Data

Summary

Data in statistics refers to information collected for analysis. It can be categorized into different types based on its characteristics.

• Qualitative Data — data that can only be written in words, not numbers.
  Example: The colors of cars in a car park.
• Quantitative Data — data that can be written in numbers.
  Example: The heights of children.
• Discrete Data — numerical data that cannot be shown in decimals.
  Example: The number of children in a classroom.
• Continuous Data — numerical data that can be shown in decimals.
  Example: The weights of 10 babies.
• Primary Data — data collected from the original source for a specific purpose.
  Example: Surveying students about the school canteen service.
• Secondary Data — data not originally collected for a specific purpose.
  Example: Using national statistics to find the average cost of cars.

Exam Tips

Key Definitions to Remember

• Qualitative Data
• Quantitative Data
• Discrete Data
• Continuous Data
• Primary Data
• Secondary Data

Common Confusions

• Confusing discrete data with continuous data.
• Mixing up primary and secondary data sources.

Typical Exam Questions

• What is qualitative data?
  Data that can only be described in words.
• How do you differentiate between discrete and continuous data?
  Discrete data cannot be decimals, continuous data can.
• What is an example of primary data?
  Surveying students directly for opinions.

What Examiners Usually Test

• Understanding the difference between types of data.
• Ability to categorize data as qualitative or quantitative.
• Knowing how to organize data using frequency tables.