Types of Data

Qualitative Data

• Qualitative data refers to non-numerical information that is typically descriptive in nature.
• It can take the form of words, pictures, objects, symbols, and other observable characteristics.
• Examples might include colours, tastes, textures, smells, and sounds.
• In a statistical context, it often involves classifying or categorising individuals or items into groups.
• It's often collected through methods like interviews, focus groups, and direct observation.

Quantitative Data

• Quantitative data is numerical information that can be measured or counted.
• It lends itself well to statistical analysis, as you can perform various mathematical and statistical calculations.
• It's usually presented in the form of numbers, percentages, averages, or other statistical measurements.

Discrete Quantitative Data

• With discrete quantitative data, values can only take specific, separate values.
• This type of data is countable and often includes things like the number of siblings a person has or the number of cars in a parking lot.

Continuous Quantitative Data

• Continuous quantitative data can take on any value within a given range.
• These values often have a logical order or sequence and can be subdivided into ever-smaller units.
• Examples include height, weight, temperature, and time.

Primary Data

• Primary data is data that you collect yourself, specifically for the purpose of your investigation.
• These collection methods can include surveys, interviews, and direct observations.
• This data is often more reliable and relevant to the study at hand, but it can be time-consuming to collect and process.

Secondary Data

• Secondary data is data that was collected by someone else and is already publicly available.
• This could include government records, research studies, newspaper articles, and web content.
• This kind of data can be very useful in saving time and resources, but you need to be careful to ensure it is reliable, accurate, and relevant to your investigation.