Table of Contents
Introduction to Discrete and Continuous Data
Discrete data is data that can be counted and is represented by whole numbers. Continuous data is data that can be measured and is represented by real numbers. Discrete and Continuous Data.
What is Discrete Data?
Discrete data is data that is collected in a specific, finite number of buckets. For example, the number of students in a classroom is a discrete dataset, because it can be counted and there are a specific, finite number of students in the room. Contrast this with a dataset that measures the weight of all the students in the room, which would be a continuous dataset.
What is Continuous Data?
Continuous data is data that can be measured on a continuum. This type of data can take on any value within a given range. For example, time, weight, and height are all continuous data.
Discrete vs Continuous Examples
A discrete example would be flipping a coin. There are only two possible outcomes – heads or tails.
A continuous example would be measuring the temperature of a room. The temperature can be any number between 0 and 100 degrees Celsius.
Continuous data can be any value within a given range, while discrete data can only be certain values within a given range. Continuous data is measured on a scale, while discrete data is counted.
Questions :
1. What is the difference between discrete and continuous data?
Discrete data are data that can be counted and has a finite number of possible values. Continuous data are data that can take any value within a given range.
Tips and Tricks :
A. When studying discrete data, it is important to identify and understand the different types of discrete data.
B. When studying continuous data, it is important to identify and understand the different types of continuous data.
C. It is also important to understand the different types of distributions that can be used to describe continuous data.
D. In addition, it is important to understand how to identify and use important statistical measures when describing data.
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