Notes > Foundations of Computing > Statistics and Data
The term "statistics" is associated with the properties or attributes of a whole population. Collecting and processing raw data plays an important part in decision making within business. Raw data is data that has been collected but not organised in any way. The evaluation of past data and looking at the impact of past decisions enables the business to predict future events and make policy decisions accordingly. Of course, these predictions are never 100% accurate but the better the research, the better the prediction.
There are 3 basic methods of data collection:
Data that is collected can be qualitative or quantitative. Qualitative data cannot be measured (i.e. the data is not typically numeric) but can be described and sorted into categories or classes (e.g. hair colour of a certain number of people). Quantitative data is numeric and therefore can be measured (e.g. height).
Quantitative variables can either be discrete or continuous. Discrete data only includes whole positive integers including zero (0,1,2,3 etc...). Continuous data can be of any value between a set of limits (e.g. height, weight).
Primary data is data that has been collected specifically for the purpose it was collected for. Collecting primary data for use in business can be quite expensive due to the effort and resources needed to collect it. The business would have to take into consideration how useful the collecting of that data will be and the actual benefits that will result.
Secondary data is gained from an source that has already collected that data. This is a cheaper method of obtaining data but the data available may not be the exact data required. Some sources of secondary data are the official statistics provided by the government or non-official statisitics provided by other associations such as professional institutes or media organisations.
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