If you are debating using a sample size calculator for your survey or doing the calculations on your own, the former is better – and for many reasons. Instead of spending time and effort on the complicated equation that can succumb to human error, using a sample size calculator is faster, easy to use, and provides more accurate results.
Let’s see the basics of using the sample size calculator, what variables that you need to plug into, and why the Z score is important in your determination of the sample size!
How can I calculate the sample size?
First off – what is the sample size? Before you can calculate the proper sample size for your survey, you need to know what this is. Simply put, the sample size is a term that means you are taking a random sample of the entire population that you are curious about. Since this subgroup of people is going to be able to represent the entire population without being focused on a specific subgroup of people – females, those over 40 years old, athletes, etc – you can get an accurate representation of the entire population that you are interested in.
The sample size is an important factor when it comes to creating and carrying out your survey. If your survey sample size is too small, you might have outliers and random answers that are going to alter the average mean of the results for your population. If the sample size is too big, then it can be too complicated and costly to run – this means that you may end up shutting down the survey before it is even complete.
But what is the ideal sample size for my survey? There are a few things that you need to take into account before you can create the ideal sample size – by learning about the population size, margin of error, confidence level, and standard deviation, you can calculate the best sample size for your population:
- The population size is the entire group of people that you are talking about that you want to get more information on.
- The margin of error is how many mistakes that you will allow per survey – basically, you will be able to see the percentage of the difference between the mean results and the outliers in your survey.
- The margin of error is one of the most important factors in your survey sample size. Since this relates to the amount of error that the results will obtain, you can then see the accuracy of your survey by analyzing these results. A high margin of error shows that there is less confidence in your survey, here’s a lower margin of error that shows that you are confident in the procedures of your survey.
- The confidence level is the sureness in your survey that you believe the result will fall within the preset margin of error. If you are 95% sure that your results will fall within a 4% margin of error, then your confidence level is 95%.
- The standard deviation is the spread of results around the mean of your survey – if you find that the results of the survey are all clustered around the central mean, then you will have a low standard deviation.
What is the z score?
Another variable that you may have heard of – but you are unsure what it means – is the z score. The z score is basically a term that can give the user a guess as to how far away from the mean of the results that a data point is lying. In other words, since we know about the standard deviation now, the z score is the number of standard deviations that occur below or above the mean of your survey. Since the standard deviation is the scope of the results, the z score takes into account the distance of the spread of the result and how often it occurs in a survey.
Usually, a score is normally distributed on a graph curve. It typically has between -3 and +3 standard deviations, with the negative standard deviations ending up way below the standard distribution curve. The normal distribution curve is the representation on a graph of the mean of the numbers of a survey – if the numbers are falling way below or way over this curve, this is the measure of the z score spread.
Taking into account the margin of error and z score are two important variables in calculating your sample size! By understanding the importance of these two variables, you can calculate an accurate sample size for your upcoming survey.
Addsion Is a Blogger and an SEO professional. Co-founder of dsnews.co.uk, I have 2 years of experience in SEO & 1 year of Successful blogging @ dsnews.co.uk. I have a passion for SEO & Blogging, Affiliate marketer & also interested to invest on profitable stocks.