Category : Standard Error

Benefits Of Using A Standard Error Calculator

When you are learning and studying statistics, you will soon realize that you need to use calculators to determine a wide variety of variables. The truth is that while you can do some of these calculations by hand (especially when you are dealing with small samples of population), it is easy to make mistakes. So, you want to ensure that you always have a good standard error calculator in hand. 

standard error calculator

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Before we show you the benefits of using a standard error calculator, we believe that it is important that you first understand what the standard error is first. 

What Is The Standard Error?

What Is The Standard Error?

Simply put, the standard error os a statistic is just the approximate standard deviation of a statistical sample population. So, if you want to take a more practical definition, you can also say that the standard error calculator is a statistical concept or term that determines the accuracy with which a sample distribution represents a population by using standard deviation. 

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When we are talking about statistics, it is important to always keep in mind that a sample mean deviates from the real mean of the population. And this deviation is known as the standard error of the mean. 

Understanding The Standard Error

Understanding The Standard Error

When you listen to or read the term standard error, you need to know that it refers to the standard deviation of the different sample statistics like the median or mean. For example, when you see the term standard error of the mean, then you know that it refers to the standard deviation of the distribution of sample means that were taken from a population. 

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Notice that the smaller the standard error that you get, the more representative the sample will be of the entire population. 

The truth is that there is a very deep connection between the standard error and the standard deviation. After all, for any given sample size, the standard error is always equal to the standard deviation divided by the square root of the sample size. Besides, you should also know that the standard error is also inversely proportional to the sample size. This means that the larger the sample size, the smaller the standard error. And this occurs because the statistic will always tend to approach the real or actual value. 

It’s important to understand that the standard error is considered a part of the descriptive statistics. After all, as you can easily understand, it represents the standard deviation of the mean within a dataset. Therefore, this serves as a measure of the variation of random variables, providing a measurement for the spread. So, the smaller this spread, the more accurate the dataset. 

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Benefits Of Using A Standard Error Calculator

Benefits Of Using A Standard Error Calculator

The truth is that there are many benefits of using a standard error calculator. These include:

  • Knowing how much data is clustered around the mean value
  • Getting a more accurate idea of how the data is distributed
  • Not being affected by extreme values
  • No mistakes: with a standard error calculator, you won’t make so many mistakes when you need to calculate the different variables and statistics. 

Standard Error Of Mean Vs Standard Deviation

When you are learning statistics, two of the first concepts that you will need to understand are the standard error of mean and the standard deviation. However, many students tend to confuse both. So, to prevent this from happening to you, we decided to tell you a bit more about each one of these concepts as well as show you the differences between them. 

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Standard Error Of Mean Vs Standard Deviation

standard error of mean

Simply put, the standard deviation measures the amount of dispersion or variability for a specific set of data from the mean. On the other hand, the standard error of mean measures how far the sample mean of the data is likely to be from the true population mean. 

One of the things that you should keep in mind is that the standard error of mean is always smaller than the standard deviation. 

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When They Are Both Used

Notice that in some instances, researchers can use both the standard error of mean and the standard deviation. This occurs, for example, in some clinical experimental studies. 

In these particular cases, both the standard error of mean and the standard deviation are used to display the characteristics of the sample data as well as they both serve to explain the statistical analysis results. 

Standard Error Of Mean Vs Standard Deviation

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A very important aspect to consider is that there are many researchers who tend to use both concepts as if they were the same. This is especially the case os studies related to medical literature. So, it is very important that these researchers keep in mind that the standard error of mean and the standard deviation are two different concepts. As we already explained above, the standard deviation is the dispersion of the data in a normal distribution. This simply means that this measure indicates how accurately the mean actually represents the sample data. On the other hand, the standard error of mean includes statistical inference that is based on the sampling distribution. 

Calculating Standard Error Of Mean

calculating standard error of the mean​

As you can see, when you need to calculate the standard error of mean, you need to take the standard deviation and divide it by the square root of the sample size. 

If you take a closer look at the standard deviation formula, then it is easy to understand that you need to follow some steps:

#1: Take the square of the difference between each data point and the sample mean, finding the sum of those values.

#2: Now, divide that sum by the sample size minus one, which is the variance.

#3: Finally, take the square root of the variance to get the SD.

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Bottom Line

Simply put, the standard error of mean is just an estimate of how far the sample mean is likely to be from the population mean, whereas the standard deviation of the sample is the degree to which individuals within the sample differ from the sample mean. 

So, if the population standard deviation is finite, the standard error of the mean of the sample will tend to zero with increasing sample size, because the estimate of the population mean will improve, while the standard deviation of the sample will tend to approximate the population standard deviation as the sample size increases.