What are some common misconceptions about sample size in research?

What are some common misconceptions about sample size in research?

One common misconception is that a larger sample size always leads to more accurate results. While larger samples can reduce variability, they don't guarantee accuracy if the sample isn't representative.

So, does that mean a small sample can be useful?

Yes, a small sample can be useful if it's well-chosen and representative of the population. It's all about the quality of the sample, not just the quantity.

What about the idea that you need a minimum sample size for validity?

That's another misconception. While certain statistical tests have minimum sample size requirements, validity often depends more on how the sample is selected than on its size.

Can you explain how to determine the right sample size?

Determining the right sample size involves considering the population size, the desired confidence level, and the margin of error you can accept. Statistical formulas can help with this.