Data Collection
Definition: Data collection is the process of gathering information to answer a research question. It’s like collecting facts or details to learn something.
Simple Explanation: When you do research, you need info—like numbers, words, or observations. Data collection is how you get that info.
Example: Imagine you want to know how much time students spend on homework. You could collect data by giving them a survey asking, “How many hours do you study each day?” Their answers are your data.
Sampling Design
Definition: Sampling design is the way you choose who or what to collect data from. It’s about picking a small group (sample) that represents a bigger group (population).
Simple Explanation: You can’t ask everyone in the world, so you pick a few people or things to study. How you pick them is your sampling design.
Example: If you want to find the average height of kids in a school, you can’t measure all 1,000 students. Instead, you might randomly pick 50 kids to measure. Randomly picking them is your sampling design.
Why They Matter
Data collection gets you the info you need, and it has to be clear and correct.
Sampling design makes sure the group you study is a good match for the bigger group you’re curious about.
Together, they help you trust your research results!
Another Example (Putting It Together)
Question: Do people like online classes?
Sampling Design: Pick 100 students—25 from each grade (1st, 2nd, 3rd, 4th year)—so all grades are included. This is called stratified sampling.
Data Collection: Send them a survey asking, “Do you like online classes? Why or why not?” Their answers are your data.
That’s it! Data collection is about getting the info, and sampling design is about choosing who gives you that info. Both help make research easy to understand and reliable.