Collecting Data

Collecting data is the foundation of any statistical analysis. It involves gathering relevant information systematically to answer a specific question or investigate a hypothesis. Accurate data collection ensures reliable results and meaningful conclusions.

Types of Data

• Data can be divided into two main types: qualitative and quantitative.
  • Qualitative data is non-numerical.
  • Example: Somebody's written opinion about the state of the roads.
  • Quantitative data is numerical.
  • Example: The number of different color cars that pass a certain point.

Discrete, Continuous, and Categorical Data

• Quantitative data can be divided into three types:
  • Continuous data:
  • Numerical in nature.
  • Can take an infinite number of values.
  • Example: Heights of trees. This must be a scale with no gaps.
  • Discrete data:
  • Data that can only take certain values.
  • These values are countable.
  • Example: Number of goals scored in a game, height of trees to the nearest meter.
  • Categoric data:
  • Data that describes but the variables are non-numeric.
  • Example: Apples - $12$, Bananas - $6$, Carrots - $4$.