The Assumed Mean Method is a practical approach for calculating the mean from grouped data. In this method, a value 'a' is assumed as the reference or the mean value based on the dataset's central tendency. The differences between the actual midpoints and this assumed mean are calculated, leading to a simplified computation of the mean. The formula follows:
Formula:
$$x = a + \frac{\Sigma fd}{\Sigma f}$$
where
- a: Assumed mean
- Σfd: Sum of the product of frequency and deviation from the assumed mean
- Σf: Total frequency
One can choose 'a' to be around the central values of the dataset to minimize computational effort and errors. Through this method, one can transform larger datasets into manageable calculations, emphasizing the practicality of the Assumed Mean Method, especially when computing the mean is tedious.