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Understanding the essence of correct sample size

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A good research is one that is well-designed and leads to high accuracy with the correct sample size. 

Adequate sample size will meet your requirements for accuracy in quantitative study results. It is generally decided by a mix of predicted confidence, budget, and analysis of resource availability.

Here we will discuss how you can achieve the correct sample size and its importance. 

What is the survey sample size?

In market research, sample size refers to the number of individuals included in a sample size. It is a group of subjects chosen from the general population who are considered to be representative of the target population for that specific study.

The correct sample size process includes:

  1. Defining the population that is the object of the research
  2. Choosing the sampling size frame and procedure
  3. Establishing the mechanism of the selection of the sample size units
  4. Determining the mother of the sample size
  5. Choosing the exact sample size unit
  6. Carrying out field activity

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How to calculate the correct sample size?

The calculation of sample size is a critical part of every research. It should be done at the planning stage of a study, based on the type of proposed study and study design.

The sample size can be calculated using a formula:

Where,

  • Z-score is determined by the confidence level
  • Margin of error is the confidence interval

Following is the list for basic z-scores:

  • 90% – Z Score = 1.645
  • 95% – Z Score = 1.96
  • 99% – Z Score = 2.576

For instance, assume that you want 95% confidence level, 0.2 standard deviation, and confidence interval of 4%.

Using the formula, your correct sample size would be:

Sample size = (1.96)2 * 0.2 * (1-0.2)/ (0.04)2

= 3.92 * 0.2 * 0.8/0.08

= 0.6272 /0.08

=7.84

This covers how to calculate the sample size, let us now explore the importance of correct sample size.

Importance of correct sample size

Whatever market research or study you’re conducting, to understand your consumers or the success of your products, it is challenging to collect data from everyone you’re interested in.

Researchers choose a sample (or subset) of their community of interest and look for insights from that sample. This helps them draw factual insights about their larger and more diverse target population’s attitudes and behaviors without having to address the entire population. 

When we consider the well-documented relevance of sample size in quantitative and qualitative research, the value of choosing sample size is rapidly brought into focus.

The capacity to conclude with sufficient confidence in quantitative research depends on a correct sample size calculation since this can lead to erroneous results. It may also render a study immoral, unpublishable, or both.

While qualitative research projects do not normally require as big a sample size as quantitative research, they still need to be large enough to reveal the range of opinions required to answer their questions and produce findings of sufficient value to their field of study.

Determine the accuracy of your survey data with our FREE MoE calculator.

Calculate the Margin of Error

Tips for correct sample size

Calculation of sample size is a complicated process for those who don’t have experience with statistical calculations. The correct sample size is influenced by various factors.

A small sample size may result in outliers and anomalies. These distort the data, and you don’t obtain a true representation of the population.

With a large sample size, the entire research becomes difficult, costly, and time-consuming to perform.  While the results are more accurate, the advantages do not exceed the costs.

How to fix the large sample size results?

If your sample size is too large to manage, you may alter the results to get the correct sample size by

  • lowering your confidence level or 
  • raising your margin of error.

This increases the possibility of sampling error but can significantly reduce the number of responses required.

The following table shows what effect survey values have on the accuracy of its results:

 

Value increased

Value decreased

Population size

Accuracy decreases

Accuracy increases

Sample size

Accuracy increases

Accuracy decreases

Confidence level

Accuracy increases 

Accuracy decreases

Margin of error

Accuracy decreases

Accuracy increases

[Also read: Understanding Sample Size: How To Ensure Your Survey Delivers Better Results]

What problems are faced with sample size?

There are many problems that researchers face if they fail to calculate the correct sample size. Some of them are as follows:

  1. A small sample size results in ambiguous data, thus skewing your entire research. 
  2. A small sample size decided due to convenience or for cost-efficiency stops you from achieving statistical significance.
  3. Lack of correct sample size may leave you with data unrepresentative of the target audience. As a result, leading you to make assumptions about the population.

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Conclusion

The correct sample size determines your survey’s authenticity and integrity. It is especially critical in quantitative research, where reliable data is the key to achieving actionable results.

Using a correct sample size enhances the likelihood that your survey findings will correctly reflect the opinions of your target population. After determining the sample size, you may now find respondents for specific research.

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