01 Key Concepts
Mean Formula
Add up every value in the dataset, then divide by how many values there are.
Population Mean vs. Sample Mean
The population mean is written mu (calculated from the entire population); the sample mean is written x-bar (calculated from a sample).
Sensitivity to Outliers
The mean is heavily influenced by extreme values — a single very large or very small number can pull the mean away from what feels 'typical'.
Weighted Mean
Used when values contribute unequally; multiply each value by its weight, sum the results, then divide by the total weight.
When to Use the Mean
Best for symmetric datasets without extreme outliers; for skewed data, the median is often more representative.
02 Key Formulas
- Mean = (sum of all values) / (number of values)
03 Solved Examples
Example 1 Find the mean of 4, 8, 6, 10, 12.
- Sum = 4+8+6+10+12 = 40.
- Count = 5.
- Mean = 40/5.
Answer: 8
Example 2 A class of 5 students scores 60, 70, 80, 90, and 100 on a quiz. Find the mean score.
- Sum = 60+70+80+90+100 = 400.
- Count = 5.
- Mean = 400/5.
Answer: 80
Example 3 Add an outlier of 500 to the dataset 10, 12, 14, 16 and see how the mean changes.
- Original mean: (10+12+14+16)/4 = 52/4 = 13.
- New mean with 500: (10+12+14+16+500)/5 = 552/5.
Answer: New mean = 110.4, dramatically pulled up by the outlier
04 Practice Questions
1Find the mean of 2, 4, 6, 8.
5
2Find the mean of 15, 20, 25.
20
3Find the mean of 100, 200, 300, 400, 500.
300
4Why is the mean sensitive to outliers?
Because it uses every value's exact size, so extreme values pull it strongly in their direction
5Find the mean of -5, 0, 5, 10.
2.5
📄 Mean — Downloadable Worksheet
10 questions with a full answer key. Grab the PDF to print, or try the interactive version in your browser.