## What are the two requirements for a discrete probability?

In the development of the **probability** function for a **discrete** random variable, **two** conditions must be satisfied: (1) f(x) must be nonnegative for each value of the random variable, and (2) the sum of the **probabilities** for each value of the random variable must equal one.

## What are the two requirements for a discrete probability distribution quizlet?

What are the **two requirements for a discrete probability** **distribution**? Each **probability** must be between 0 and 1, inclusive, and the sum of the **probabilities** must equal 1.

## What are the two key properties of a discrete probability distribution?

A **discrete probability distribution** function has **two characteristics**: Each **probability** is between zero and one, inclusive. The sum of the **probabilities** is one.

## What are the requirements for a distribution to be a probability distribution?

**Three Requirements for probability distribution:**

- The
**random variable**is associated with numerical. - The sum of the
**probabilities**has to be equal to 1, discounting any round off error. - Each individual
**probability**must be a number between 0 and 1, inclusive. THIS SET IS OFTEN IN FOLDERS WITH

## What is discrete probability distribution example?

If you roll a six, you win a prize. Game 2: Guess the weight of the man. If you guess within 10 pounds, you win a prize. One of these games is a **discrete probability distribution** and one is a continuous **probability distribution**.

## How do you know if a distribution is discrete?

A random variable is **discrete if** it has a finite number of possible outcomes, or a countable number (i.e. the integers are infinite, but are able to be counted). For example, the number of heads you get **when** flip a coin 100 times is **discrete**, since it can only be a whole number between 0 and 100.

## Is the probability distribution a discrete distribution?

If a random variable is a **discrete** variable, its **probability distribution** is called a **discrete probability distribution**. The random variable X can only take on the values 0, 1, or 2, so it is a **discrete** random variable.

## Which of the following is a valid discrete probability distribution?

A **valid probability distribution** for a **discrete** random variable is the one whose sum of **probabilities** is 1.

## Is the following table a valid discrete probability distribution?

Yes, since all the **probabilities** are between 0 and 1 and the **probabilities** add up to one.

## What is a discrete probability distribution function?

A **discrete probability distribution** is applicable to the scenarios where the set of possible outcomes is **discrete** (e.g. a coin toss, a roll of a dice), and the **probabilities** are here encoded by a **discrete** list of the **probabilities** of the outcomes, known as the **probability** mass **function**.

## What is a discrete probability distribution?

A **discrete distribution** describes the **probability** of occurrence of each value of a **discrete** random variable. A **discrete** random variable is a random variable that has countable values, such as a list of non-negative integers. Thus, a **discrete probability distribution** is often presented in tabular form.

## Which of the following is an example of a continuous random variable?

A continuous random variable can take any **value** within an **interval**, and for example, the length of a rod measured in meters or, **temperature** measured in Celsius, are both continuous random variables..

## What are the 4 requirements needed to be a binomial distribution?

1: The number of observations n is fixed. 2: Each observation is independent. 3: Each observation represents one of two outcomes (“success” or “failure”). **4**: The **probability** of “success” p is the same **for** each outcome.

## What makes a valid probability distribution?

Solution: To be a **valid probability** density function, all values of f(x) must be positive, and the area beneath f(x) must equal one. The first condition is met by restricting a and x to positive numbers. To meet the second condition, the integral of f(x) from one to ten must equal 1.

## What is a probability distribution for a discrete random variable What does it look like?

The probability distribution of a discrete random variable X is a listing of each possible **value** x taken by X along with the probability P(x) that X takes that **value** in one trial of the experiment.