Assumed Mean Method
The Assumed Mean Method is a statistical technique used to calculate the arithmetic mean of grouped data. It simplifies manual calculations by selecting an arbitrary central value from the class marks, known as the assumed mean, and calculating the deviations of all other class marks from this chosen value. This method is highly effective when the numerical values of class marks and frequencies are large.
Key Concepts
The first step is to find the class mark for each class interval by averaging the upper and lower class limits.
An assumed mean (denoted by a) is chosen, usually the class mark located near the middle of the distribution, to minimize calculation size.
The deviation for each class is calculated by subtracting the assumed mean from the respective class mark, and the mean is found by adding the assumed mean to the weighted average of these deviations.
Real World Applications
Calculating the average daily wages of hundreds of workers in a factory where the wage brackets and number of workers are large numbers.
Determining the average monthly electricity consumption of households in a city, where data is grouped into large intervals.