Linear Correlation
Gujarat Board · Class 12 · Statistics
Quick revision notes for Linear Correlation — Gujarat Board Class 12 Statistics. Key concepts, formulas, and definitions for last-minute revision.
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Key Topics to Revise
Core Concepts and Definitions
- Correlation measures the simultaneous change in two variables due to a direct or indirect cause-effect relationship.
- Linear correlation means the points of ordered pairs lie on or very near to a straight line — i.e., changes in two variables are nearly in constant proportion.
- Positive Correlation: both variables move in the SAME direction (e.g., price and supply).
Scatter Diagram Method
- Scatter Diagram is a graph where values of variable X are plotted on the X-axis and values of variable Y on the Y-axis.
- Each ordered pair (xᵢ, yᵢ) is represented as a point on the graph.
- The PATTERN of points tells us about the nature and approximate strength of correlation.
Karl Pearson's Product Moment Method
- Karl Pearson's r is the most widely used and most efficient method for measuring linear correlation.
- It uses all actual observations, not ranks.
- Based on two assumptions: (1) Linear relationship between X and Y, (2) Cause-effect relationship exists between X and Y.
Properties of Correlation Coefficient – Detailed Study
- Property 1 (Range): -1 ≤ r ≤ 1. This is the most fundamental property.
- Property 2 (Unit-free): r has NO unit of measurement regardless of the units of X and Y.
- Property 3 (Symmetry): r(X,Y) = r(Y,X). It does not matter which variable is X and which is Y.
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