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atroni [7]
1 year ago
11

The time needed to complete a final examination in a particular college course is normally distributed with a mean of 79 minutes

and a standard deviation of 8 minutes. Answer the following questions. a. What is the probability of completing the exam in one hour or less (to 4 decimals)? b. What is the probability that a student will complete the exam in more than minutes but less than minutes (to 4 decimals)? c. Assume that the class has students and that the examination period is minutes in length. How many students do you expect will be unable to complete the exam in the allotted time (to nearest whole number)?
Mathematics
1 answer:
Jlenok [28]1 year ago
8 0

Answer:

a) P(x ≤ 60) = 0.0087

b) P(60 < x < 75) = 0.3009

c) About 6 students will be unable to finish the exam in the allotted time

Step-by-step explanation:

This is a normal distribution problem with

Mean = μ = 79 minutes

Standard deviation = σ = 8 minutes.

a) The probability of completing the exam in one hour or less. P(x ≤ 60)

We first standardize/normalize 60 minutes

The standardized score for any value is the value minus the mean then divided by the standard deviation.

z = (x - μ)/σ = (60 - 79)/8 = - 2.38

To determine the probability of completing the exam in one hour or less.

P(x ≤ 60) = P(z ≤ -2.38)

We'll use data from the normal probability table for these probabilities

P(x ≤ 60) = P(z ≤ -2.38) = 0.00866 = 0.0087 to 4d.p

b) The probability that a student will complete the exam in more than 60 minutes but less than 75 minutes. P(60 < x < 75)

We first standardize/normalize 60 and 75 minutes

For 60 minutes

z = (x - μ)/σ = (60 - 79)/8 = - 2.38

For 75 minutes

z = (x - μ)/σ = (75 - 79)/8 = - 0.50

To determine the probability that a student will complete the exam in more than 60 minutes but less than 75 minutes.

P(60 < x < 75) = P(-2.38 < z < -0.50)

We'll use data from the normal probability table for these probabilities

P(60 < x < 75) = P(-2.38 < z < -0.50)

= P(z < -0.50) - P(z < -2.38)

= 0.30954 - 0.00866

= 0.30088 = 0.3009

c. Assume that the class has 60 students and that the examination period is 90 minutes in length. How many students do you expect will be unable to complete the exam in the allotted time?

Probability of finishing in 90 minutes or less = P(x ≤ 90)

We first standardize/normalize 90 minutes

z = (x - μ)/σ = (90 - 79)/8 = 1.38

To determine the probability of completing the exam in 90 minutes or less.

P(x ≤ 90) = P(z ≤ 1.38)

We'll use data from the normal probability table for these probabilities

P(x ≤ 90) = P(z ≤ 1.38) = 0.91621

This means 91.621% of the class will finish just in time.

91.621% × 60 = 54.97 ≈ 54 (we can't round the number up because it represents number of students that finish in time and rounding a 0.97 to a 1 makes the analysis wrong)

About 54 students will finish in time.

Meaning about 6 students will be unable to finish the exam in the allowed time.

Hope this Helps!!!

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Answer:

50

Step-by-step explanation:

Steven = 13 marbles

Julio = 13 marbles

Megan has twice the number of marbles as Steven and Julio combined

Megan = 2 (13 + 13) = 2(26) = 52 marbles

Among the options (26, 13, 50, 169, 338), the only reasonable estimate is 50

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2 years ago
Show all your work. Indicate clearly the methods you use, because you will be scored on the correctness of your methods as well
Aleks04 [339]

The question is incomplete! Complete question along with answer and step by step explanation is provided below.

Question:

Miguel is a golfer, and he plays on the same course each week. The following table shows the probability distribution for his score on one particular hole, known as the Water Hole.  

Score 3 4 5 6 7

Probability 0.15 0.40 0.25 0.15 0.05

Let the random variable X represent Miguel’s score on the Water Hole. In golf, lower scores are better.

(a) Suppose one of Miguel’s scores from the Water Hole is selected at random. What is the probability that Miguel’s score on the Water Hole is at most 5 ? Show your work.

(b) Calculate and interpret the expected value of X . Show your work.

A potential issue with the long hit is that the ball might land in the water, which is not a good outcome. Miguel thinks that if the long hit is successful, his expected value improves to 4.2. However, if the long hit fails and the ball lands in the water, his expected value would be worse and increases to 5.4.

c) Suppose the probability of a successful long hit is 0.4. Which approach, the short hit or long hit, is better in terms of improving the expected value of the score?

(d) Let p represent the probability of a successful long hit. What values of p will make the long hit better than the short hit in terms of improving the expected value of the score? Explain your reasoning.

Answer:

a) 80%

b) 4.55

c) 4.92

d) P > 0.7083

Step-by-step explanation:

Score  |   Probability

3          |      0.15

4          |      0.40

5          |      0.25

6          |      0.15

7          |      0.05

Let the random variable X represents Miguel’s score on the Water Hole.

a) What is the probability that Miguel’s score on the Water Hole is at most 5 ?

At most 5 means scores which are equal or less than 5

P(at most 5) = P(X ≤ 5) = P(X = 3) + P(X = 4) + P(X = 5)

P(X ≤ 5) = 0.15 + 0.40 + 0.25

P(X ≤ 5) = 0.80

P(X ≤ 5) = 80%

Therefore, there is 80% chance that Miguel’s score on the Water Hole is at most 5.

(b) Calculate and interpret the expected value of X.

The expected value of random variable X is given by

E(X) = X₃P₃ + X₄P₄ + X₅P₅ + X₆P₆ + X₇P₇

E(X) = 3*0.15 + 4*0.40 + 5*0.25 + 6*0.15 + 7*0.05

E(X) = 0.45 + 1.6 + 1.25 + 0.9 + 0.35

E(X) = 4.55

Therefore, the expected value of 4.55 represents the average score of Miguel.

c) Suppose the probability of a successful long hit is 0.4. Which approach, the short hit or long hit, is better in terms of improving the expected value of the score?

The probability of a successful long hit is given by

P(Successful) = 0.40

The probability of a unsuccessful long hit is given by

P(Unsuccessful) = 1 - P(Successful)

P(Unsuccessful) = 1 - 0.40

P(Unsuccessful) = 0.60

The expected value of successful long hit is given by

E(Successful) = 4.2

The expected value of Unsuccessful long hit is given by

E(Unsuccessful) = 5.4

So, the expected value of long hit is,

E(long hit) = P(Successful)*E(Successful) + P(Unsuccessful)*E(Unsuccessful)

E(long hit) = 0.40*4.2 + 0.60*5.4

E(long hit) = 1.68 + 3.24

E(long hit) = 4.92

Since the expected value of long hit is 4.92 which is greater than the value of short hit obtained in part b that is 4.55, therefore, it is better to go for short hit rather than for long hit. (Note: lower expected score is better)

d) Let p represent the probability of a successful long hit. What values of p will make the long hit better than the short hit in terms of improving the expected value of the score?

The expected value of long hit is given by

E(long hit) = P(Successful)*E(Successful) + P(Unsuccessful)*E(Unsuccessful)

E(long hit) = P*4.2 + (1 - P)*5.4

We want to find the probability P that will make the long hit better than short hit

P*4.2 + (1 - P)*5.4 < 4.55

4.2P + 5.4 - 5.4P < 4.55

-1.2P + 5.4 < 4.55

-1.2P < -0.85

multiply both sides by -1

1.2P > 0.85

P > 0.85/1.2

P > 0.7083

Therefore, the probability of long hit must be greater than 0.7083 that will make the long hit better than the short hit in terms of improving the expected value of the score.

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1 year ago
The quality control manager at a light bulb factory needs to estimate the mean life of a batch (population) of light bulbs. We a
Nadusha1986 [10]

Answer:

<em>a)95%  confidence intervals for the population mean of light bulbs in this batch</em>

(325.5 ,374.5)

b)

<em>The calculated value Z = 4 > 1.96 at 0.05 level of significance</em>

<em>Null hypothesis is rejected </em>

<em>The manufacturer has not right to take the average life of the light bulbs is 400 hours.</em>

Step-by-step explanation:

Given sample size n = 64

Given  mean of the sample x⁻ = 350

Standard deviation of the Population σ = 100 hours

The tabulated value Z₀.₉₅ = 1.96

<em>95%  confidence intervals for the population mean of light bulbs in this batch</em>

<em></em>(x^{-} - Z_{\frac{\alpha }{2} } \frac{S.D}{\sqrt{n} } , x^{-} + Z_{\frac{\alpha }{2} }\frac{S.D}{\sqrt{n} } )<em></em>

<em></em>(350 - 1.96\frac{100}{\sqrt{64} } , 350 + 1.96\frac{100}{\sqrt{64} } )<em></em>

(350 -24.5, 350 +24.5)

(325.5 ,374.5)

b)

<u><em>Explanation</em></u>:-

Given mean of the Population μ = 400

Given sample size n = 64

Given  mean of the sample x⁻ = 350

Standard deviation of the Population σ = 100 hours

<u><em>Null hypothesis</em></u> : H₀:The manufacturer has right to take the average life of the light bulbs is 400 hours.

μ = 400

<u><em>Alternative Hypothesis: H₁:</em></u> μ ≠400

<u><em>The test statistic </em></u>

Z = \frac{x^{-}-mean }{\frac{S.D}{\sqrt{n} } }

Z = \frac{350 -400}{\frac{100}{\sqrt{64} } }

|Z| = |-4|

The tabulated value   Z₀.₉₅ = 1.96

The calculated value Z = 4 > 1.96 at 0.05 level of significance

Null hypothesis is rejected.

<u><em>Conclusion:</em></u>-

The manufacturer has not right to take the average life of the light bulbs is 400 hours.

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Answer:

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Step-by-step explanation:

the question says to estimate how many 12-inch rulers will be about the same length as a bike. In other words we have to measure the length of bike by in terms of ruler like 3 ruler length or 5 rular length etc.

Type of bike is not mentioned so i'm going to use bicyle.

From internet I found that approx lenght of a bike ( bicycle) is = 68 inches.

Given that 1 ruler = 12 inches

So number of rulers that can fit into 68 inches can be found by dividing 68 by 12

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Answer:

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Step-by-step explanation:

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