# 3.1 - Samples & Populations

3.1 - Samples & PopulationsWhile Jaylen’s decision may not seem that important, he will still be working with nurses and conducting research, the idea of deciding on a sampling strategy has far reaching implications for both the statistics and the conclusions a researcher can draw from the results.

First let’s talk about populations and samples.

We, like Jaylen wanting to know more about ALL nurses, often have questions concerning large **populations**. Gathering information from the entire population is not always possible due to barriers such as time, accessibility, or cost, imagine trying to perform Jaylen’s study on every nurse across the world! Instead of gathering information from the whole population, we often gather information from a smaller subset of the population, known as a **sample**.

Values concerning a sample are referred to as sample **statistics** while values concerning a population are referred to as population **parameters**.

- Population
- The entire set of possible cases

- Sample
- A subset of the population from which data are collected

- Statistic
- A measure concerning a sample (e.g., sample mean)

- Parameter
- A measure concerning a population (e.g., population mean)

The process of using sample statistics to make conclusions about population parameters is known as **inferential statistics**. In other words, data from a sample are used to make an inference about a population.

- Inferential Statistics
- Statistical procedures that use data from an observed sample to make a conclusion about a population