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bixtya [17]
1 year ago
15

Aarti bought a square shaped table cloth for her home the side of the table cloth measures 2 1/3m what is the area of the table

cloth
Mathematics
1 answer:
PSYCHO15rus [73]1 year ago
3 0

Answer:

Area of table cloth =  49/9 m² or 5.44 m²

Step-by-step explanation:

Given:

Side of table cloth  = 2\frac{1}{3}m = 7/3 m

Shape of cloth is square

Find:

Area of table cloth

Computation:

Area of square = side²

So,

Area of table cloth = side²

Area of table cloth = (7/3)²

Area of table cloth =  49/9 m² or 5.44 m²

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Approximately 68% of a normal distribution lies within one standard deviation of the mean, so this corresponds to students with scores between (57.5 - 6.5, 57.5 + 6.5) = (51, 64)
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The table below represents Gerry's trip to school and back home. If the total time is 45 minutes, how far does Gerry live from s
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Which of the following are terms in the sum of the given polynomials? 3x2,-2x2y, 2xy2, 4y2, xy2, -y2,2x2y
vampirchik [111]
Create the sum of the given polynomial terms.
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3:       NO
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3y²:   YES
3xy²: YES
4x²:   NO

Answer:
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6 0
2 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
2 years ago
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