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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

Fatal Car Crashes There are about 15,000 car crashes each day in the United States, and the proportion of car crashes that are fatal is 0.00559 (based on data from the National Highway Traffic Safety Administration). Assume that each day, 1000 car crashes are randomly selected and the proportion of fatal car crashes is recorded.

a. What do you know about the mean of the sample proportions?

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 between 0.5 kg and 2.5 kg during freshman year.

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.


a. Given that the water taxi that sank was rated for a load limit of 3500 lb, what is the maximum mean weight of the passengers if the boat is filled to the stated capacity of 25 passengers?

Textbook Question

Body Temperatures Listed below are body temperatures (°F) of adult males (based on Data Set 5 “Body Temperatures” in Appendix B).


97.6 98.2 99.6 98.7 99.4 98.2 98.0 98.6 98.6


a. Find the mean. Does the result seem reasonable?

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Textbook Question

Transformations The heights (in inches) of women listed in Data Set 1 “Body Data” in Appendix B have a distribution that is approximately normal, so it appears that those heights are from a normally distributed population.


a. If 2 inches is added to each height, are the new heights also normally distributed?

Textbook Question

Mendelian Genetics When Mendel conducted his famous genetics experiments with peas, one sample of offspring consisted of 929 peas, with 705 of them having red flowers. If we assume, as Mendel did, that under these circumstances, there is a 3/4 probability that a pea will have a red flower, we would expect that 696.75 (or about 697) of the peas would have red flowers, so the result of 705 peas with red flowers is more than expected.


a. If Mendel’s assumed probability is correct, find the probability of getting 705 or more peas with red flowers.