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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 6.6.15a

Smartphones Based on an LG smartphone survey, assume that 51% of adults with smartphones use them in theaters. In a separate survey of 250 adults with smartphones, it is found that 109 use them in theaters.


a. If the 51% rate is correct, find the probability of getting 109 or fewer smartphone owners who use them in theaters.

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Step 1: Identify the type of probability distribution. Since we are dealing with a fixed number of trials (250 adults), two possible outcomes (use in theaters or not), and a constant probability of success (51%), this is a binomial distribution problem.
Step 2: Define the parameters of the binomial distribution. The number of trials (n) is 250, the probability of success (p) is 0.51, and the number of successes (x) is 109.
Step 3: Convert the binomial distribution to a normal distribution for approximation. The mean (μ) and standard deviation (σ) of the binomial distribution are calculated as follows: μ = n * p and σ = sqrt(n * p * (1 - p)).
Step 4: Apply the continuity correction. Since we are finding the probability of getting 109 or fewer successes, adjust the value of x to 109.5 for the normal approximation.
Step 5: Standardize the value using the z-score formula: z = (x - μ) / σ. Then, use the standard normal distribution table or a statistical software to find the cumulative probability corresponding to the calculated z-score.

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Key Concepts

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

Binomial Distribution

The binomial distribution models the number of successes in a fixed number of independent Bernoulli trials, each with the same probability of success. In this context, the success is defined as an adult using their smartphone in a theater. The parameters include the number of trials (n = 250) and the probability of success (p = 0.51).
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Mean & Standard Deviation of Binomial Distribution

Normal Approximation to the Binomial

For large sample sizes, the binomial distribution can be approximated by a normal distribution. This is applicable when both np and n(1-p) are greater than 5. In this case, we can use the normal approximation to calculate the probability of observing 109 or fewer smartphone users in theaters, simplifying the calculations.
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Using the Normal Distribution to Approximate Binomial Probabilities

Cumulative Probability

Cumulative probability refers to the probability of a random variable being less than or equal to a certain value. In this scenario, we need to calculate the cumulative probability of observing 109 or fewer users in theaters, which can be found using the normal distribution's cumulative distribution function (CDF) after applying the normal approximation.
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Introduction to Probability
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.

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..)

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.

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)?

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.

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?