Question

What does qualitative, quantitative data, discrete, and continuous mean?

Answer 1

Qualitative data, also known as the categorical or attribute data, deals with characteristics and descriptors that can't be easily measured, but can be observed subjectively. Quantitative data, also known as numerical data, deals with numbers and things you can measure objectively, for example, dimensions such as height, width, and length, temperature and humidity, prices, area and volume. . Discrete data is a count that cannot be made more precise. Continuous data could be divided and reduced to finer and finer levels.

Complete step-by-step answer:
Let us first see what is meant by qualitative data. Qualitative data, also known as the categorical or attribute data, deals with characteristics and descriptors that can't be easily measured, but can be observed subjectively. We can say that smells, tastes, textures, attractiveness, and color are all examples of qualitative data. We can see that qualitative data are not numerical.
Let us see the types of qualitative data. There are 3 types of this data, viz. binary, nominal and ordinary. Binary data place things in one of two mutually exclusive categories: right/wrong, true/false, or accept/reject. For example, suppose we are given with broken marble and unbroken marble. We will categorize the marbles are good or bad. This type of statistical model is the binary data model. Nominal data is one of the types of qualitative information which helps to label the variables without providing the numerical value. Nominal data is also called the nominal scale. If we categorize the marbles based on colour, then this data will be termed as nominal. We can examine the nominal data using the grouping method. In this method, the data are grouped into categories, and then the frequency or the percentage of the data can be calculated. We have to visually represent these data using the pie charts. Ordinal or ordered data/variable is a type of data which follows a natural order. For example, if we can categorize the marbles based on size like small, medium and large, in an ordered manner, then this data will be ordinal. We can represent the ordinal data using a bar chart. These data are investigated and interpreted through many visualization tools. The information may be expressed using tables in which each row in the table shows the distinct category.
Now, let see about quantitative data. Quantitative data, also known as numerical data, deals with numbers and things you can measure objectively, for example, dimensions such as height, width, and length, temperature and humidity, prices, area and volume. In other words, we can say that quantitative data represents the numerical value.
We can classify quantitative data into two types, viz. continuous and discrete data. Continuous data could be divided and reduced to finer and finer levels. We can say that the measurement of height, weight, daily temperature of a place and daily wind speed are examples of continuous data. Continuous data has an infinite number of probable values that can be selected within a given specific range. Discrete data is a count that cannot be made more precise. It involves integers. In other words, we can say that discrete data contains only a finite number of possible values. If we tally the number of marbles in a box, that number is a piece of discrete data.

Note: Students must know that continuous and discrete data fall under quantitative data. When we measure something and represent it with a number value, we create quantitative data. When we classify or judge something, we create qualitative data.