CBSE Applied Maths (2026-27) Unit V: Descriptive Statistics Weightage: ~10 Marks in Unit

Chapter 11: Correlation Analysis

Analyze relationships between bivariate variables using scatter plots, Karl Pearson's coefficient (r), and Spearman's rank correlation (ρ).

4 Exercises
CBSE Curriculum Aligned
Interactive Quizzes & Solutions

Chapter Exercises & Topics

Select any exercise to access theory notes, formulas, practice drills, and mini tests.

Exercise 11.1 45 mins

Introduction to Bivariate Data

  • Univariate vs. bivariate distributions
  • Positive, negative, zero, linear, and non-linear correlation
  • Applications in finance, science, and economics
Study Exercise Mini Test
Exercise 11.2 45 mins

Scatter Diagram Method

  • Graphical plotting and visual identification of degree/direction of relationship
  • Perfect positive/negative correlation patterns and zero correlation clusters
Study Exercise Mini Test
Exercise 11.3 45 mins

Karl Pearson’s Coefficient of Correlation

  • Assumptions and mathematical limits (-1 <= r <= +1)
  • Computation via direct formula, assumed mean, and step-deviation methods
  • Properties of r (invariance under change of origin and scale)
Study Exercise Mini Test
Exercise 11.4 45 mins

Spearman’s Rank Correlation Coefficient

  • Formula when ranks are distinct: ρ = 1 - 6∑d^2 / (n(n^2-1))
  • Adjustment formula for repeated/tied ranks using correction factor m(m^2-1)/12
Study Exercise Mini Test

Chapter 11 Core Formula Sheet

Quick-glance formula revision for examination and numerical problem-solving:

  • $$\text{Positive: Both variables increase or decrease together}$$
  • $$\text{Negative: One variable increases while the other decreases}$$
  • $$-1 \le r \le +1$$
  • $$\text{Points on line sloping upwards from left to right } \implies r = +1$$
  • $$\text{Points on line sloping downwards from left to right } \implies r = -1$$
  • $$r = \frac{\sum(x - \bar{x})(y - \bar{y})}{\sqrt{\sum(x - \bar{x})^2 \sum(y - \bar{y})^2}} = \frac{\text{Cov}(X, Y)}{\sigma_x \sigma_y}$$
  • $$r = \frac{N\sum xy - \sum x \sum y}{\sqrt{[N\sum x^2 - (\sum x)^2][N\sum y^2 - (\sum y)^2]}}$$
  • $$\rho = 1 - \frac{6\sum d_i^2}{n(n^2 - 1)} \quad \text{where } d_i = R_x - R_y$$
  • $$\text{Tied Ranks: } \rho = 1 - \frac{6\left[\sum d^2 + \sum \frac{m(m^2-1)}{12}\right]}{n(n^2-1)}$$
Ch 10: Measures of Dispersion and Percentiles All Chapters Syllabus Ch 12: Regression Analysis