This module introduces the concept of inference: drawing conclusions about populations using samples. Once we have a research question, a theory, and a hypothesis, we must collect data on our dependent and independent variables in order to test our hypothesis.

Collecting data, however, can be challenging. In an ideal world we would collect data from every single unit that we are interested in (which we call the population). However, oftentimes this isn’t practical or even possible. When this is the case, we must rely on samples (a subset of units from the population).

When we only have data on some of the units that we are interested in, it’s crucial that we understand how that data was collected, because it matters for the conclusions that we can draw.

In this module, you will learn about populations and samples, as well as what conclusions we can make from different types of samples.

Module Learning Outcomes:

After completing this module, you should be able to...

Define a population
Define a sample
Explain how the sampling procedure affects the conclusions we can make
Explain the margin of error

The image below shows a simplified version of the scientific method, and highlights the where concepts covered in this module fit into the larger process.