Correlation

Correlation is a statistical measure that describes the strength and direction of a relationship between two variables.

Types of Correlation:

• Positive Correlation: As one variable increases, the other also increases (e.g., height and weight).
• Negative Correlation: As one variable increases, the other decreases (e.g., speed and travel time).
• No Correlation: No predictable relationship between variables.

Methods to Represent Correlation:

• Scatter graphs with a line of best fit.
• Correlation coefficient (\( r \)) values from -1 to +1:
  • \( r \approx +1\): Strong positive correlation
  • \( r \approx -1\): Strong negative correlation
  • \( r \approx 0\): No correlation

Qualitative Data Handling

Qualitative data refers to non-numeric information describing categories or attributes (e.g., colors, brands, opinions).

It can be classified into:

• Nominal: Categories with no natural order (e.g., blood group, eye color).
• Ordinal: Categories with an order but no fixed difference (e.g., satisfaction: Poor, Fair, Good).

Methods to Handle Qualitative Data:

1. Frequency Table: Lists each category and its frequency (number of occurrences). Useful for summarizing raw data.
2. Bar Chart: Uses rectangular bars with lengths proportional to frequencies. Gaps between bars indicate categories are discrete.
3. Pie Chart: Represents data as sectors of a circle. Each sector’s angle = \( \dfrac{\text{frequency}}{\text{total}} \times 360^\circ \).
4. Pictogram: Uses pictures or symbols to represent frequency. Each symbol represents a fixed number of items.