# What do you mean by confluent hypergeometric functions?

## What do you mean by confluent hypergeometric functions?

In mathematics, a confluent hypergeometric function is a solution of a confluent hypergeometric equation, which is a degenerate form of a hypergeometric differential equation where two of the three regular singularities merge into an irregular singularity.

**What are hypergeometric functions used for?**

Hypergeometric functions show up as solutions of many important ordinary differential equations. In particular in physics, for example in the study of the hydrogene atom (Laguerre polynomials) and in simple problems of classical mechanics (Hermite polynomials appear in the study of the harmonic oscillator).

**Why hypergeometric function is called hypergeometric?**

When a=1 and b=c, the series reduces into a plain geometric series, i.e. hence, the name hypergeometric. This function can be considered as a generalization of the geometric series.

### What is hypergeometric distribution explain with example?

Hypergeometric Distribution Example 1 A deck of cards contains 20 cards: 6 red cards and 14 black cards. 5 cards are drawn randomly without replacement. What is the probability that exactly 4 red cards are drawn? 6C4 means that out of 6 possible red cards, we are choosing 4.

**How do you find the hypergeometric distribution?**

Hypergeometric Distribution

- P = K C k * (N – K) C (n – k) / N C n
- Mean = n * K / N.
- Standard Deviation = [n * K * (N – K) * (N – n) / {N2 * (N – 1)}]1/2
- P = K C k * (N – K) C (n – k) / N C n

**What is the difference between binomial and hypergeometric distribution?**

For the binomial distribution, the probability is the same for every trial. For the hypergeometric distribution, each trial changes the probability for each subsequent trial because there is no replacement.

#### What is the formula for hypergeometric distribution?

The hypergeometric distribution has the following properties: The mean of the distribution is equal to n * k / N . The variance is n * k * ( N – k ) * ( N – n ) / [ N2 * ( N – 1 ) ] .

**Why do you use hypergeometric distribution?**

The hypergeometric distribution can be used for sampling problems such as the chance of picking a defective part from a box (without returning parts to the box for the next trial). The hypergeometric distribution is used under these conditions: Total number of items (population) is fixed.

**What is hypergeometric distribution example?**

## What is hypergeometric distribution explain with an example?

The hypergeometric distribution differs from the binomial distribution in the lack of replacements. Thus, it often is employed in random sampling for statistical quality control. A simple everyday example would be the random selection of members for a team from a population of girls and boys.

**When should use hypergeometric distribution?**

When do we use the hypergeometric distribution? The hypergeometric distribution is a discrete probability distribution. It is used when you want to determine the probability of obtaining a certain number of successes without replacement from a specific sample size.

**What is the hypergeometric distribution in statistics?**

hypergeometric distribution, in statistics, distribution function in which selections are made from two groups without replacing members of the groups. The hypergeometric distribution differs from the binomial distribution in the lack of replacements.

### What is an example of hypergeometric distribution?

If you play poker, the hypergeometric distribution can tell you the probability of getting 3 of the same suit in a 5 card hand (or any number of other card/hand combinations). The PowerBall lottery game is a televised, two part drawing. In the first stage, five white balls are drawn randomly from a bowl of 49 balls.

**What is the formula of hypergeometric distribution?**

**When would you use a hypergeometric distribution?**

#### How do you explain hypergeometric distribution?

hypergeometric distribution, in statistics, distribution function in which selections are made from two groups without replacing members of the groups.