Table of Contents
Introduction of Mean Deviation Method
The mean deviation (MD) method is a technique used to estimate the variability of a population. It is a measure of the average distance of individual data points from the mean. The MD method can be used to estimate the standard deviation of a population or the variance of a population.
Types of Data
There are three types of data:
-Numeric data: This is data that can be represented by numbers, such as the number of people in a room or the temperature outside.
-Categorical data: This is data that can be represented by categories, such as the colors of the rainbow or the types of animals.
-Text data: This is data that is made up of words, such as a person’s name or a sentence.
Calculating the Mean Deviation for Ungrouped Statistics
The mean deviation for ungrouped statistics is calculated by taking the average of the absolute deviations from the mean. The absolute deviation is the distance of each value from the mean, measured in terms of the magnitude of the number. For example, if the mean is 5 and a value is 7, the absolute deviation is 2 (7-5). To calculate the mean deviation, simply add up all of the absolute deviations and divide by the number of values.
1. Calculating the Central Tendency i.e. Mean and Median
The mean of a set of data is found by adding up all the data points and dividing by the number of data points.
The median of a set of data is found by arranging the data points in numerical order and finding the middle number.
2. Calculating the Variability
The variability of a set of data is found by calculating the standard deviation.
2. Calculating Mean Deviation
To calculate the mean deviation of a set of data, we first calculate the mean of the data set. We then subtract each value in the data set from the mean and then divide that number by the number of data points in the set.
The mean deviation of a set of data is:
MD = (Σ(x-x̄)) / n
Calculating the Mean Deviation for Ungrouped data step wise
The Mean Deviation for Ungrouped data can be calculated step wise by dividing the Sum of Squares by the number of data points in each step.
The Mean Deviation for Ungrouped data can be calculated step wise by dividing the Sum of Squares by the number of data points in each step.
Step 1:
Sum of Squares = 15
Number of points = 5
Mean Deviation = 3
Step 2:
Sum of Squares = 25
Number of points = 7
Mean Deviation = 3.57
Step 3:
Sum of Squares = 35
Number of points = 9
Mean Deviation = 3.89
