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4 years ago

Proportional or Non-Proportional? y=4/5x

Mathematics

2 answers:

cluponka [151]4 years ago

6 0

You already got a really good answer on this same post

iVinArrow [24]4 years ago

5 0

Answer:

proportional

Step-by-step explanation:

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Kelly contracts with Raphael for Raphael to bring a pony to her daughter's birthday party in exchange for $100. Kelly later lear

Alex Ar [27]

Answer:

It was discharged by substituted contract

Step-by-step explanation:

In this situation, instead of simply canceling their original contract and terminating their interaction, Raphael and Kelly reached another agreement and stablished a substituted contract in place of the original one.

Therefore, the original agreement involving the pony and the $100 was discharged by substituted contract .

5 0

3 years ago

Three over X equals three or 4X +3

lina2011 [118]

Can’t understand please give the questions clear

5 0

3 years ago

What is the difference in the account balances shown below? Behrooz: (-$21.00) Cody: $3.00

suter [353]

Answer:

-7

Step-by-step explanation:

-21.00/3.00

4 0

3 years ago

What is the image of (0,6) after a dilation by a scale factor of 1/3

Pepsi [2]

Answer:

Step-by-step explanation:

What is the image of (0,6) after dilation by a scale factor of 1/3 centered at the origin

6 0

3 years ago

From past experience, a company has found that in carton of transistors: 92% contain no defective transistors 3% contain one def

jasenka [17]

Answer:

$E(X) = 0*0.92 + 1*0.03 +2*0.03 +3*0.02 = 0.1500$

In order to find the variance we need to find first the second moment given by:

$E(X^2) = \sum_{i=1}^n X^2_i P(X_i)$

And replacing we got:

$E(X^2) = 0^2*0.92 + 1^2*0.03 +2^2*0.03 +3^2*0.02 = 0.3300$

The variance is calculated with this formula:

$Var(X) = E(X^2) -[E(X)]^2 = 0.33 -(0.15)^2 = 0.3075$

And the standard deviation is just the square root of the variance and we got:

$Sd(X) = \sqrt{0.3075}= 0.5545$

Step-by-step explanation:

Previous concepts

The expected value of a random variable X is the n-th moment about zero of a probability density function f(x) if X is continuous, or the weighted average for a discrete probability distribution, if X is discrete.

The variance of a random variable X represent the spread of the possible values of the variable. The variance of X is written as Var(X).

Solution to the problem

LEt X the random variable who represent the number of defective transistors. For this case we have the following probability distribution for X

X 0 1 2 3

P(X) 0.92 0.03 0.03 0.02

We can calculate the expected value with the following formula:

$E(X) = \sum_{i=1}^n X_i P(X_i)$

And replacing we got:

$E(X) = 0*0.92 + 1*0.03 +2*0.03 +3*0.02 = 0.1500$

In order to find the variance we need to find first the second moment given by:

$E(X^2) = \sum_{i=1}^n X^2_i P(X_i)$

And replacing we got:

$E(X^2) = 0^2*0.92 + 1^2*0.03 +2^2*0.03 +3^2*0.02 = 0.3300$

The variance is calculated with this formula:

$Var(X) = E(X^2) -[E(X)]^2 = 0.33 -(0.15)^2 = 0.3075$

And the standard deviation is just the square root of the variance and we got:

$Sd(X) = \sqrt{0.3075}= 0.5545$

8 0

4 years ago