SAMPLE SIZE DETERMINATION || PRACTICAL RESEARCH 2

Summary

This video lesson on sample size determination explains the importance of sampling in research, highlighting its time and cost efficiency, as well as its ability to reduce errors compared to full censuses. The presenter outlines key concepts such as population size, margin of error, and confidence levels, introducing Slovin's formula for calculating sample sizes. Through practical examples, viewers learn how to apply the formula to various scenarios. The session concludes with practice questions, reinforcing the significance of understanding sample sizes for effective research design.

Takeaways

• 😀 Samples (n) represent a selection of respondents from a total population (N) for research purposes.
• 😀 Using samples is more time-efficient compared to conducting full censuses.
• 😀 Sampling is cost-effective, as it requires less funding than full-scale surveys.
• 😀 Focused attention on specific elements is easier with samples than with complete censuses.
• 😀 Inexperienced interviewers can introduce errors, making samples less prone to reporting mistakes.
• 😀 Margin of error (e) is the allowable error in study results, often expressed as a percentage.
• 😀 A confidence interval indicates the degree of certainty about the sample size estimate.
• 😀 Slovin's formula is used to calculate sample size based on total population and margin of error.
• 😀 Example calculations illustrate how to apply Slovin's formula for determining sample size.
• 😀 Practicing with different scenarios helps solidify understanding of sample size determination.

Q & A

What is a sample in the context of research?

A sample is a selection of respondents chosen to represent the total population in a research study.

How is the total population denoted in research terminology?

The total population is denoted as capital letter 'N'.

Why is using a sample preferred over a full census?

Using a sample saves time and money, allows for more focused attention on specific elements, and reduces errors caused by inexperienced interviewers.

What does the margin of error represent in a research study?

The margin of error indicates the allowable error in the study, expressed as a percentage, which reflects the precision of the sample estimate.

What is a common confidence level used in research, and what does it indicate?

A common confidence level is 95%, indicating that researchers can be 95% certain the results are accurate.

What formula is used to calculate the sample size based on total population and margin of error?

Slovin's formula is used: n = N / (1 + N * e^2), where 'n' is the sample size, 'N' is the total population, and 'e' is the margin of error.

How do you convert a percentage margin of error into decimal form?

To convert a percentage margin of error to decimal form, divide the percentage by 100 (e.g., 5% becomes 0.05).

What was the sample size calculated for a population of 6,000 with a 5% margin of error?

The calculated sample size for a population of 6,000 with a 5% margin of error is 375 respondents.

If a study involves a total population of 500 with a 2% margin of error, what is the sample size?

The sample size for a total population of 500 with a 2% margin of error is 417 respondents.

What factors must be determined before calculating sample size?

Before calculating sample size, researchers must determine the target population and the desired margin of error.