Understanding The Different Types of Research Data
In this Hub I will cover some of the basic understandings of research data, specifically targeted towards sports. Each of the sections can also be used for research of all types.
Types of Data
There are two different types of data that we use when we are carrying our research projects. These two different types of data are called Primary and Secondary data collection.
Primary data is data that we collect ourselves during the period of our research e.g. Questionnaires, Observations, Interviews and so on. We then use the data we have collected and noted down to begin the next stage of out research which is the theory making and the understanding of what we are researching.
Primary data is best used for ever evolving research because different factors play roles in things we research and can lead to varying results depending on the factor and how much of a role it plays on the research.
Secondary data is data that has already been collect and we use for reference or to gain knowledge from other peoples experiences e.g. published books, Government publications, Journals and the internet. We then use this data to add to the Primary data that we have collected and use it to combine different people’s opinions and base a theory with evidence to back this point up.
Secondary data is best used to add other existing evidence and proof to the Primary data that we have collected, we are better using Secondary data as reference and to gain the knowledge that we need to begin our own research processes.
Classification of Data
There are multiple classifications of data that we used in our research these include, discrete data, Ordinal data, Continuous data, Nominal data, Interval data and Ratio data.
Discrete data can’t be broken down into smaller data values, e.g. a questionnaire with answer options of “Yes/No?” and “Male/Female?” This type of research is best used for things that are counted in whole numbers like the example showed.
Ordinal data is usually data that can be ranked and put in place depending on the values that each subject has for example a football league table, the team with more points will be placed higher up in the league table.
Continuous data can have and number value with any number of desired decimal places , this data is used in events that require time as major part of how the event works and is ranked e.g. a formula one race can come down to milliseconds between the placing the drivers receive. And example of continuous data is “The driver completed the fastest lap of the race winning by 1m 12.34 seconds”
Nominal data is used to assign categories for identification purposes e.g. “Male = 1 Female = 2” the numbers have no value but identify the difference between the male and female population participating in the research or data evidence.
Interval data is used on an order of scale basis that is equal to intervals between scores e.g. Olympic judging scores 6.0, 6.5, 7.0, 7.5, this data is used if judges are unsure whether to round off the scores higher or lower so have the option to offer up a score in-between the two scores that the performer received.
Ratio data is based on an order scale with proportional equal units of measurement e.g. Rugby scores – scoring 40 points has twice the value of scoring 20 points. This data is also used in things such as blood pressure measurements.
Thank you for taking the time to read the hub! If you have any questions or any tips to add, then please post them in the comment section below and maybe we can all learn something new.
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