🎯Key Concepts: Sampling strategies, Correlational research, Target population, Random sampling, Stratified sampling, Opportunity sampling, Self-selected sampling, Generalizability, Representativeness, Population validity.

Just like picking your team for a fun game of dodgeball, researchers also have to "pick their team" in research studies, except we call this 'sampling.' Sampling strategies in correlational research follow the same rules as in experiments. 👩‍🔬👨‍🔬

The process starts with identifying the target population, just like you would scope out the best players for your dodgeball team. The target population is picked based on the study's aims. It's like the pool of all potential dodgeball players you might choose from. 🏊‍♀️

From this pool, a sample is drawn using one of the following methods:

Random Sampling: This is the luck-of-the-draw method. Everyone in your population pool has an equal chance of being chosen. Imagine picking names out of a hat! 🎩🎫

Stratified Sampling: This is like organizing players by skill level (beginner, intermediate, pro), and then picking a few from each group. This way, your team has players of all skill levels, just like your sample will have people from all strata of the population. ⚖️

Opportunity Sampling: This is grabbing whoever's available! Say you're at the park and pick your team from whoever's around. Similarly, researchers sometimes pick samples from whoever's available and willing to participate. 🚶‍♂️🚶‍♀️

Self-selected Sampling: This is when people volunteer to be part of the study, like if you put up a poster saying "Join our dodgeball team!" and take whoever shows up. 🙋‍♀️🙋‍♂️