Out of a group of 120 students that were surveyed about winter sports 28 said they ski 53 said they snowboard Sixteen of the stu
2 answers:
Answer:
P ( snowboard I ski) = 0.5714
Step-by-step explanation:
Conditional Probability
We use the conditional probability formula to solve this question. It is
In which
P(B|A) is the probability of event B happening, given that A happened.
is the probability of both A and B happening.
P(A) is the probability of A happening.
In this question:
Event A: Ski
Event B: Snowboard.
28 out of 120 students ski:
This means that
16 out of 120 do both:
This means that
P ( snowboard I ski)
So
P ( snowboard I ski) = 0.5714
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Answer:
a) 87.49%
b) 2.72%
Step-by-step explanation:
Mean of the waist sizes = u = 32.6 inches
Standard Deviation of the waist sizes = = 1.3 inches
It is given that the Distribution is approximately Normal, so we can use the z-distribution to answer the given questions.
Part A) A male sailor whose waist is 34.1 inches is at what percentile
In order to find the percentile score of 34.1 we need to convert it into equivalent z-scores, and then find what percent of the value lie below that point.
So, here x = 34.1 inches
The formula for z score is:
Using the values in the above formula, we get:
Thus, 34.1 is equivalent to z score of 1.15
So,
P( X ≤ 34.1 ) = P( z ≤ 1.15 )
From the z-table we can find the probability of a z score being less than 1.15 to be: 0.8749
Thus, the 87.49 % of the values in a Normal Distribution are below the z score of 1.15. For our given scenario, we an write: 87.49% of the values lie below 34.1 inches.
Hence, the percentile rank of 34.1 inches is 87.49%
Part B)
The regular measure of waist sizes is from 30 to 36 inches. Any measure outside this range will need a customized order. We need to find that what percent of the male sailors will need a customized pant. This question can also be answered by using the z-distribution.
In a normal distribution, the overall percentage of the event is 100%. So if we find what percentage of values lie between 30 and 36, we can subtract that from 100% to obtain the percentage of values that are outside this range and hence will need customized pants.
First step is again to convert the values to z-scores.
30 converted to z scores will be:
36 converted to z score will be:
So,
P ( 30 ≤ X ≤ 36 ) = P ( -2 ≤ z ≤ 2.62 )
From the z table, we can find P ( -2 ≤ z ≤ 2.62 )
P ( -2 ≤ z ≤ 2.62 ) = P(z ≤ 2.62) - P(z ≤ -2)
P ( -2 ≤ z ≤ 2.62 ) = 0.9956 - 0.0228
P ( -2 ≤ z ≤ 2.62 ) = 0.9728
Thus, 97.28% of the values lie between the waist sizes of 30 and 36 inches. The percentage of the values outside this range will be:
100 - 97.28 = 2.72%
Thus, 2.72% of the male sailors will need custom uniform pants.
The given scenario is represented in the image below. The black portion under the curve represents the percentage of male sailors that will require custom uniform pants.
