Standard Deviation (Leaving Cert Mathematics): Revision Notes
📚 Revision Notes
Standard Deviation of Frequency Distribution by Hand
Overview
The standard deviation measures the spread of data around the mean in a frequency distribution. Calculating it by hand for grouped data involves the following steps:
Formula for Standard Deviation
Where:
- : Midpoint of each class interval.
- : Mean of the distribution.
- : Frequency of each class.
- : Sum of the squared deviations multiplied by their frequencies.
- : Total frequency.
Steps to Calculate Standard Deviation
- Calculate the Mean ():
- Use the formula:
- Find Deviations:
- Subtract the mean from each midpoint ().
- Square the Deviations:
- Square each deviation
- Multiply by Frequency:
- Multiply the squared deviations by their respective frequencies
- Sum Up:
- Add all the values to get the total deviation.
- Calculate Standard Deviation:
- Divide the total deviation by the total frequency
- Take the square root.
infoNote
Worked Example
Problem
Calculate the standard deviation for the following grouped frequency distribution:
| Interval | Frequency () |
|---|---|
| 10–20 | 3 |
| 20–30 | 5 |
| 30–40 | 8 |
| 40–50 | 4 |
Solution
Step 1: Calculate Midpoints
| Interval | Midpoint () | Frequency () |
|---|---|---|
| 10–20 | 15 | 3 |
| 20–30 | 25 | 5 |
| 30–40 | 35 | 8 |
| 40–50 | 45 | 4 |
Step 2: Find Mean ()
Step 3: Compute Deviations and Squares
| 15 | 3 | −16.5-16.5 | 272.25 | 816.75 |
| 25 | 5 | −6.5-6.5 | 42.25 | 211.25 |
| 35 | 8 | 3.53.5 | 12.25 | 98.00 |
| 45 | 4 | 13.513.5 | 182.25 | 729.00 |
Step 4: Total Deviation
Step 5: Standard Deviation
Answer: The standard deviation is approximately
:::
Summary
- The standard deviation measures data spread within a frequency distribution.
- Steps:
- Calculate midpoints.
- Compute the mean.
- Find deviations () and square them.
- Multiply squared deviations by frequency.
- Sum up and divide by total frequency.
- Take the square root to get the standard deviation.
- Standard deviation provides valuable insights into data variability and distribution.