector to the point (1 ( 5)

Explain how you can use base-ten blocks or as a decimal models to find 3.15 divided by 3. Include pictures to support your expla

AlladinOne [14]

You have to turn the number or ratio and simplified the number and put it in to the chart like the norm number

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5 0

3 years ago

A squirrel is 5.0 m away from you while moving at a constant velocity of 3m/s away from you. How far away is the squirrel after

Vladimir [108]

20 meters away.......

5 0

2 years ago

ANYONE IM RUNNING OUT OF TIME!!!!!

adelina 88 [10]

Answer:

Y= -5/2x+3

Step-by-step explanation:

A perpendicular slope is always opposite (meaning if the original is negative, then it is positive and vice versa) and reciprocal (meaning the numerator and denominator of the original are flipped).

The y intercept I found by applying the slope to the point given.

8 0

2 years ago

Read 2 more answers

A filtration process removes a random proportion of particulates in water to which it is applied. Suppose that a sample of water

Doss [256]

Answer:

$E(Y)=\frac{1}{25}$

Step-by-step explanation:

Let's start defining the random variables for this exercise :

$X_{1}:$ '' The proportion of the particulates that are removed by the first pass ''

$X_{2}:$ '' The proportion of what remains after the first pass that is removed by the second pass ''

$Y:$ '' The proportion of the original particulates that remain in the sample after two passes ''

We know the relation between the random variables :

$Y=(1-X_{1})(1-X_{2})$

We also assume that $X_{1}$ and $X_{2}$ are independent random variables with common pdf.

The probability density function for both variables is $f(x)=4x^{3}$ for $0$ and $f(x)=0$ otherwise.

The first step to solve this exercise is to find the expected value for $X_{1}$ and $X_{2}$ .

Because the variables have the same pdf we write :

$E(X_{1})= E(X_{2})=E(X)$

Using the pdf to calculate the expected value we write :

$E(X)=\int\limits^a_b {xf(x)} \, dx$

Where $a=$ ∞ and $b=$ - ∞ (because we integrate in the whole range of the random variable). In this case, we will integrate between $0$ and $1$ ⇒

Using the pdf we calculate the expected value :

$E(X)=\int\limits^1_0 {x4x^{3}} \, dx=\int\limits^1_0 {4x^{4}} \, dx=\frac{4}{5}$

⇒ $E(X)=E(X_{1})=E(X_{2})=\frac{4}{5}$

Now we need to use some expected value properties in the expression of $Y$ ⇒

$Y=(1-X_{1})(1-X_{2})$ ⇒

$Y=1-X_{2}-X_{1}+X_{1}X_{2}$

Applying the expected value properties (linearity and expected value of a constant) ⇒

$E(Y)=E(1)-E(X_{2})-E(X_{1})+E(X_{1}X_{2})$

Using that $X_{1}$ and $X_{2}$ have the same expected value $E(X)$ and given that $X_{1}$ and $X_{2}$ are independent random variables we can write $E(X_{1}X_{2})=E(X_{1})E(X_{2})$ ⇒