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N76 [4]
3 years ago
15

Bryson hopes to win a three-day vacation in a drawing that is being held at his office. He purchased 40 raffle tickets. There we

re 500 raffle tickets sold. What is the theoretical probability of Bryson winning the trip?
A-2/25

B-1/5

C-4/5

D-500/40
Mathematics
1 answer:
Savatey [412]3 years ago
9 0
The correct answer would be A, 2/25. 
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There 16 markers for every 2 boxes. Write a ratio for boxes to markers in the simplest from
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1:8

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What is 0.68 expressed as a fraction in simplest form? Both the 6 and the 8 repeat.
andreev551 [17]

Answer:

68/99

Step-by-step explanation:

.68686868686 repeating

Let x= .68686868668repeating

Multiply by 100

100x = 68.686868686repeating

Subtract x = .68686868repeating from this equation

100x = 68.686868686repeating

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------------------------------------------

99x = 68

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3 0
3 years ago
3. The Food Marketing Institute shows that 17% of households spend more than $100 per week on groceries. Assume the population p
damaskus [11]

Answer:

A)sample proportion = 0.17,  the sampling distribution of p can be calculated/approximated with normal distribution of sample proportion = 0.17 and standard error/deviation = 0.013281

B) 0.869

C)0.9668

Step-by-step explanation:

A) p ( proportion of population that spends more than $100 per week) = 0.17

sample size (n)= 800

the sample proportion of p = 0.17

standard error of p = \sqrt{\frac{p(1-p)}{n} } = 0.013281

the sampling distribution of p can be calculated/approximated with

normal distribution of sample proportion = 0.17 and standard error/deviation = 0.013281

B) probability that the sample proportion will be +-0.02 of the population proportion

= p (0.17 - 0.02 ≤ P ≤ 0.17 + 0.02 ) = p( 0.15 ≤ P ≤ 0.19)

z value corresponding to P

Z = \frac{P - p}{standard deviation}

at P = 0.15

Z =  (0.15 - 0.17) / 0.013281 = = -1.51

at P = 0.19

z = ( 0.19 - 0.17) / 0.013281 = 1.51

therefore the required probability will be

p( -1.5 ≤ z ≤ 1.5 ) = p(z ≤ 1.51 ) - p(z ≤ -1.51 )

                           = 0.9345 - 0.0655 = 0.869

C) for a sample (n ) = 1600

standard deviation/ error = 0.009391 (applying the equation for calculating standard error as seen in part A above)

therefore the required probability after applying

z = \frac{P-p}{standard deviation} at p = 0.15 and p = 0.19

p ( -2.13 ≤ z ≤ 2.13 ) = p( z ≤ 2.13 ) - p( z ≤ -2.13 )

                               = 0.9834 - 0.0166 = 0.9668

7 0
3 years ago
Read 2 more answers
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