We now learn about the different types of data we'll come across in statistics.
Before learning any methods for calculations and illustrations in statistics, it is essential to know how to distinguish the different types of data we may need to analyze.
That is what we learn in this section.
To begin with, we start by watching two tutorials, below.
Do take the time to watch these as they will help in understanding.
The definitions seen in this tutorials are then written clearly, along with some examples, further down.
Qualitative data is characterized by some quality, or its belonging to some category.
The main type of statistical analysis we do with this type of data is done with graphical methods, such as bar charts, pie charts, pictograms.
Some examples of scenarios in which we'd be observing qualitative data are listed here:
Quantitative data comes in one of two categories. Those are discrete data and continuous data.
Discrete data can only take-on certain values, or certain types of values.
Given two distinct observations of discrete data it is not possible for another observation to take-on any value between them (only certain values).
For example, when buying a pair of shoes, we can buy a size \(7\) or a size \(8\). We may also be able to buy a size \(7.5\). But we cannot by a size \(7.326573\), that number is not a possible shoe size in stores.
Shoe sizes correspond to discrete data.
The following is a list of scenarious in which the data collected would be discrete quantitative data:
Continuous data is characterized by the fact that it can take-on any value between any two distinct observations.
Some typical examples of continuous data would be length and time.
For example, the World Record for \(100\)m sprint is \(9.58\)s. This value is limited by the accuracy of the instruments with which time was measured. The actual time taken to run the \(100\)m could be anything between \(9.575\)s and \(9.585\)s.
The time may well be \(9.58143256378\)s.
Data such as this, which is limited by the accuracy of the instruments with which they are measured, are contnuous.
The following is a list of scenarious in which the data collected would be continuous quantitative data:
Continuous data is measured. The actual value we use depends on the level of accuracy we need as well as the measuring accuracy of the tools used.
Discrete data isn't measured. It is counted or read; we don't measure shoe sizes, we read them.
State whether each of the following data types is qualitative of quantitative:
State whether each of the following quantitative data types is discrete or continuous: