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Notes/CA Foundation/Quantitative Aptitude (Maths, LR, Stats)

CA Foundation · Quantitative Aptitude (Maths, LR, Stats)

Correlation and Regression

Chapter 5 · 5 formulas · 4 exam-critical pointers

Core concepts

  1. 01Correlation measures direction and strength of linear relation (−1 to +1).
  2. 02Karl Pearson's coefficient is for quantitative data.
  3. 03Spearman's rank correlation for qualitative / ranked data.
  4. 04Regression: estimating one variable based on another using best-fit line.
  5. 05Two regression lines: Y on X and X on Y; intersect at (x̄, ȳ).

Flowchart summary

Scatter Plot | . . . | . . . . |_____________ X Direction: r > 0 : positive r < 0 : negative r = 0 : no linear relation

Exam-critical pointers

  • ⭐Both regression coefficients have the same sign as r.
  • ⭐Product of regression coefficients ≤ 1 (since |r| ≤ 1).
  • ⭐Probable Error = 0.6745 × (1 − r²)/√n (used for significance check).
  • ⭐Distinguish regression from correlation — regression has cause-effect direction.

Make it click

Formula sheet

  • r = Σ[(x − x̄)(y − ȳ)] / √[Σ(x − x̄)² · Σ(y − ȳ)²]
  • Spearman R = 1 − 6Σd² / [n(n² − 1)]
  • Regression Y on X: byx = r(σy/σx)
  • Regression X on Y: bxy = r(σx/σy)
  • r² = byx · bxy (Coefficient of determination)

More from Quantitative Aptitude (Maths, LR, Stats)

  1. Ch 1Ratio, Proportion, Indices and Logarithms
  2. Ch 2Permutations and Combinations
  3. Ch 3Time Value of Money
  4. Ch 4Measures of Central Tendency & Dispersion
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