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serious [3.7K]
2 years ago
15

An automated egg carton loader has a 1% probability of cracking an egg, and a customer will complain if more than one egg per do

zen is cracked. Assume each egg load is an independent event.
(a) What is the distribution of cracked eggs per dozen ? Include parame-ter values.

(b) What is the probability that a carton of a dozen eggs results in more than one cracked egg ?

(c) Approximate the probability that among 100 dozen of eggs (i.e. 1200 eggs), there will be at most 1 cracked egg in total.

(d) What is the probability that we need more than 100 loaded eggs to observed a cracked egg?
Mathematics
1 answer:
vaieri [72.5K]2 years ago
5 0

Answer:

a) Binomial distribution B(n=12,p=0.01)

b) P=0.007

c) P=0.999924

d) P=0.366

Step-by-step explanation:

a) The distribution of cracked eggs per dozen should be a binomial distribution B(12,0.01), as it can model 12 independent events.

b) To calculate the probability of having a carton of dozen eggs with more than one cracked egg, we will first calculate the probabilities of having zero or one cracked egg.

P(k=0)=\binom{12}{0}p^0(1-p)^{12}=1*1*0.99^{12}=1*0.886=0.886\\\\P(k=1)=\binom{12}{1}p^1(1-p)^{11}=12*0.01*0.99^{11}=12*0.01*0.895=0.107

Then,

P(k>1)=1-(P(k=0)+P(k=1))=1-(0.886+0.107)=1-0.993=0.007

c) In this case, the distribution is B(1200,0.01)

P(k=0)=\binom{1200}{0}p^0(1-p)^{12}=1*1*0.99^{1200}=1* 0.000006 = 0.000006 \\\\ P(k=1)=\binom{1200}{1}p^1(1-p)^{1199}=1200*0.01*0.99^{1199}=1200*0.01* 0.000006 \\\\P(k=1)= 0.00007\\\\\\P(k\leq1)=0.000006+0.000070=0.000076\\\\\\P(k>1)=1-P(k\leq 1)=1-0.000076=0.999924

d) In this case, the distribution is B(100,0.01)

We can calculate this probability as the probability of having 0 cracked eggs in a batch of 100 eggs.

P(k=0)=\binom{100}{0}p^0(1-p)^{100}=0.99^{100}=0.366

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Scores on a biology final exam are normally distributed with a mean of 220 and a standard deviation of 16. Determine the percent
IrinaK [193]

Answer:

86.64%

Step-by-step explanation:

Mean (μ) = 220

σ= 16

n= 4

mean score(X) = 220 -12

= 208

Using central limit theorem which says that for a sample of size (n), the standard error is

standard deviation /√n

= 16/√4

= 16/2

= 8

Standard error = 8

Using Z score

Z = (μ - x) / standard error

Z= (220 -208)/8

Z= 12/8

Z= 1.5

From the table, Z = 1.5 = 0.4332

Since the normal distribution curve is symmetrical, we have

0.4332*2

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Percentage = 0.8664*100

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To babysit one child, Fernando charges $10 to drive to the appointment plus $4 per hour. He saves 30% of the total amount he ear
Kazeer [188]
Answer: 10 hours

Explanation:

1) Fernando's earnings:

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2) Fernando's savings

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3 + 1.2h ← distributive property

3) Brenna's earnings

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4) Brenna's savings

0.25(6h) ← 25% = 25/100 = 0.25

1.5h ←0.25 × 6 = 1.5

5) Equal savings

3 + 1.2h = 1.5h

1.5th- 1.2h = 3 ← transpose terms

0.3h = 3 ← combine like terms

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4 0
2 years ago
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Answer:

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Alenkasestr [34]

Answer: 6x^2+11

Step-by-step explanation:

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The Greatest Common Factor (GCF), is the highest number that divides into two or more numbers without leaving remainder.

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You can observe that the common factor that is missing from both sets of parentheses is:

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