**What is Parameter in Statistics?**

**In statistics, a parameter is a specific number or fact that describes an entire group or population. **It’s not a guess or an estimate; it’s an exact value because it considers everyone in the group.

Imagine you’re in a town called “Statville” with exactly 10,000 residents. You want to know **the average height** of EVERY person in this town.

After measuring **everyone**, you find out the average height is 165 cm.

**This average height of 165 cm for the entire town is called a “parameter”.** It represents a fact about the whole population of Statville.

**µ**: The average (or mean) of a population is symbolized by µ. In our Statville example, µ would be 165 cm.**σ**: The standard deviation of a population, which tells us how spread out the heights are around the average.

**Key Points**:

**Parameter vs Statistic**

**Parameter**: An exact value that describes a characteristic of the entire group or population.**Statistic**: A value derived from a subset or sample of the group or population, used to estimate a parameter.

While both parameters and statistics provide valuable insights, they serve different purposes and are derived from different sources.

**Parameter**

- Refers to
**the entire population**. **Constant**and doesn’t change unless the population itself changes.

If we were to measure the height of every adult in a country, the average would be a parameter.

**Statistic**

- Refers to
**a sample**taken from the population. - Can
**vary**depending on the sample.

If we measure the height of 100 randomly selected adults from the same country, the average would be a statistic.