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Ch. 6 - Normal Probability Distributions
Triola - Elementary Statistics 14th Edition
Triola14th EditionElementary StatisticsISBN: 9780137366446Not the one you use?Change textbook
Chapter 6, Problem 6.4.5a

Using the Central Limit Theorem. In Exercises 5–8, assume that the amounts of weight that male college students gain during their freshman year are normally distributed with a mean of 1.2 kg and a standard deviation of 4.9 kg (based on Data Set 13 “Freshman 15” in Appendix B).


a. If 1 male college student is randomly selected, find the probability that he has no weight gain during his freshman year. (That is, find the probability that during his freshman year, his weight gain is less than or equal to 0 kg.)

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Step 1: Identify the given parameters for the normal distribution. The mean (μ) is 1.2 kg, and the standard deviation (σ) is 4.9 kg. The random variable X represents the weight gain of a male college student during his freshman year.
Step 2: Define the probability to be calculated. We are tasked with finding the probability that the weight gain is less than or equal to 0 kg, i.e., P(X ≤ 0).
Step 3: Standardize the random variable X to convert it into a standard normal variable Z using the formula Z = (X - μ) / σ. Substituting the values, Z = (0 - 1.2) / 4.9.
Step 4: Simplify the Z-score calculation to find the standardized value. This will give you the Z-score corresponding to X = 0.
Step 5: Use a standard normal distribution table or a statistical software to find the cumulative probability corresponding to the calculated Z-score. This cumulative probability represents P(X ≤ 0).

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Key Concepts

Here are the essential concepts you must grasp in order to answer the question correctly.

Normal Distribution

Normal distribution is a probability distribution that is symmetric about the mean, depicting that data near the mean are more frequent in occurrence than data far from the mean. In this context, the weight gain of male college students follows a normal distribution with a specified mean and standard deviation, allowing us to use statistical methods to calculate probabilities related to weight gain.
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Finding Standard Normal Probabilities using z-Table

Central Limit Theorem (CLT)

The Central Limit Theorem states that the sampling distribution of the sample mean will approach a normal distribution as the sample size increases, regardless of the original distribution of the population. This theorem is crucial when dealing with sample means and allows for the application of normal distribution properties even when the population distribution is not normal, provided the sample size is sufficiently large.
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Probability Calculation

Probability calculation involves determining the likelihood of a specific event occurring within a defined set of outcomes. In this scenario, we need to calculate the probability that a randomly selected male college student has a weight gain of less than or equal to 0 kg, which requires using the properties of the normal distribution to find the corresponding z-score and then referencing the standard normal distribution table.
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Related Practice
Textbook Question

In Exercises 7–10, use the same population of {4, 5, 9} that was used in Examples 2 and 5. As in Examples 2 and 5, assume that samples of size n = 2 are randomly selected with replacement.


Sampling Distribution of the Sample Standard Deviation For the following, round results to three decimal places.


a. Find the value of the population standard deviation σ.

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Textbook Question

Using the Central Limit Theorem. In Exercises 5–8, assume that the amounts of weight that male college students gain during their freshman year are normally distributed with a mean of 1.2 kg and a standard deviation of 4.9 kg (based on Data Set 13 “Freshman 15” in Appendix B).


a. If 1 male college student is randomly selected, find the probability that he gains at least 2.0 kg during his freshman year..)

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Textbook Question

Ergonomics. Exercises 9–16 involve applications to ergonomics, as described in the Chapter Problem.


Safe Loading of Elevators The elevator in the car rental building at San Francisco International Airport has a placard stating that the maximum capacity is “4000 lb—27 passengers.” Because 4000/27=148, this converts to a mean passenger weight of 148 lb when the elevator is full. We will assume a worst-case scenario in which the elevator is filled with 27 adult males. Based on Data Set 1 “Body Data” in Appendix B, assume that adult males have weights that are normally distributed with a mean of 189 lb and a standard deviation of 39 lb.


b. Find the probability that a sample of 27 randomly selected adult males has a mean weight greater than 148 lb.

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Textbook Question

Ergonomics. Exercises 9–16 involve applications to ergonomics, as described in the Chapter Problem.


Water Taxi Safety Passengers died when a water taxi sank in Baltimore’s Inner Harbor. Men are typically heavier than women and children, so when loading a water taxi, assume a worst-case scenario in which all passengers are men. Assume that weights of men are normally distributed with a mean of 189 lb and a standard deviation of 39 lb (based on Data Set 1 “Body Data” in Appendix B). The water taxi that sank had a stated capacity of 25 passengers, and the boat was rated for a load limit of 3500 lb.


b. If the water taxi is filled with 25 randomly selected men, what is the probability that their mean weight exceeds the value from part (a)?

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Textbook Question

In Exercises 7–10, use the same population of {4, 5, 9} that was used in Examples 2 and 5. As in Examples 2 and 5, assume that samples of size n = 2 are randomly selected with replacement.


Sampling Distribution of the Sample Proportion


a. For the population, find the proportion of odd numbers.

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Textbook Question

Cell Phones and Brain Cancer In a study of 420,095 cell phone users in Denmark, it was found that 135 developed cancer of the brain or nervous system. For those not using cell phones, there is a 0.000340 probability of a person developing cancer of the brain or nervous system. We therefore expect about 143 cases of such cancers in a group of 420,095 randomly selected people.

a. Find the probability of 135 or fewer cases of such cancers in a group of 420,095 people.

b. What do these results suggest about media reports that suggest cell phones cause cancer of the brain or nervous system?

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