The standard error of the mean is a measurement of how closely a sample represents the population by determining the amount of variation between the sample mean and the true population mean. It is calculated by taking the standard deviation of the sample and dividing it by the square root of the sample size. This provides an estimate of how far the sample mean is likely to be from the true population mean. The document then provides an example of measuring weights of men and calculating the standard error of the mean to determine variation from the average weight. It also outlines the 8 step process for calculating the standard error of the mean from a sample.

1. Standard Error of
the Mean
(Biostatistics)

2. Standard Error of the Mean
• If we are gathering data for scientific or
statistical purposes, the standard error of the
mean can help in determining how closely a
set of data represents that actual population.
• By verifying the accuracy of our sample, we
can know the accuracy of our study.

3. Example
• Measurement of the weight of a large sample
of men
• Their weights could range from 70 to 130 Kg.
• If we calculate the mean of the sample data,
the samples will only vary by a few kg.
• Use of standard error of the mean tells how
much the weight varies from the mean.

4. Standard error of the mean formula
SE = σ/√n
• SE = standard error of the sample
• σ = sample deviation
• n = size of the sample.

6. How to calculate the standard error of
the mean
1. Calculate the mean
2. Calculate deviation from the
mean
3. Square each deviation from the
mean
4. Calculate the sum of the squared
deviations

7. 5. Divide that sum by one less
than the sample size
6. Calculate the square root
7. Divide the standard deviation
by the square root of the
sample size
8. Calculate the standard error
of the mean

8. TAPAN KUMAR MAHATO
Assistant Professor
tapan.mahato@gmail.com

9. FINISHED