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3 years ago

Ella has 50 stacks of ten pennies in each stack. Describe how to find how many pennies Ella has it all.

Mathematics

2 answers:

bagirrra123 [75]3 years ago

6 0

In each (1) stack, Ella has --> 10 pennies.
Then in 50 stacks, Ella will have --> 10 x 50 = 500 pennies.

Softa [21]3 years ago

5 0

You would multiply 50 by ten to get 500 pennies.

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First 8 is added to me , then j am multiplied by 6.then 40 is subtracted from me .Finally I am divided by 10. The result is 11.

alexdok [17]

11x10=110
110+40=150
150/6=25
25-8=17
17 is the number.

4 0

2 years ago

Graph this inequality:<br> y ≤ 1/4x

Leviafan [203]

Graph this inequality:

8 0

2 years ago

Please help me with this

sesenic [268]

Ok so the average is 50

average of x number of things is
(add value of all things)/x=average

4 test scores needed
so divide by 4
3 test scores ar known
average is 50
x= missing score

(43+48+42+x)/4=50
times 4 both sides
133+x=200
minus 133 both sides
x=67

a score of 67 is needed

5 0

2 years ago

Determine whether a probability distribution is given. If a probability distribution is given, find its mean and standard deviat

drek231 [11]

Answer:

$E(X) = \sum_{i=1}^n X_i P(X_i) = 0*0.031 +1*0.156+ 2*0.313+3*0.313+ 4*0.156+ 5*0.031 = 2.5$

We can find the second moment given by:

$E(X^2) = \sum_{i=1}^n X^2_i P(X_i) = 0^2*0.031 +1^2*0.156+ 2^2*0.313+3^2*0.313+ 4^2*0.156+ 5^2*0.031 =7.496$

And we can calculate the variance with this formula:

$Var(X) =E(X^2) -[E(X)]^2 = 7.496 -(2.5)^2 = 1.246$

And the deviation is:

$Sd(X) = \sqrt{1.246}= 1.116$

Step-by-step explanation:

For this case we have the following probability distribution given:

X 0 1 2 3 4 5

P(X) 0.031 0.156 0.313 0.313 0.156 0.031

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).

We can verify that:

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

And $P(X_i) \geq 0, \forall x_i$

So then we have a probability distribution

We can calculate the expected value with the following formula:

$E(X) = \sum_{i=1}^n X_i P(X_i) = 0*0.031 +1*0.156+ 2*0.313+3*0.313+ 4*0.156+ 5*0.031 = 2.5$

We can find the second moment given by:

$E(X^2) = \sum_{i=1}^n X^2_i P(X_i) = 0^2*0.031 +1^2*0.156+ 2^2*0.313+3^2*0.313+ 4^2*0.156+ 5^2*0.031 =7.496$

And we can calculate the variance with this formula:

$Var(X) =E(X^2) -[E(X)]^2 = 7.496 -(2.5)^2 = 1.246$

And the deviation is:

$Sd(X) = \sqrt{1.246}= 1.116$

6 0

3 years ago

Jim bought a fishing rod for $42. This price was 70% of the original price. What was the original price?

Dmitry [639]

Answer:

54.6

Step-by-step explanation:

42 = 70%

100% - 70% = .30%

42 x 1.3 = 54.6

5 0

2 years ago