on of adult Americans who believe marriage is obsolete. (b) What is the probability that in a random sample of 500 adult Americans less than 38% believe that marriage is obsolete? (c) What is the probability that in a random sample of 500 adult Americans between 40% and 45% believe that marriage is obsolete? (d) Would it be unusual for a random sample of 500 adult Americans to result in 210 or more who believe marriage is obsolete? 18. Credit Cards According to creditcard.com, 29% of adults do not own a credit card. (a) Suppose a random sample of 500 adults is asked, "Do you own a credit card?" Describe the sampling distribution of p, the proportion of adults who do not own a credit card. 414 CНAPТER 8 Sampling Distributions (b) What is the probability that in a random sample of 500 adults more than 30% do not own a credit card? (c) What is the probability that in a random sample of 500 adults between 25% and 30% do not own a credit card? (d) Would it be unusual for a random sample of 500 adults to result in 125 or fewer who do not own a credit card? Why? 19. Afraid to Fly According to a study conducted by the Gallup organization, the proportion of Americans who are afraid to fly is 0.10. A random sample of 1100 Americans results in 121 indicating that they are afraid to fly. Explain why this is not necessarily evidence that the proportion of Americans who are afraid to fly has increased since the time of the Gallup study. 20. Having Children? The Pew Research Center recently reported that 18% of women 40-44 years of age have never given birth. Suppose a random sample of 250 adult women 40-44 years of age results in 52 indicating they have never given birth. Explain why this is not necessarily evidence that the proportion of women 40-44 years of age who have not given birth has increased since the time of the Pew studu u

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Addition Rule of Probability

It simply refers to the likelihood of an event taking place whenever the occurrence of an event is uncertain. The probability of a single event can be calculated by dividing the number of successful trials of that event by the total number of trials.

Expected Value

When a large number of trials are performed for any random variable ‘X’, the predicted result is most likely the mean of all the outcomes for the random variable and it is known as expected value also known as expectation. The expected value, also known as the expectation, is denoted by: E(X).

Probability Distributions

Understanding probability is necessary to know the probability distributions. In statistics, probability is how the uncertainty of an event is measured. This event can be anything. The most common examples include tossing a coin, rolling a die, or choosing a card. Each of these events has multiple possibilities. Every such possibility is measured with the help of probability. To be more precise, the probability is used for calculating the occurrence of events that may or may not happen. Probability does not give sure results. Unless the probability of any event is 1, the different outcomes may or may not happen in real life, regardless of how less or how more their probability is.

Basic Probability

The simple definition of probability it is a chance of the occurrence of an event. It is defined in numerical form and the probability value is between 0 to 1. The probability value 0 indicates that there is no chance of that event occurring and the probability value 1 indicates that the event will occur. Sum of the probability value must be 1. The probability value is never a negative number. If it happens, then recheck the calculation.