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mel-nik [20]
3 years ago
14

Find the domain and range of each relation. Then determine if the relation is a function. (5,0),(6,-2),(7,10),(8,-3)

Mathematics
1 answer:
leonid [27]3 years ago
3 0

Answer:

Domain: 5, 6, 7, 8

Range: 0, -2, 10, -3

The relation is a function because each x-value has its own y-value.

Step-by-step explanation:

Domain: Set of all first elements in relation

Range: Set of all second elements in relation

How to determine if the relations is a function:

1. Identify the input values.

2. Identify the output values.

3. If each input value leads to only one output value, classify the relationship as a function.

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x=16

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The price of an item has increased 15% since last year. However, a person can buy the item for a 25% employee discount. The empl
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Answer: $200

Explanation:

The employee pays $172.50 and he got 25% employee discount.

If the cost is $100, he pays $(100 - 25) = $75.

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172.50

= $230.00.

Again, price was increased by 15% last year. So whose cost is $100

is sold by $(100+15) = $115.

When sell price is $115, then cost price is $100. Then,

when sell price is $230, then cost price is  

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5 0
3 years ago
Three teachers share 2 packs of paper equally.
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a mixture of 40 liters of paint is 25% red tint, 30% yellow tint and 45% water. 6 liters of yellow tint are added to the origina
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5 0
3 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
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