Last updated on June 18th, 2025
Sample space is a set of all possible outcomes of an experiment. We use sample space in real-life uncertain situations such as drawing a particular card from a deck or guessing the correct answer in multiple-choice questions. In this topic, we will learn about sample space from a broad perspective.
The sample space is a mathematical concept that refers to the possibility of the occurrences of different outcomes in a random experiment. Sample space is often represented by “S”.
For example, the sample space for rolling a die is S = {1, 2, 3, 4, 5, 6}. Understanding random events is essential for calculating probabilities correctly.
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The probability of the sample place can be determined using the following steps:
Both event and sample space are significant elements of an experiment. The key differences between them are discussed below:
Sample Space | Event |
Collection of all possible outcomes of a given experiment. | Collection of specific outcomes from an experiment. |
Denoted by ‘S’ | Denoted by ‘E’ or other symbols. |
Includes all possible outcomes | Concentrates on specific outcomes. |
Applied to determine the probability of total possible outcomes. | Used to determine the probability of a specific outcome. |
For example: The sample space for a single coin flip: {H, T} |
For example: Obtaining tails: E = {T} |
Sample space is a significant concept that lists all the possible options for an event. It can be applied in various fields to determine probability. Now, let’s explore the real-life applications of Sample Space:
Sample space is an important concept that helps students predict the probability of uncertain events. However, some students make mistakes when working with problems related to sample spaces. Here, we list some common mistakes along with ways to master the concept easily:
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Lena has two shirts (Black, Red) and two pairs of skirts (Blue, White). Determine the sample space for their outfit choices.
S = { (Black, Blue), (Black, White), (Red, Blue), (Red, White)}
The first step is to identify the experiment:
Choosing a combination of one shirt and one pair of skirts.
Here, we list all the possible combinations:
Now, we get the sample space as:
S = { (Black, Blue), (Black, White), (Red, Blue), (Red, White)}.
John arrives at a bus stop where three subways (Subway 1, Subway 2, Subway 3, and Subway 4) can arrive next. What is the sample space?
The sample space we get is: {Subway 1, Subway 2, Subway 3, Subway 4}
The experiment needs to determine which subway arrives next.
Here, we list all possible outcomes:
Now, the sample space we get is: {Subway 1, Subway 2, Subway 3, Subway 4}.
A teacher asks students to pick a paper lot numbered from 1 to 6. What is the sample space?
S = {1, 2, 3, 4, 5, 6}
Here, the experiment is students picking a paper lot numbered from 1 to 6.
We will now list all possible numbers written on the paper lots:
Thus, the sample space is S = {1, 2, 3, 4, 5, 6}.
A café offers four varieties of ice cream flavors such as corn, mint chocolate chip, bubblegum, and cinnamon apple. If a customer randomly picks a random flavor of ice cream, what is the sample space?
S ={Corn, Mint chocolate chip, Bubblegum, Cinnamon apple}
Here, the experiment is to determine the sample space, where a customer randomly picks an ice cream flavor.
The possible flavors we have:
Therefore, the sample space is:
S ={Corn, Mint chocolate chip, Bubblegum, Cinnamon apple}
Angel randomly chooses a mode of transportation to go to the office. The available options are walking, a two-wheeler, a cab, and a car. What is the sample space?
S = {Walking, Two-wheeler, Car, Cab}
The experiment is to determine the selection of a mode of transportation to go to the office.
All the available options are listed:
Thus, the sample space including all possible outcomes is:
S = {Walking, Two-wheeler, Car, Cab}
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Jaipreet Kour Wazir is a data wizard with over 5 years of expertise in simplifying complex data concepts. From crunching numbers to crafting insightful visualizations, she turns raw data into compelling stories. Her journey from analytics to education ref
: She compares datasets to puzzle games—the more you play with them, the clearer the picture becomes!