Conditional Binomial Distribution

Thread starter shespuzzling
Start date Oct 27, 2010
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Binomial Binomial distribution Conditional Distribution

In summary, a conditional binomial distribution is a probability distribution that describes the number of successes in a fixed number of trials, given that the probability of success for each trial is not constant. It differs from a regular binomial distribution in that the probability of success can change based on certain conditions. Real-life examples of a conditional binomial distribution include the probability of a student passing an exam after studying a certain number of hours, and the probability of a car starting in freezing temperatures. The mean and standard deviation for a conditional binomial distribution are calculated by multiplying the number of trials by the probability of success for each trial and using the formula sqrt(np(1-p)), respectively. It can only be used for discrete data with a fixed number of trials

Oct 27, 2010

shespuzzling

How do I find a conditional bionomial distribution? For example, if I want the probability that k=7 (for instance, 7 could be any number depending on the experiment), given that k is greater/equal to 4. I know what the equation would look like

i.e.: F(k=7|k >= 4)= P(k=7, k>=4)/P(k>=4). Then, would this be equal to P(k=7)/P(k>=4)? Thanks in advance for your help.

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Oct 27, 2010

statdad

Homework Helper

Yup.

Oct 27, 2010

shespuzzling

thanks!

Related to Conditional Binomial Distribution

1. What is a conditional binomial distribution?

A conditional binomial distribution is a probability distribution that describes the number of successes in a fixed number of trials, given that the probability of success for each trial is not constant.

2. How is a conditional binomial distribution different from a regular binomial distribution?

In a regular binomial distribution, the probability of success for each trial is constant. In a conditional binomial distribution, the probability of success for each trial can change based on certain conditions.

3. What are some real-life examples of a conditional binomial distribution?

One example is the probability of a student passing an exam, given that they have studied a certain number of hours. Another example is the probability of a car starting, given that the temperature outside is below freezing.

4. How is the mean and standard deviation calculated for a conditional binomial distribution?

The mean of a conditional binomial distribution is calculated by multiplying the number of trials by the probability of success for each trial. The standard deviation is calculated using the formula sqrt(np(1-p)), where n is the number of trials and p is the probability of success for each trial.

5. Can a conditional binomial distribution be used for continuous data?

No, a conditional binomial distribution is only used for discrete data, where the number of trials is fixed and there are only two possible outcomes (success or failure) for each trial.