Can a random variable be discrete or continuous?

Random variables can be classified as either discrete (that is, taking any of a specified list of exact values) or as continuous (taking any numerical value in an interval or collection of intervals).

What is both discrete and continuous?

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.

Which data type can be both discrete and continuous?

There are two types of quantitative data, which is also referred to as numeric data: continuous and discrete. As a general rule, counts are discrete and measurements are continuous.

Can a random variable be neither discrete or continuous?

Continuous random variables, which can take on a continuous range (i.e., interval) of values. There are random variables that are neither discrete nor continuous, i.e., they can take on an uncountably infinite set of values but do not have a well-defined pdf.

What is the similarities between discrete and continuous variables?

Comparison Chart

Basis for Comparison	Discrete Variable	Continuous Variable
Values	Values are obtained by counting.	Values are obtained by measuring.
Classification	Non-overlapping	Overlapping
Assumes	Distinct or separate values.	Any value between the two values.
Represented by	Isolated points	Connected points

What are the similarities of discrete and continuous variables?

Which data are continuous and take continuous values?

Digital data take on discrete values. Data can be analog or digital. Analog data are continuous and take Analog data are continuous and take continuous values.

Which of these 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 is the difference between discrete and continuous statistics?

Discrete data refers to specific and distinct values, while continuous data are values within a bounded or boundless interval. Discrete data and continuous data are the two types of numerical data used in the field of statistics. Data is generally classified into two categories: descriptive and numerical.

What is the difference between discrete and continuous distribution?

The difference between discrete and continuous data can be drawn clearly on the following grounds: Discrete data is the type of data that has clear spaces between values. Continuous data is data that falls in a continuous sequence. Discrete data is countable while continuous data is measurable.

What is an example of a discrete random variable?

A discrete variable is a variable which can only take a countable number of values. In this example, the number of heads can only take 4 values (0, 1, 2, 3) and so the variable is discrete. The variable is said to be random if the sum of the probabilities is one.

What are some examples of a discrete variable?

The following are examples of discrete random variables: The number of cars sold by a car dealer in one month. The number of students who were protesting the tuition increase last semester. The number of applicants who have applied for a vacant position at a company. The number of typographical errors in a rough draft of a book.