Lecture Pod 2: Data Types

This weeks lecture pod was about Data Types. There were four data types discussed in this lecture, Nominal, Ordinal, Interval and Ration.

Nominal data (pertaining to names) consists of named categories into which data falls. Nominal data can be counted to calculate percentages but it is not able to take the average of something. An example of Nominal data is at a supermarket were food items are sorted into specific categories ( Dairy, Fresh produce, Packaged and Frozen)

Ordinal data (the order) can also be used to find percentages, however there is still some debate over whether you are able to calculate averages with this type of data. The easiest example of this data is supermarket lines (Short lines, Medium lines and Long lines).

Interval Data (time) is numeric data which is fixed between specific points. It refers to an intervals between each consecutive point of measurement being equal to each other. In this type of data the value of 0 is still a measurement as 0°C is still a temperature as well as 0 seconds is still a measurement of time. The most common example of this is something we use everyday, Time is broken down in 60 seconds a minute.

Ratio data is numeric data that is similar to interval dat except it does have a meaningful zero point. The value of 0 indicates an absence of what is being measured. This can be found in a persons age, weight and height.

Lastly, we looked at Qualitative and Quantitative data. Qualitative data is non numerical descriptive information and quantitative data is numerical information.

The key points to remember from this lecture is that we need to be able to sort data in data types to allows for the correct information to be portrayed. Data types are used to prevent mistakes from happening such as interpreting the data incorrectly. Data types are used to breakdown data into simplifies categories that are easy to understand and relate to for everyday use.