Examples of Frequency Distribution

Explore practical examples of frequency distribution across diverse contexts.
By Jamie

Understanding Frequency Distribution

Frequency distribution is a statistical tool used to organize and analyze data by showing the number of occurrences of each value in a dataset. This method allows researchers and analysts to visualize the distribution of values and identify patterns or trends. Below are three practical examples that illustrate how frequency distribution can be applied in various fields.

Example 1: Student Test Scores Distribution

Context

In an educational setting, teachers often analyze student performance to understand how well a class is doing on exams. Frequency distribution can help visualize the range of test scores and identify areas for improvement.

In this example, let’s consider the test scores of 30 students in a mathematics exam:

  • Scores: 56, 78, 89, 45, 67, 78, 90, 45, 75, 82, 67, 89, 91, 72, 68, 85, 95, 70, 74, 88, 60, 70, 76, 81, 84, 88, 92, 66, 55, 80

To create a frequency distribution, we can categorize the scores into ranges:

Score Range Frequency
40-49 2
50-59 3
60-69 6
70-79 7
80-89 7
90-99 5

This table shows how many students scored within each range. It indicates that most students scored between 70 and 89, suggesting a strong overall performance.

Notes

  • This frequency distribution could be visualized using a histogram to better illustrate the data.
  • Variations can include different score ranges or cumulative frequency distributions.

Example 2: Daily Sales Data Distribution

Context

Retail businesses track daily sales to analyze performance trends over time. A frequency distribution can help identify the most common sales figures.

Consider a small bookstore that records its sales over a week:

  • Daily Sales (in dollars): 150, 200, 250, 300, 150, 400, 350

The frequency distribution for these sales might look like this:

Sales Range Frequency
100-199 2
200-299 3
300-399 2
400-499 1

This table reveals that the bookstore typically makes sales between $200 and $299, which can inform stock and staffing decisions.

Notes

  • This example highlights the importance of understanding sales patterns for inventory management.
  • Different time frames (e.g., monthly or yearly) can also be analyzed for broader insights.

Example 3: Age Distribution in a Community Survey

Context

Understanding the age distribution of a population can provide valuable insights for community planning and resource allocation. Frequency distribution can be utilized in surveys to summarize this demographic data.

Imagine a local government conducts a survey of residents’ ages:

  • Ages of 50 Residents: 12, 25, 34, 45, 23, 67, 18, 30, 29, 40, 55, 62, 24, 19, 33, 47, 54, 60, 70, 22, 36, 48, 39, 38, 27, 32, 41, 50, 56, 21, 26, 35, 44, 52, 58, 63, 37, 42, 46, 72, 71, 49, 57, 61, 28, 20, 73, 74, 75, 76

The frequency distribution might be organized as follows:

Age Range Frequency
10-19 7
20-29 8
30-39 7
40-49 10
50-59 9
60-69 6
70-79 3

This distribution shows a balanced age range in the community, with a notable number of residents in their 40s.

Notes

  • Community services can be tailored based on this distribution, ensuring various age groups are adequately supported.
  • More detailed analysis can involve gender or socioeconomic status alongside age.

By employing these examples of frequency distribution, we can illustrate how different fields utilize this statistical tool to make informed decisions based on data.