StatsLab Pro

Frequency Distributions, Histograms & Ogives

Core Mathematical Objective

Constructing Continuous Frequency Distributions, Histograms & Ogives

In statistics, real-world raw data can be messy and confusing. This platform teaches you how to clean, structure, and visualize discrete or grouped data. Let us tackle this realistic problem step-by-step:

"In a survey of 40 different types of foods containing protein quantity, convert the discrete raw dataset into a continuous grouped frequency distribution using class intervals 10–15, 15–20, 20–25, ... Then draw a Histogram, a Less Than Ogive, and a More Than Ogive."

The Exact Raw Dataset ($N = 40$ observations)

What you will master:

  • Ascending sorting & range exploration
  • Designing continuous class boundaries
  • Continuous data grouping rules (tallying)
  • Calculating relative, cumulative & "more-than" frequencies
  • Drawing adjacent rectangles in Histograms
  • Plotting Less Than & More Than Ogives

Dataset Summary

Total Sample size
$N = 40$
Minimum Value
12
Maximum Value
57
Range
45

Grouped Continuous Frequency Master Table

Compiled from the initial 40 core observations.

Class Interval (Discrete Limits) Continuous Class Boundary Frequency ($f$) Cumulative Frequency ($CF \text{ Less Than}$) More Than Cumulative Frequency