In this lecture we discover four different data types Nominal, Ordinal, Interval and Ratio and their meanings.
Nominal data is the Latin word for Nomen – pertaining to names essentially meaning named categories and is unordered. It is also important that this type of data cannot be average An example would be the section a certain type of food came from whether that be (canned, frozen, produce and dairy).
Ordinal is all about order. With no true numerical value meaning even when numbers are assigned they are used for data analysis. An example of this would be calculating which line is the quickest to get out of the store; these are then broken down into (short lines, medium lines and long lines).
Interval data refers to the amount of time between each given point. This type of data is numeric. It is also important that it doesn’t have a meaningful zero point 0am doesn’t mean the absence of time it just means the start of a new day 12:15 to 12:30pm and 12:30 to 12:45 are both consider interval data with both having equal value.
Ratio data is numeric with a meaningful 0 point. Zero is considered to be the absence of data that is being measured you don’t have anything of that type. Some examples would be age, money, weight and height.
The most important part of the lecture I believe to be “Do data types matter?” Simply the answer is Yes, it is vital that we label our different data types as this could very easily lead to mistakes and wrong calculations through analysis work. Without it you could average out the numbers of postcodes, which could be easily avoided.