Measures of central tendency are statistical tools used to summarize a set of data by identifying the central or typical value within the distribution. These measures are essential in social work research as they provide a simple yet effective way of analyzing data and drawing meaningful conclusions about a population or a sample. The three most commonly used measures of central tendency are the mean, median, and mode, each offering a different perspective on the data set. The mean is the arithmetic average of a set of values. To calculate the mean, one must sum all the values in the data set and then divide by the number of values. The mean is particularly useful when dealing with continuous data that follows a normal distribution. It provides a balanced measure that incorporates every value in the data set, making it an accurate representation of the data when there are no extreme values, or outliers. For instance, in a study of social work clients’ income levels, the mean income could give a general idea of the average earnings in a community. However, the mean is sensitive to outliers—extremely high or low values that deviate from the rest of the data. This can skew the mean, leading to a distorted representation of the data, especially in cases of highly varied or skewed distributions. The median is the middle value of a data set when the values are arranged in ascending or descending order. If the number of data points is odd, the median is the value in the middle; if the number is even, it is the average of the two middle values. The median is a more robust measure than the mean when the data set includes outliers or skewed distributions. For example, in the case of social work research on housing, if most families have similar income levels but a few have extremely high incomes, the median income would provide a better understanding of the typical