Please help!!! 20 points

Is this true or false <br><br> grouping Addends will not change the sum

gregori [183]

Grouping addends will change the sum

3 0

3 years ago

Read 2 more answers

Find the perimeter of the square:

Anna [14]

By definition a square has all 4 sides equal, the area of a square is sxs or s^2, so s^2 = 400, s = square root of 400 = 20. All sides will be equal to 20 m. The perimeter is the sum of the sides or 4 x s or 80.

Steps:

A= L^2

Where L is length of the side

400=L^2 》》》》》 square root

L= 20 all sides of square are 20 m

P = 4L

=4(20)

=80m

7 0

3 years ago

<img src="https://tex.z-dn.net/?f=%20%7Bx%7D%5E%7B2%7D%20%2B%2016x%20%2B%2010%20%3D%200" id="TexFormula1" title=" {x}^{2} + 16x

Sergio039 [100]

Answer :-0.65 , -15.34

4 0

3 years ago

Suppose that the quarterly sales levels among health care information systems companies are approximately normally distributed w

jok3333 [9.3K]

Complete Question

The complete question is shown on the first uploaded image

Answer:

The sales level that is the cut-off between quarters that are considers as "failure" and those that are not is evaluated as

$y = 6.3 \ million \ dollars$

Step-by-step explanation:

From the question we are told that the

Mean is $\mu = 8 \ million \ dollars$

Standard deviation is $\sigma = 1.3 \ million \ dollars$

Let Y be the random variable that denotes the sales made quarterly among health care information system

The normal distribution for this data is mathematically represented as

$Y$ ~ N $(\mu = 8 , \sigma^2 = 1.69)$

From the question we are told that a quarter is consider a failure by the company if the sales level that quarter in the bottom 10% of the of all quarterly sales

So

The the Probability of obtaining quarterly sales level that is equal to 10% of all quarterly sale (It is not below 10%) is mathematically represented as

$P[Y < y ] = 0.10$

This can be represented as a normal distribution in this manner

$P [ \frac{Y- \mu}{\sigma } < \frac{y -\mu}{\sigma} ] = 0.10$

Where $\frac{Y - \mu }{\sigma } = Z$ ~ $N(0 , 1)$

{This mean that this equal to the normal distribution between 0, 1 which is the generally range of every probability }

Therefor we have

$P[Z < \frac{y- 8}{1.3} ]$

The cumulative distribution function for a normal distribution of y is mathematically represented as

$\phi [\frac{y- 8}{1.3} ] = 0.10$

This is because a cumulative distribution function of a random value Y or a distribution of Y evaluated at y is the probability that Y will take will take a value that is less or equal to y

$\frac{y- 8}{1.3} = \phi ^{-1}(0.10)$

Calculating the inverse of the cumulative distribution function value of 0.10 which is negative the the critical value(Critical values determine what probability a particular variable will have when a sampling distribution is normal or close to normal.) of 0.01

$\phi ^{-1}(0.10) =- [1 - \frac{0.10}{2}]$