Normally we use mean value to express sociodemographic characteristics of respondents ( e.g. average age of rice farmers). In few articles, median was used instead of mean. How can I differentiate, where to use mean and where to use median?
The median is generally considered to be the best representative of the central location of the data. The more skewed the distribution, the greater the difference between the median and mean, and the greater emphasis should be placed on using the median as opposed to the mean. https://statistics.laerd.com/statistical-guides/measures-central-tendency-mean-mode-median.php
If you have a skewed distribution, the median is often the best measure of central tendency. When you have ordinal data, the median or mode is usually the best choice. https://statisticsbyjim.com/basics/measures-central-tendency-mean-median-mode/
The median is usually preferred to other measures of central tendency when your data set is skewed (i.e., forms a skewed distribution) or you are dealing with ordinal data. https://statistics.laerd.com/statistical-guides/measures-central-tendency-mean-mode-median-faqs.php
The median provides a helpful measure of the centre of a dataset. By comparing the median to the mean, you can get an idea of the distribution of a dataset. When the mean and the median are the same, the dataset is more or less evenly distributed from the lowest to highest values https://www.abs.gov.au/ausstats/[email protected]/Products/6FA51527EA94B3CCCA25747400158EB5?opendocument
As Dr. Kan pointed out, when data are not normally distributed around the mean and there is indication of a skewed distribution, then it is better to use the median instead of the mean. Thus, you have to check for normality first.