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# Measures of Central Tendency Measures of central tendency are statistical measures used to identify and describe the central or typical value of a set of observations. In epidemiology and public health, large amounts of numerical data are collected regarding diseases, mortality, morbidity, nutritional status, demographic characteristics, health-service utilization, and other population health indicators. It is often difficult to understand a large dataset by examining every individual observation. Measures of central tendency provide a single value that represents the centre of the distribution and helps researchers summarize and interpret health-related data. The three major measures of central tendency are mean, median, and mode. Each measure has a different method of calculation and is appropriate under different circumstances. Their selection depends on the nature of the data, the distribution of observations, and the purpose of analysis. The arithmetic mean, commonly called the mean or average, is obtained by adding all observations and dividing their sum by the total number of observations. If the observations are (x_1, x_2, x_3,\ldots,x_n), the mean is expressed as: Mean = Sum of all observations / Number of observations For example, if the ages of five patients attending a health centre are 20, 25, 30, 35 and 40 years, the mean age is 30 years. In epidemiology, the mean is frequently used for variables such as age, height, weight, blood pressure, serum cholesterol, haemoglobin level, duration of hospital stay, and number of clinic visits. The mean uses every observation in the dataset and therefore provides a useful summary when the data are approximately symmetrically distributed. However, it is sensitive to extreme values. For example, if the ages of patients are 20, 22, 25, 27 and 80 years, the mean is considerably increased by the single very high observation. Therefore, the mean may not adequately represent the typical individual when the distribution _________ _______ _______ ___ ___ _______ ___.
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