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makkiz [27]
4 years ago
12

Help me please Jose has 9 more comic books than Robin. Robin has 5 more comic books than Lee. a. If Jose has 23 comic books, how

many comic books does Robin have? b. How many comic books does Lee have?
A. Robin has 14 comic books; Lee has 9 comic books

B. Robin has 14 comic books; Lee has 18 comic books

C. Robin has 32 comic books; Lee has 37 comic books

D. Robin has 9 comic books; Lee has 5 comic books
Mathematics
2 answers:
rodikova [14]4 years ago
8 0
<span>If Jose has 23 comic books, this means that Robin has 14 comic books because he has 9 more than her. This would also mean that Lee has 9 comic books because Robin has 5 more than him.</span>
SVETLANKA909090 [29]4 years ago
3 0

Answer with Step-by-step explanation:

We are given that:

Jose has 9 more comic books than Robin.

Robin has 5 more comic books than Lee.

Let number of comic books with Robin=x

Then number of comic books with Jose=x+9

and number of comic books with Lee=x-5

Jose has 23 comic books.

i.e. x+9=23

i.e. x=14

So, number of comic books with Robin=14

and number of comic books with Lee=9

Hence, correct option is:

A. Robin has 14 comic books; Lee has 9 comic books

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Answer:

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Step-by-step explanation:

Given the data in the question;

During a specific ten-hour period, one defective circuit board was found.

Lets X represent the number of defective circuit boards coming out of the machine , following Poisson distribution on a particular 10-hours workday which one defective board was found.

Also let Y represent the event of producing one defective circuit board, Y is uniformly distributed over ( 0, 10 ) intervals.

f(y) = \left \{ {{\frac{1}{b-a} }\\\ }} \right   _0;   ( a ≤ y ≤ b )_{elsewhere

= \left \{ {{\frac{1}{10-0} }\\\ }} \right   _0;   ( 0 ≤ y ≤ 10 )_{elsewhere

f(y) = \left \{ {{\frac{1}{10} }\\\ }} \right   _0;   ( 0 ≤ y ≤ 10 )_{elsewhere

Now,

a) the probability that it was produced during the first hour of operation during that period;

P( Y < 1 )   =   \int\limits^1_0 {f(y)} \, dy

we substitute

=    \int\limits^1_0 {\frac{1}{10} } \, dy

= \frac{1}{10} [y]^1_0

= \frac{1}{10} [ 1 - 0 ]

= \frac{1}{10} or 0.1000

Therefore, the probability that the defective board was produced during the first hour of operation is \frac{1}{10} or 0.1000

b) The probability that it was produced during the last hour of operation during that period.

P( Y > 9 ) =    \int\limits^{10}_9 {f(y)} \, dy

we substitute

=    \int\limits^{10}_9 {\frac{1}{10} } \, dy

= \frac{1}{10} [y]^{10}_9

= \frac{1}{10} [ 10 - 9 ]

= \frac{1}{10} or 0.1000

Therefore, the probability that the defective board was produced during the  last hour of operation is \frac{1}{10} or 0.1000

c)

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probability that the defective board was manufactured during the sixth hour will be;

P( 5 < Y < 6 | Y > 5 ) = P[ ( 5 < Y < 6 ) ∩ ( Y > 5 ) ] / P( Y > 5 )

= P( 5 < Y < 6 ) / P( Y > 5 )

we substitute

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= (\frac{1}{10} [y]^{6}_5) / (\frac{1}{10} [y]^{10}_5)

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