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Fantom [35]
3 years ago
11

Probability check point 6 , you have a bag containing 2 red balls, 4 green balls, and 5 purple balls. you draw one ball from the

bag: it's green. call this draw 0. keep this ball and continue drawing (without replacement) until you get another green ball. call these draws 1, 2...k. what is the probability that you don't draw another green ball until draw 3
Mathematics
1 answer:
natta225 [31]3 years ago
8 0
There are now 10 balls in the bag since you took 1 green out
There are now 3 greens in the bag
3/10 is the chance you pick a green,so 7/10 is the chance you DIDNT pick a green ball for the first round
Second round:-1 ball that is not green now the number of ball is 9
10+9=19

(# of green balls still in the bag)3/19 final answer 
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In studies for a​ medication, 3 percent of patients gained weight as a side effect. Suppose 643 patients are randomly selected.
timofeeve [1]

Part a)

It was given that 3% of patients gained weight as a side effect.

This means

p = 0.03

q = 1 - 0.03 = 0.97

The mean is

\mu  = np

\mu = 643 \times 0.03 = 19.29

The standard deviation is

\sigma =  \sqrt{npq}

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We want to find the probability that exactly 24 patients will gain weight as side effect.

P(X=24)

We apply the Continuity Correction Factor(CCF)

P(24-0.5<X<24+0.5)=P(23.5<X<24.5)

We convert to z-scores.

P(23.5 \: < \: X \: < \: 24.5) = P( \frac{23.5 - 19.29}{4.33} \: < \: z \: < \:  \frac{24.5 - 19.29}{4.33} ) \\  = P( 0.97\: < \: z \: < \:  1.20) \\  = 0.051

Part b) We want to find the probability that 24 or fewer patients will gain weight as a side effect.

P(X≤24)

We apply the continuity correction factor to get;

P(X<24+0.5)=P(X<24.5)

We convert to z-scores to get:

P(X \: < \: 24.5) = P(z \: < \:  \frac{24.5 - 19.29}{4.33} )  \\ =   P(z \: < \: 1.20)  \\  = 0.8849

Part c)

We want to find the probability that

11 or more patients will gain weight as a side effect.

P(X≥11)

Apply correction factor to get:

P(X>11-0.5)=P(X>10.5)

We convert to z-scores:

P(X \: > \: 10.5) = P(z \: > \:  \frac{10.5 - 19.29}{4.33} )  \\ = P(z \: > \:  - 2.03)

= 0.9788

Part d)

We want to find the probability that:

between 24 and 28, inclusive, will gain weight as a side effect.

P(24≤X≤28)=

P(23.5≤X≤28.5)

Convert to z-scores:

P(23.5  \:  <  \: X \:  <  \: 28.5) = P( \frac{23.5 - 19.29}{4.33}   \:  <  \: z \:  <  \:  \frac{28.5 - 19.29}{4.33} ) \\  = P( 0.97\:  <  \: z \:  <  \: 2.13) \\  = 0.1494

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Answer:

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Step-by-step explanation:

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