Continuous absolute zero value, for example the Fahrenheit

Continuous data is data that can take any value for example time or distance. Unlike continuous data discrete data is numeric data that can take only a limited number of values such as number of people or heart rate. Nominal data (sometimes referred to as discreet data) is data that can be grouped in to categories. It is some times called frequency data because it indicates the number of times a piece of data has come about.

A good example of nominal data is where in the country people live. For example Manchester, Nottingham. Whereas Interval data is measured on a scale that has equal number of units or intervals and is accepted as a physical unit of measurement. But does not have an absolute zero value, for example the Fahrenheit temperature on a thermometer. However Ratio data does have an absolute zero determined by nature. For example height, weight. (Interval and ratio data are a further type of numerical data.

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They are two different classifications of data but due to there many similarities can sometimes be classed as one.) ratio data is measured on a ratio scale similarly to interval data it has equal numbers of units or intervals, It uses zero to represent a missing value and it is impossible to have a negative value. An example of this would be distance covered on the bruce protocol test or VO2 max.

Ordinal data is often referred to as ranking data, gives a numerical value to the order of different variables but doesn’t indicate the actual scores for example ordered scales (never, rarely, sometimes, often, all the time) Variable data is a characteristic of a person, place or thing that can assume more than one value. Constant data however is data that can not change and can only assume one value.

I am now going to give some examples of data and say what type they are and describe the characteristics that it has along with some similarities and differences of other types of data.
Primary data is data that you measured your self. Because of this you know exactly were the results come from and that they are reliable. Secondary data is data that some one else has collected. This is beneficial if you need to find something out like the number of red cards given in one season of football. Because it would be time consuming and you wouldn’t be able to watch every match that was played. However this type of data could be completely unreliable and made up. If it was found on the internet the chances of this increase. Which would mean that the quality of you research wouldn’t be good and the results wouldn’t necessarily be correct.

Validity refers to the meaningfulness of data. For example the multistage fitness test. This test is designed to measure fitness. If it is a valid test the results would be gathered correctly and the fitness of athletes would be correctly assessed. The multi stage fitness test is valid and meaningful for athletes playing a sport such as basketball because it tests there speed and agility. However it is not very valid or meaningful for swimmers because they don’t have to be able to run.