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3 years ago

5

A ramp has a horizontal distance of 10 feet and a vertical rise of 3 feet. Find the length of the ramp. Round to the nearest ten

th.

1 answer:

Alona [7]3 years ago

5 0

Answer:Gygggyj

Step-by-step explanation:

You might be interested in

Changing the mean and standard deviation of a Normal distribution by a moderate amount can greatly change the percent of observa

sweet-ann [11.9K]

Answer:

a) $P(X>750)=P(\frac{X-\mu}{\sigma}>\frac{750-\mu}{\sigma})=P(Z1.798)$

$P(Z>1.798)=1-P(z$

f. 3.59 %

b) $P(X>750)=P(\frac{X-\mu}{\sigma}>\frac{750-\mu}{\sigma})=P(Z2.21)$

$P(Z>2.21)=1-P(Z$

d. 1.36 %

Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".

Part a

Let X the random variable that represent the scores of men of a population, and for this case we know the distribution for X is given by:

$X \sim N(527,124)$

Where $\mu=65.5$ and $\sigma=2.6$

We are interested on this probability

$P(X>750)$

And the best way to solve this problem is using the normal standard distribution and the z score given by:

$z=\frac{x-\mu}{\sigma}$

If we apply this formula to our probability we got this:

$P(X>750)=P(\frac{X-\mu}{\sigma}>\frac{750-\mu}{\sigma})=P(Z1.798)$

And we can find this probability using the complement rule and with the normal standard distribution table or excel:

$P(Z>1.798)=1-P(Z$

So then the correct answer for this case would be:

f. 3.59 %

Part b

Let X the random variable that represent the scores of women's of a population, and for this case we know the distribution for X is given by:

$X \sim N(496,115)$

Where $\mu=496$ and $\sigma=115$

We are interested on this probability

$P(X>750)$

And the best way to solve this problem is using the normal standard distribution and the z score given by:

$z=\frac{x-\mu}{\sigma}$

If we apply this formula to our probability we got this:

$P(X>750)=P(\frac{X-\mu}{\sigma}>\frac{750-\mu}{\sigma})=P(Z2.21)$

And we can find this probability using the complement rule and with the normal standard distribution table or excel:

$P(Z>2.21)=1-P(Z$

So then the correct answer for this case would be:

d. 1.36 %

7 0

3 years ago

I need help solving this problem. Thanks

Kamila [148]

9514 1404 393

Answer:

y = -4/7x +58/7

Step-by-step explanation:

The slope of the given line segment is ...

m = (y2 -y1)/(x2 -x1)

m = (17 -3)/(1 -(-7)) = 14/8 = 7/4

Then the slope of the perpendicular line is ...

-1/m = -4/7 . . . . . slope of the perpendicular bisector.

__

The midpoint of the given line segment is ...

M = 1/2(x1 +x2, y1 +y2)

M = (1/2)(-7 +1, 3 +17) = 1/2(-6, 20) = (-3, 10)

__

The y-intercept of the bisector can be found from ...

b = y -mx

b = 10 -(-4/7)(-3) = 10 -12/7 = 58/7

Then the slope-intercept form equation for the perpendicular bisector is ...

y = mx +b

y = -4/7x +58/7

6 0

3 years ago

Canadians who visit the United States often buy liquor and cigarettes, which are much cheaper in the United States. However, the

fenix001 [56]

Answer:

(a): Marginal pmf of x

$P(0) = 0.72$

$P(1) = 0.28$

(b): Marginal pmf of y

$P(0) = 0.81$

$P(1) = 0.19$

(c): Mean and Variance of x

$E(x) = 0.28$

$Var(x) = 0.2016$

(d): Mean and Variance of y

$E(y) = 0.19$

$Var(y) = 0.1539$

(e): The covariance and the coefficient of correlation

$Cov(x,y) = 0.0468$

$r \approx 0.2657$

Step-by-step explanation:

Given

<em>x = bottles</em>

<em>y = carton</em>

<em>See attachment for complete question</em>

<em />

Solving (a): Marginal pmf of x

This is calculated as:

$P(x) = \sum\limits^{}_y\ P(x,y)$

So:

$P(0) = P(0,0) + P(0,1)$

$P(0) = 0.63 + 0.09$

$P(0) = 0.72$

$P(1) = P(1,0) + P(1,1)$

$P(1) = 0.18 + 0.10$

$P(1) = 0.28$

Solving (b): Marginal pmf of y

This is calculated as:

$P(y) = \sum\limits^{}_x\ P(x,y)$

So:

$P(0) = P(0,0) + P(1,0)$

$P(0) = 0.63 + 0.18$

$P(0) = 0.81$

$P(1) = P(0,1) + P(1,1)$

$P(1) = 0.09 + 0.10$

$P(1) = 0.19$

Solving (c): Mean and Variance of x

Mean is calculated as:

$E(x) = \sum( x * P(x))$

So, we have:

$E(x) = 0 * P(0) + 1 * P(1)$

$E(x) = 0 * 0.72 + 1 * 0.28$

$E(x) = 0 + 0.28$

$E(x) = 0.28$

Variance is calculated as:

$Var(x) = E(x^2) - (E(x))^2$

Calculate $E(x^2)$

$E(x^2) = \sum( x^2 * P(x))$

$E(x^2) = 0^2 * 0.72 + 1^2 * 0.28$

$E(x^2) = 0 + 0.28$

$E(x^2) = 0.28$

So:

$Var(x) = E(x^2) - (E(x))^2$

$Var(x) = 0.28 - 0.28^2$

$Var(x) = 0.28 - 0.0784$

$Var(x) = 0.2016$

Solving (d): Mean and Variance of y

Mean is calculated as:

$E(y) = \sum(y * P(y))$

So, we have:

$E(y) = 0 * P(0) + 1 * P(1)$

$E(y) = 0 * 0.81 + 1 * 0.19$

$E(y) = 0+0.19$

$E(y) = 0.19$

Variance is calculated as:

$Var(y) = E(y^2) - (E(y))^2$

Calculate $E(y^2)$

$E(y^2) = \sum(y^2 * P(y))$

$E(y^2) = 0^2 * 0.81 + 1^2 * 0.19$

$E(y^2) = 0 + 0.19$

$E(y^2) = 0.19$

So:

$Var(y) = E(y^2) - (E(y))^2$

$Var(y) = 0.19 - 0.19^2$

$Var(y) = 0.19 - 0.0361$

$Var(y) = 0.1539$

Solving (e): The covariance and the coefficient of correlation

Covariance is calculated as:

$COV(x,y) = E(xy) - E(x) * E(y)$

Calculate E(xy)

$E(xy) = \sum (xy * P(xy))$

This gives:

$E(xy) = x_0y_0 * P(0,0) + x_1y_0 * P(1,0) +x_0y_1 * P(0,1) + x_1y_1 * P(1,1)$

$E(xy) = 0*0 * 0.63 + 1*0 * 0.18 +0*1 * 0.09 + 1*1 * 0.1$

$E(xy) = 0+0+0 + 0.1$

$E(xy) = 0.1$

So:

$COV(x,y) = E(xy) - E(x) * E(y)$

$Cov(x,y) = 0.1 - 0.28 * 0.19$

$Cov(x,y) = 0.1 - 0.0532$

$Cov(x,y) = 0.0468$

The coefficient of correlation is then calculated as:

$r = \frac{Cov(x,y)}{\sqrt{Var(x) * Var(y)}}$

$r = \frac{0.0468}{\sqrt{0.2016 * 0.1539}}$

$r = \frac{0.0468}{\sqrt{0.03102624}}$

$r = \frac{0.0468}{0.17614266944}$

$r = 0.26569371378$

$r \approx 0.2657$ --- approximated

8 0

2 years ago

Help pls!! I need help!!

AlladinOne [14]

Answer:

what u need help wt?

Step-by-step explanation:

6 0

3 years ago

1. Choose the appropriate symbol to make the following statment true. 0.586_0.568

exis [7]

Answer:

>

Step-by-step explanation:

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3 years ago