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nekit [7.7K]
2 years ago
15

Rory works at a produce packing plant she packed 2172 strawberries last week and put them in a container with 8 strawberries in

each one how many containers of strawberries did Rory fill with 8 strawberries explains how you used the quotient and the remainder to awnser the question

Mathematics
1 answer:
mezya [45]2 years ago
8 0

Answer:

 Number of containers = 271

 Number of strawberries left = 4

Explanation:

Total number of strawberries = 2172.

Number of strawberries per container = 8

Number of strawberry container =  Total number of strawberries/Number of strawberries per container.

Number of strawberry container = 2172/8

 Refer the figure to see division,

 Number of containers = 271

 Number of strawberries left = 4                    

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Anna and Lionel share $675 in the ratio 4 : 5 Lionel gives 3/5 of his share of the money to his mother. How much money does Lion
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Answer:

$225

Step-by-step explanation:

Total share ratio = 4+5 = 9

Lionel's ratio = 5

Lionel's share = (5/9) × 675

                       = $375

Lionel's mum = (3/5) x 375

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7 0
1 year 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

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