Numerical data is collected in number form. This data is measurable, that means the data is about the particular characteristic or it can be used in order to determine the trend of particular variables. There are several applications for numerical data. Some of the examples of numerical data are: census, age, height, marks of students, scores of players, time taken to complete certain tasks, temperature, annual income, etc.
As we know, different cities will be having different weather conditions. For example, consider two cities of different types of weather. One can be a city which is in the middle of the country and the other one is a coastal area. It is easy to analyse that the range of daily high temperatures for cities of the coastal region is smaller than for cities in the middle of the country. However, the standard deviation of the daily high temperature for the coastal city will be less than that of the other city. All these values are represented with numbers, that means, it is quantitative data.
In any sports team, there will be players where some are good at some things and not at others. The players who are ranked highest will not show many differences in their abilities. They do well in most of the categories. The lower the standard deviation of their abilities in each category, it is treated in the way that they are more balanced and consistent. Players with higher standard deviation will be less identified. This data helps in understanding the form of the player.
One of the special types of numbers are complex numbers. We can define complex numbers as an ordered pair of two real numbers. The complex numbers contain a number i, an imaginary unit. The value of i is the square root of -1. Every complex number is represented as a+ib, where x and y real numbers are respectively called the real part and imaginary part of the complex number. Complex numbers are useful conceptual quantities that can be used in calculations and result in physically meaningful solutions. These numbers helps in solving any polynomial.