What Are Measures of Central Tendency?
When we collect data — like the heights of students in a class, or the scores on a quiz — we end up with a big list of numbers. It can be hard to make sense of so many numbers at once. So mathematicians invented ways to summarise a whole dataset with just one number that represents the "centre" or "typical value" of the data.
A set of values that describe where the centre of a dataset lies. They summarise a large collection of numbers into a single, representative value. The three main measures are the mean, median, and mode.
Think of it like this: if someone asks "how tall are the students in your class?" you wouldn't list every single height — you'd say something like "about 155 cm on average." That's a measure of central tendency in action!
There is also a fourth important concept called the range, which tells us about the spread of the data — how far apart the highest and lowest values are.
Imagine you and your friends each guess how many sweets are in a jar. Measures of central tendency help you find a "best guess" from all of your answers, rather than listing every single one.
The Mean (Average)
The mean is calculated by adding all the values in a dataset together and then dividing by the number of values. It is often called the "average."
The formula for the mean is:
The mean takes every single data point into account, which makes it a very thorough measure. However, it can be affected by very large or very small values (called outliers).
Example: Finding the Mean
Five students scored the following marks in a science quiz:
Step 1: Add all the values together.
Step 2: Divide by the number of values (there are 5 students).
Answer: The mean score is 7 marks.
Be careful — if one value is very different from the rest (an outlier), the mean can be misleading. For example, if one student scored 0 and everyone else scored around 8, the mean would be dragged down and wouldn't represent most students' performance.
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