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3 years ago

PLEASE HELP ME QUICK PLEASE!!!!!!

Mathematics

1 answer:

gayaneshka [121]3 years ago

3 0

Only constraint 2 would be met if 9 vanilla cups and 18 chocolate cups were purchased

Only constraint 1 would be met if 6 vanilla cups and 18 chocolate cups were purchased

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Solve the equation by taking the square root 4(x+1)^2=100

Naddika [18.5K]

Answer:

Step-by-step explanation:

4(x+1)²=100

(x+1)²= 5²

(x+1)²- 5² = 0

(x+1-5)(x+1+5) = 0 by identity : a² - b ² = (a - b) (a+b)

(x - 4 ) (x+6) =0

x - 4 = 0 or x+6 = 0

x = 4 or x = - 6

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3 years ago

Paul's car is 13 feet long. He is making a model of his car that is the actual size. What is the length of the model?

hram777 [196]

I believe the length of Paul's model is C, 13/6 feet

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3 years ago

How can I calculate a certain decimal given a length? Let's say n is a decimal, and I want that decimal to be a length of 3. The

xeze [42]

N /(n*10^n)
So 3 would be
3/(3×1000)=1/1000=.001

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3 years ago

What percent of 300 is 51?

natita [175]

Is 250 basically in 50 but the percentage of the 100 is 50% of the hundred right does that mean in this question it would have to be 250 is half of 300

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3 years ago

Kelsie works at a bicycle shop as a salesperson. She records the number of bicycles she sells daily. Here is the probability dis

Andru [333]

Answer:

a) $E(B)= \sum_{i=1}^n B_i P(B_i) =0*0.3+1*0.5+2*0.15+ 3*0.05=0.95$

b) $E(T)= \sum_{i=1}^n T_i P(T_i) =10*0.3+20*0.5+30*0.15+ 40*0.05=19.5$

c) $E(B^2)= \sum_{i=1}^n B^2_i P(B_i) =0^2 *0.3+1^2 *0.5+2^2 *0.15+ 3^2 *0.05=1.55$

And the variance is given by:

$Var(B) = E(B^2) -[E(B)]^2 = 1.55- [0.95]^2 =0.6475$

And the deviation would be $Sd(B) = \sqrt{0.6475}=0.8047$

$E(T^2)= \sum_{i=1}^n T^2_i P(T_i) =10^2 *0.3+20^2 *0.5+30^2 *0.15+ 40^2 *0.05=445$

And the variance is given by:

$Var(T) = E(T^2) -[E(T)]^2 = 445- [19.5]^2 =64.75$

And the deviation would be $Sd(T) = \sqrt{64.75}=8.047$

Step-by-step explanation:

Previous concepts

In statistics and probability analysis, the expected value "is calculated by multiplying each of the possible outcomes by the likelihood each outcome will occur and then summing all of those values".

The variance of a random variable Var(X) is the expected value of the squared deviation from the mean of X, E(X).

And the standard deviation of a random variable X is just the square root of the variance.

Solution to the problem

Part a

For this case we have the following info:

B 0 1 2 3

____________________________________

T 10 20 30 40

____________________________________

P 0.3 0.5 0.15 0.05

____________________________________

And we can calculate the expected value for the random variable B like this:

$E(B)= \sum_{i=1}^n B_i P(B_i) =0*0.3+1*0.5+2*0.15+ 3*0.05=0.95$

Part b

Similar to part a we can find the expected value for the random variable T like this:

$E(T)= \sum_{i=1}^n T_i P(T_i) =10*0.3+20*0.5+30*0.15+ 40*0.05=19.5$

Part c

In order to find the variance for B we need to calculate the second moment given by:

$E(B^2)= \sum_{i=1}^n B^2_i P(B_i) =0^2 *0.3+1^2 *0.5+2^2 *0.15+ 3^2 *0.05=1.55$

And the variance is given by:

$Var(B) = E(B^2) -[E(B)]^2 = 1.55- [0.95]^2 =0.6475$

And the deviation would be $Sd(B) = \sqrt{0.6475}=0.8047$

Similar for the random variable T we have:

$E(T^2)= \sum_{i=1}^n T^2_i P(T_i) =10^2 *0.3+20^2 *0.5+30^2 *0.15+ 40^2 *0.05=445$

And the variance is given by:

$Var(T) = E(T^2) -[E(T)]^2 = 445- [19.5]^2 =64.75$

And the deviation would be $Sd(B) = \sqrt{64.75}=8.047$

7 0

4 years ago