What is the difference between a discrete and continuous random variable give an example of each?

A random variable is a variable whose value is a numerical outcome of a random phenomenon. A discrete random variable X has a countable number of possible values. Example: Let X represent the sum of two dice. A continuous random variable X takes all values in a given interval of numbers.

What are the real life examples of discrete random variable just give 1 example and explain?

If a random variable can take only a finite number of distinct values, then it must be discrete. Examples of discrete random variables include the number of children in a family, the Friday night attendance at a cinema, the number of patients in a doctor’s surgery, the number of defective light bulbs in a box of ten.

What is a discrete random variable give some examples?

Examples of discrete random variables include: The number of eggs that a hen lays in a given day (it can’t be 2.3) The number of people going to a given soccer match. The number of students that come to class on a given day. The number of people in line at McDonald’s on a given day and time.

What is the difference of continuous and discrete?

Discrete data is information that can only take certain values. Continuous data is data that can take any value. Height, weight, temperature and length are all examples of continuous data.

What is the difference between discrete and continuous probability distribution?

A probability distribution may be either discrete or continuous. A discrete distribution means that X can assume one of a countable (usually finite) number of values, while a continuous distribution means that X can assume one of an infinite (uncountable) number of different values.

Which is an example of continuous variable?

If your data deals with measuring a height, weight, or time, then you have a continuous variable. Some examples of variables in statistics might include age, eye color, height, number of siblings, gender, or number of pets. Our definition of a continuous variable also mentions that it’s quantitative.

What are examples of continuous?

Continuous data is data that can take any value. Height, weight, temperature and length are all examples of continuous data. Some continuous data will change over time; the weight of a baby in its first year or the temperature in a room throughout the day.

What are the examples of continuous variables?

You often measure a continuous variable on a scale. For example, when you measure height, weight, and temperature, you have continuous data. With continuous variables, you can calculate and assess the mean, median, standard deviation, or variance.

How will you differentiate between discrete and continuous random variables?

A discrete random variable has a finite number of possible values. A continuous random variable could have any value (usually within a certain range). A continuous random variable could take on any value (usually within a certain range); there are not a fixed number of possible values.

What is the difference between continuous and discontinuous variables?

a variable that has distinct, discrete values but no precise numerical flow. For example, gender can be thought of as a discontinuous variable with two possible values, male or female. In contrast, a continuous variable involves numerically precise information, such as height, weight, and miles per hour.

What is the difference between discrete and continuous random variables?

A discrete random variable has a finite number of possible values. A continuous random variable could have any value (usually within a certain range). A discrete random variable is typically an integer although it may be a rational fraction.

What is the definition of continuous variable?

Definition of Continuous Variable. Continuous variable, as the name suggest is a random variable that assumes all the possible values in a continuum. Simply put, it can take any value within the given range.

What is the difference between discrete and categorical?

Any value between the two values. A discrete variable is a type of statistical variable that can assume only fixed number of distinct values and lacks an inherent order. Also known as a categorical variable, because it has separate, invisible categories.

When is a variable said to be discrete?

However no values can exist in-between two categories, i.e. it does not attain all the values within the limits of the variable. So, the number of permitted values that it can suppose is either finite or countably infinite. Hence if you are able to count the set of items, then the variable is said to be discrete.