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# Central Tendency and Dispersion in Business Data Analysis Central tendency and dispersion are two fundamental concepts in statistical analysis that help researchers and managers understand the characteristics of a set of numerical data. In business research, large volumes of data are collected regarding sales, costs, profits, employee performance, customer satisfaction, production, inventory, and market conditions. Raw data by itself may be difficult to interpret because individual observations can vary considerably. Measures of central tendency provide a representative or typical value of the dataset, while measures of dispersion indicate the extent to which individual observations differ from this central value. Together, these measures enable managers to summarise, compare, interpret, and make decisions based on business data. Central tendency refers to the statistical tendency of observations to cluster around a central or typical value. The three most commonly used measures of central tendency are mean, median, and mode. The arithmetic mean is calculated by adding all observations and dividing the total by the number of observations. If the monthly sales of five branches are ₹20 lakh, ₹25 lakh, ₹30 lakh, ₹35 lakh, and ₹40 lakh, the mean sales are ₹30 lakh. The mean uses every observation in the dataset and is therefore widely used in business and statistical analysis. It is particularly useful when the data are quantitative and reasonably balanced. However, the mean can be strongly influenced by extremely high or low observations. For example, the average income of employees may be distorted if a few senior executives receive exceptionally high salaries. The median is the middle value when observations are arranged in ascending or descending order. If there are an odd number of observations, the median is the central observation; when there is an even number, it is generally obtained by averaging the two middle observations. The median is less affected by extreme values than the mean. Consequently, it is _______ ________ _________ _________ _____ __________ ______ ________ _______ ___ _______ _________.
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