Data Types

• Quantitative data: Data in numbers
• Strength of Quantitative data: Easy to analyse as data is in numbers
• Strength of Quantitative data: Easy to draw conclusions from
• Weakness of Quantitative data: Oversimplifies reality, as it suggests there are simple answers
• Qualitative data: Data in words or pictures
• Strength of Qualitative data: Represents the complexity of human behaviour
• Strength of Qualitative data: Provides high detail of how people think and behave as they can express their true feelings
• Weakness of Qualitative data: More difficult to draw conclusions and analyse data, as there is a large variety of data collected
• Primary data: Data collected by a researcher for the study being undertaken
• Strength of Primary data: Data collection can be designed so it fits and aims and hypothesis of the study
• Weakness of Primary data: Very lengthy and expensive to recruit participants and design the study
• Secondary data: Data collected for a purpose other than the current one
• Strength of Secondary data: Simpler and cheaper to access data of others
• Strength of Secondary data: Data may have been subjected to statistical testing, and thus it is known whether or not it is significant
• Weakness of Secondary data: The data may not fit the needs of the study
• Nominal data: Data is in separate categories, for example grouping people as tall, medium and short
• Ordinal data: Data is ordered in some way, for example each person lines up in order of size
• Interval data: Data is measured using units of equal intervals, such as measuring everyone's height in centimetres