Warning: foreach() argument must be of type array|object, bool given in /var/www/html/web/app/themes/studypress-core-theme/template-parts/header/mobile-offcanvas.php on line 20

What does it mean to say that the probability that a coin toss will land head side up is \(0.5 ?\)

Short Answer

Expert verified
The probability \(0.5\) for a coin toss landing head side up means that there is an equal chance (50%) of the coin landing heads up or tails up. In larger number of tosses, heads would be expected to appear about half the time.

Step by step solution

01

Understand the concept of probability

Probability is a measurement of the likelihood that an event will happen. It is a value between 0 and 1, inclusive. A probability of 1 means the event is certain to happen, a probability of 0 means the event will not happen, and a probability of 0.5 suggests the event is equally likely to happen or not happen.
02

Apply the concept to the given situation

In the context of a coin toss, there are two possible outcomes: heads or tails. If the coin is fair (i.e., not biased), then each side has an equal chance of appearing. Therefore, the probability is \(0.5\) or 50% for each.
03

Interpret the probability

To say that the probability that a coin toss will land head side up is \(0.5\) means that, for a large number of coin flips, we would expect heads to appear approximately half of the time. In other words, if the coin is flipped 100 times, we would expect to see about 50 heads. This doesn't mean every 100 flips will produce exactly 50 heads, but rather, this is the expected average over repeated trials.

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with Vaia!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Consider a chance experiment that consists of selecting a customer at random from all people who purchased a car at a large car dealership during 2010 . a. In the context of this chance experiment, give an example of two events that would be mutually exclusive. b. In the context of this chance experiment, give an example of two events that would not be mutually exclusive.

A friend who works in a big city owns two cars, one small and one large. Three-quarters of the time he drives the small car to work, and one-quarter of the time he takes the large car. If he takes the small car, he usually has little trouble parking and so is at work on time with probability \(0.9 .\) If he takes the large car, he is on time to work with probability 0.6 . Given that he was at work on time on a particular morning, what is the probability that he drove the small car?

Automobiles that are more than 10 years old must pass a vehicle inspection to be registered in a particular state. The state reports the probability that a car more than 10 years old will fail the vehicle inspection is \(0.09 .\) Give a relative frequency interpretation of this probability.

In an article that appears on the website of the American Statistical Association (www.amstat.org), Carlton Gunn, a public defender in Seattle, Washington, wrote about how he uses statistics in his work as an attorney. He states: I personally have used statistics in trying to challenge the reliability of drug testing results. Suppose the chance of a mistake in the taking and processing of a urine sample for a drug test is just 1 in \(100 .\) And your client has a "dirty" (i.e., positive) test result. Only a 1 in 100 chance that it could be wrong? Not necessarily. If the vast majority of all tests given - say 99 in 100 - are truly clean, then you get one false dirty and one true dirty in every 100 tests, so that half of the dirty tests are false. Define the following events as \(T D=\) event that the test result is dirty \(T C=\) event that the test result is clean \(D=\) event that the person tested is actually dirty \(C=\) event that the person tested is actually clean a. Using the information in the quote, what are the values of i. \(P(T D \mid D)\) iii. \(P(C)\) ii. \(P(T D \mid C)\) iv. \(P(D)\) b. Use the probabilities from Part (a) to construct a "hypothetical 1000 " table. c. What is the value of \(P(T D)\) ? d. Use the table to calculate the probability that a person is clean given that the test result is dirty, \(P(C \mid T D)\). Is this value consistent with the argument given in the quote? Explain.

A large cable company reports that \(80 \%\) of its customers subscribe to its cable TV service, \(42 \%\) subscribe to its Internet service, and \(97 \%\) subscribe to at least one of these two services. (Hint: See Example 5.6\()\) a. Use the given probability information to set up a "hypothetical \(1000 "\) table. b. Use the table from Part (a) to find the following probabilities: i. the probability that a randomly selected customer subscribes to both cable TV and Internet service. ii. the probability that a randomly selected customer subscribes to exactly one of these services.

See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.

Sign-up for free