Standard Error Definition
In statistics, the standard error refers to the deviation of a sample mean from the actual meaning of a particular population. When there is a diffusion of sample means around the actual mean of a population, standard error has occurred. In a simple language, standard error (SE) is the estimated standard deviation of a sample population.
Before we proceed, here are vital points you should know about standard error;
- Standard error refers to the estimate of the standard deviation of a sample population.
- It can also refer to the dispersion or disbandment of samples means around the actual mean of the population.
- A variation from the accurate meaning of a sample population can lead to the occurrence of standard error.
- According to researchers and statisticians, standard errors can be reduced when more data points are used in calculating the mean of a sample population.
A Little More on What is Standard Error
The standard deviations of various sample populations, statistics and parameters is called the standard error. When there is a variation from the accepted o accurate mean of a sample population and the calculated one, standard error has occurred. The standard error of mean can occur when there is a standard deviation of sample means from the actual mean of the population.
When calculating standard error in a particular sample population or statistics, it is calculated by dividing the standard deviation by the square root of the sample size. In statistics, the smaller the standard error, the more accurate and representative of the sample population.
It is widely believed that for a sample population to give an accurate result and be more representative, more data sets must be used. In every given sample statistics or population, the mean is estimated, a variation or deviation between the mean that is calculated and the mean given as the acceptable or accurate mean is standard error. Standard error in a sample population indicates that the sample is not representative of the entire population, it identifies shortcomings that might have occured when gathering the sample.
A spread or dispersion in the mean of variables is detected through the standard error. The smaller the standard error, the more accurate and true the population data is. The standard deviation helps to recognize the spread of data points or variables in a given sample population.