How to decide on Sample Size in research ?

Summary

In this video, Prasad Shakram explains how to determine the right sample size for research studies, focusing on essential factors like population size, margin of error, confidence level, standard deviation, and z-score. He outlines that choosing an appropriate sample is crucial for accurate results and shares the sample size formula to use when the population is unknown. The video also discusses how sample size changes with different confidence levels and margin of errors, emphasizing the importance of consistency in statistical methods. Practical examples and the use of online calculators are provided for better understanding, ensuring researchers can make informed decisions for their studies.

Takeaways

• 😀 Sample size determination is crucial in research, ensuring that your results are statistically valid.
• 😀 There are two main types of sampling: probability sampling and non-probability sampling. The sample size should be decided before choosing the sampling technique.
• 😀 Key factors influencing sample size include population size, margin of error, confidence level, standard deviation, and z-score.
• 😀 Population size refers to the entire group of people or subjects you're studying. It can be either known or unknown, depending on your research.
• 😀 Margin of error (confidence interval) reflects the range of error in your results. A typical margin of error is ±5%.
• 😀 Confidence level refers to how confident you are that your sample reflects the population. Common levels are 90%, 95%, and 99%, with 95% being most common.
• 😀 Standard deviation measures how much individual data points deviate from the mean. A standard deviation of 0.5 is generally accepted for most studies.
• 😀 Z-score corresponds to your confidence level and is essential for calculating sample size when the population size is unknown.
• 😀 To calculate sample size, use the formula: (Z^2 × σ × (1 - σ)) / E^2, where Z is the z-score, σ is the standard deviation, and E is the margin of error.
• 😀 If you know the population size, you can use an online sample size calculator to easily determine the required sample size based on the confidence level and margin of error.
• 😀 For large populations, the required sample size stabilizes around 385 when using standard confidence levels and margin of error. For small populations, the sample size may be close to the total population.

Q & A

What is the main focus of this video?

The main focus of this video is to guide viewers on how to decide the appropriate sample size for a research study.

What are the two types of sampling mentioned in the video?

The two types of sampling mentioned are probability sampling and non-probability sampling.

Why is it not feasible to study the entire population in research?

It is not feasible to study the entire population due to practical challenges, such as the difficulty and cost involved in studying large groups of people, which is why a sample is selected.

What does the margin of error represent in research?

The margin of error, or confidence interval, represents the acceptable level of error in the study. A typical margin of error used in research is ±5%.

What are the three common confidence levels used in research?

The three common confidence levels are 90%, 95%, and 99%, with 95% being the most commonly used.

How does the confidence level impact the sample size?

As the confidence level increases, the required sample size also increases. Higher confidence levels provide more reliable results but require larger sample sizes.

What is the standard deviation, and what is the accepted value for research?

The standard deviation measures the variation from the mean in a dataset. An accepted standard deviation value for research is 0.5, with lower values being preferable for better statistical significance.

Why is the z-score important in determining sample size?

The z-score is important because it corresponds to the confidence level chosen for the research. It is used in calculating the sample size when the total population size is unknown.

What is the formula used to calculate the sample size when the population size is unknown?

The formula to calculate the sample size when the population size is unknown involves multiplying the z-score by two, then the standard deviation, and dividing by the margin of error squared.

How can researchers calculate the sample size when the population size is known?

When the population size is known, researchers can use an online sample size calculator where they input the population size, margin of error, and confidence level to get the required sample size.