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Harman [31]
4 years ago
8

The amount of money in your bank account is $512.18. Is the data type discrete or continuous?

Mathematics
1 answer:
docker41 [41]4 years ago
7 0
<u><em>Answer:</em></u>
<span>It is discrete because there are a finite number of possible values.

<u><em>Explanation:</em></u>
<u>Discrete data </u>is a type of data that can take possible values only such as the number of students in class, the number of bags you have, the number of quizzes a student took during a week, .... etc

<u>Continuous data</u> is a type of data that falls within a range such as the weight, height, ..... etc

<u>In the question</u>, we are given that the bank account has exactly </span><span>$512.18
This is an exact value that has only one possibility and is not subjected to a range of values

Therefore, this is a discrete data type as it has only one value

Hope this helps :)</span>
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In the transmission of digital information, the probability that a bit has high, moderate, and low distortion is 0.02, 0.07, and
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A. (Table Attached)

B. (See Step 3)

C. 0.06 (See Step 4)

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Step-by-step explanation:

<h3 /><h3>STEP 1:</h3>

Name the probabilities:

p₁ = 0.02,   p₂ = 0.07,   p₃ = 0.91

q₁ = 1-p₁ = 0.98 ,   q₂ = 1-p₂ = 0.93 ,   q₃ = 0.09

Let X and Y be the number of bits with high and moderate distortion out of three.

<h3>STEP 2:</h3>

A.

The function will follow multinomial distribution:

f_{XY}(x,y) = P(X=x, Y=y) = \frac{3!}{x!y!(3-x-y)!} (p_1^x)(p_2^y)(p_3^{3-x-y})

Substitute the values and make a table.

TABLE IN ATTACHMENT

<h3>STEP 3:</h3>

B.

We calculate marginal distribution by:

P (X=x)= <em>∑</em> P(X=x,Y=y)

fx(x) can be found by adding all the probabilities in each row for different value of X

For X=0 , ∑P = 0.94157441

For X=1 , ∑P = 0.057624

For X=2 , ∑P = 0.001176

For X=3 , ∑P =0.000008

<h3>STEP 4:</h3><h3>C.</h3>

The mathematic expectation E is the sum of product of each possibility with its probabiity.

E(X)=<em>∑ </em>xP(X=x)

Find E(X):

E(X)= (0*0.9415744)+(1*0.057624)+(2*0.001176)+(3*0.000008)

E(X)=0.06

<h3>STEP 5:</h3>

Condition probability states:

P(A|B)=\frac{P(A,B)}{P(B)}

It can also be written as:

f_{Y|X=1}(y)=\frac{f_{XY}(1,y)}{f_x(1)}

Where f_x(1)\\ = 0.057624

Calculate the quotient:

Y|_{x=1} = 0 ,  f_{Y|_X=1 = 0.862245

Y|_{x=1} = 1 ,  f_{Y|_X=1 = 0.132653

Y|_{x=1} = 2 ,  f_{Y|_X=1 = 0.000510

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Find the dependency:

f_{XY}(y)=f_X(x)f_Y(y)

We found that

f_{Y|_X=1 = 0.862245

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Which are not equal.

Conclusion:

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