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Grouped Frequency Distributions Simplified Revision Notes

Revision notes with simplified explanations to understand Grouped Frequency Distributions quickly and effectively.

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Grouped Frequency Distributions

Overview

A grouped frequency distribution is a method of organising data into intervals (called classes or bins) to summarise and display large data sets more effectively. Each interval is associated with a frequency, which indicates the number of data points that fall within that range.

Key Components of a Grouped Frequency Distribution

Class Intervals:

  • Non-overlapping ranges that divide the data.
  • Intervals are usually of equal width for simplicity.
  • Example: 1020,2030,304010-20, 20-30, 30-40

Frequency (ff):

The number of data points within each class interval.

Midpoint (xx):

The central value of a class interval:

Midpoint=Lower Bound+Upper Bound2\text{Midpoint} = \frac{\text{Lower Bound} + \text{Upper Bound}}{2}

Cumulative Frequency:

The running total of frequencies, showing how many data points fall below the upper limit of each interval.

Relative Frequency:

Proportion of data in each interval, expressed as a fraction or percentage:

Relative Frequency=FrequencyTotal Frequency\text{Relative Frequency} = \frac{\text{Frequency}}{\text{Total Frequency}}

Steps to Create a Grouped Frequency Distribution

Step 1: Determine Range:

Subtract the smallest data value from the largest.

Step 2: Choose the Number of Intervals:

Commonly, use between 5 and 10 intervals depending on the data set size.

Step 3: Calculate Interval Width:

Interval Width=RangeNumber of Intervals\text{Interval Width} = \frac{\text{Range}}{\text{Number of Intervals}}

Step 4: Create the Intervals:

Start from the smallest data value and add the interval width to form consecutive intervals.

Step 5: Tally Frequencies:

Count how many data points fall into each interval.


Worked Examples

infoNote

Example 1: Creating a Grouped Frequency Table

Problem: The ages of 20 people are: 12,13,15,16,16,17,18,19,19,20,21,22,23,24,24,25,26,27,28,30.12, 13, 15, 16, 16, 17, 18, 19, 19, 20, 21, 22, 23, 24, 24, 25, 26, 27, 28, 30.


Solution:

Step 1: Range:

Range=3012=:highlight[18]\text{Range} = 30 - 12 = :highlight[18]

Step 2: Intervals:

Choose 5 intervals:

Interval Width=185:highlight[4]\text{Interval Width} = \frac{18}{5} \approx :highlight[4]

Step 3: Create Intervals:

1215,1619,2023,2427,283112−15,16−19,20−23,24−27,28−31

Step 4: Tally Frequencies:

Count how many ages fall into each interval.


Grouped Frequency Table:

IntervalFrequency (ff)Midpoint (xx)Cumulative Frequency
12–15313.53
16–19517.58
20–23421.512
24–27625.518
28–31229.520

infoNote

Example 2: Calculating Relative Frequency

Problem: Use the table above to find the relative frequency of each interval.


Solution:

Step 1: Calculate Total Frequency

(f)::highlight[20](\sum f): :highlight[20]


Step 2: Calculate Relative Frequency for each interval:

  • 1215:320=:highlight[0.15]12−15: \frac{3}{20} = :highlight[0.15] (15%)
  • 1619:520=:highlight[0.25]16-19: \frac{5}{20} = :highlight[0.25] (25%)
  • 2023:420=:highlight[0.20]20−23: \frac{4}{20} = :highlight[0.20] (20%)
  • 2427:620=:highlight[0.30]24-27: \frac{6}{20} = :highlight[0.30] (30%)
  • 2831:220=:highlight[0.10]28-31: \frac{2}{20} = :highlight[0.10] (10%)

Relative Frequency Table:

IntervalFrequency (ff)Relative Frequency
12–1530.15
16–1950.25
20–2340.20
24–2760.30
28–3120.10

Summary

  • A grouped frequency distribution organises data into intervals, making it easier to analyse large data sets.
  • Key components:
    • Class Intervals, Frequencies, Midpoints, Cumulative Frequency, and Relative Frequency.
  • Steps:
    1. Calculate the range and interval width.
    2. Create class intervals.
    3. Count and record frequencies.
    4. Calculate midpoints and relative frequencies.
  • Grouped frequency distributions simplify patterns and trends in data.
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