# Geometric Distribution At Most Examples And Solutions Pdf

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*What is the probability that it takes five games until you lose? You throw darts at a board until you hit the center area.*

How long should we expect to flip a coin until it turns up heads? Or how many times should we expect to roll a die until we get a 1? These questions can be answered using the geometric distribution. We first formalize each trial - such as a single coin flip or die toss - using the Bernoulli distribution, and then we combine these with our tools from probability Chapter 2 to construct the geometric distribution.

## Geometric Distribution

How long should we expect to flip a coin until it turns up heads? Or how many times should we expect to roll a die until we get a 1? These questions can be answered using the geometric distribution. We first formalize each trial - such as a single coin flip or die toss - using the Bernoulli distribution, and then we combine these with our tools from probability Chapter 2 to construct the geometric distribution.

Stanley Milgram began a series of experiments in to estimate what proportion of people would willingly obey an authority and give severe shocks to a stranger. Over the years, additional research suggested this number is approximately consistent across communities and time.

Find further information on Milgram's experiment at www. Each person in Milgram's experiment can be thought of as a trial. We label a person a success if she refuses to administer the worst shock. A person is labeled a failure if she administers the worst shock. Thus, success or failure is recorded for each person in the study. When an individual trial only has two possible outcomes, it is called a Bernoulli random variable.

A Bernoulli random variable has exactly two possible outcomes. We typically label one of these outcomes a "success" and the other outcome a "failure". We may also denote a success by 1 and a failure by 0. TIP: "success" need not be something positive.

We chose to label a person who refuses to administer the worst shock a "success" and all others as "failures". However, we could just as easily have reversed these labels. The mathematical framework we will build does not depend on which outcome is labeled a success and which a failure, as long as we are consistent. Bernoulli random variables are often denoted as 1 for a success and 0 for a failure.

In addition to being convenient in entering data, it is also mathematically handy. Suppose we observe ten trials:. This mathematical inquiry of Bernoulli random variables can be extended even further. Because 0 and 1 are numerical outcomes, we can define the mean and standard deviation of a Bernoulli random variable:. If X is a random variable that takes value 1 with probability of success p and 0 with probability 1 - p, then X is a Bernoulli random variable with mean and standard deviation.

In general, it is useful to think about a Bernoulli random variable as a random process with only two outcomes: a success or failure.

Then we build our mathematical framework using the numerical labels 1 and 0 for successes and failures, respectively. In this case, the independence aspect just means the individuals in the example don't affect each other, and identical means they each have the same probability of success. Smith wants to repeat Milgram's experiments, but she only wants to sample people until she finds someone who will not inflict the worst shock.

This is hypothetical since, in reality, this sort of study probably would not be permitted any longer under current ethical standards.

If the probability a person will not give the most severe shock is still 0. The second person? The third? What about if it takes her n - 1 individuals who will administer the worst shock before finding her first success, i. The probability it will be the second person is. Figure 3. In general, the probabilities for a geometric distribution decrease exponentially fast.

While this text will not derive the formulas for the mean expected number of trials needed to find the first success or the standard deviation or variance of this distribution, we present general formulas for each. The mean i. The mean and the expected value are one and the same. This mathematical result is consistent with what we would expect intuitively. If the probability of a success is high e. If the probability of a success is low e.

The probability that an individual would refuse to administer the worst shock is said to be about 0. If we were to examine individuals until we found one that did not administer the shock, how many people should we expect to check?

What is the chance that Dr. Smith will find the first success within the first 4 people? Because the individuals in the sample are randomly sampled from a large population, they are independent. We compute the probability of each case and add the separate results:. Determine a more clever way to solve Example 3.

Show that you get the same result. If people were randomly selected from this region, what is the expected number of people who must be checked before one was found that would be deemed a success? What is the standard deviation of this waiting time? Using the results from Example 3. The geometric distribution is always right skewed and can never be well-approximated by the normal model.

The independence assumption is crucial to the geometric distribution's accurate description of a scenario. Mathematically, we can see that to construct the probability of the success on the nth trial, we had to use the Multiplication Rule for Independent Processes. It is no simple task to generalize the geometric model for dependent trials. Bernoulli Distribution Stanley Milgram began a series of experiments in to estimate what proportion of people would willingly obey an authority and give severe shocks to a stranger.

Bernoulli random variable descriptive A Bernoulli random variable has exactly two possible outcomes. TIP: "success" need not be something positive We chose to label a person who refuses to administer the worst shock a "success" and all others as "failures". Answer No.

## Hypergeometric Distribution

This is true no matter how many times you roll the die. Suppose you want to know the probability of getting the first three on the fifth roll. On rolls one through four, you do not get a face with a three. You play a game of chance that you can either win or lose there are no other possibilities until you lose. What is the probability that it takes five games until you lose?

The probability distribution of a hypergeometric random variable is called a hypergeometric distribution. This lesson describes how hypergeometric random variables, hypergeometric experiments, hypergeometric probability, and the hypergeometric distribution are all related. The following notation is helpful, when we talk about hypergeometric distributions and hypergeometric probability. A hypergeometric experiment is a statistical experiment that has the following properties:. Consider the following statistical experiment.

The geometric probability density function builds upon what we have learned from the binomial distribution. In this case the experiment continues until either a success or a failure occurs rather than for a set number of trials. There are three main characteristics of a geometric experiment. You play a game of chance that you can either win or lose there are no other possibilities until you lose. What is the probability that it takes five games until you lose?

X is a GEOMETRIC RANDOM VARIABLE. PDF: P(X = x) = qx−1p; x = 1,2,3,··· Example: Products produced by a machine has a 3% defective rate. • What is the probability that the first or with 7 inspections, there is at least a 75% chance of.

## 3.3: Geometric Distribution (Special Topic)

A representative from the National Football League's Marketing Division randomly selects people on a random street in Kansas City, Missouri until he finds a person who attended the last home football game. Note that there are theoretically an infinite number of geometric distributions. Breadcrumb Home 11 Font size. Font family A A.