There are four basic types of data: nominal, ordinal, interval and ratio.
Ratio data is quantitative data. For ratio data we can obtain all three basic measures of central tendency: mode, median and mean. Moreover, we can obtain both geometric mean and arithmetic mean from this kind of data.
Interval data is also quantitative data. For interval data we can obtain all three basic measures of central tendency: mode, median and mean. But here we can calculate only arithmetic mean.
Ordinal data is qualitative data. For ordinal data we can obtain only median and mode. Mean is not acceptable measure.
Nominal data is also qualitative data. For nominal data we can obtain only mode. Other measures of central tendency are not acceptable for this kind of data.
According to statistics.laerd.com, “the mean is usually the best measure of central tendency to use when your data distribution is continuous and symmetrical, such as when your data is normally distributed. However, it all depends on what you are trying to show from your data. 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. However, the mode can also be appropriate in these situations, but is not as commonly used as the median.”
A pie chart shows us the ratio of shares of each category in a whole. Thus, 11% of employment opportunities are in education, communication and governmental services, 15% are in agricultural and forestry production, 27% are in science and engineering and 47% are in management and business.