Skip to the content

Useful for UGC NET · CSIR NET · ASRB NET · ISS · APPSC

On this page
  1. Welcome
  2. Course Outcomes
  3. Units in this Course
  4. Recommended Textbooks

Welcome

This is the complete study package for Statistical Methods. Each unit builds the toolkit for analysing relationships between variables — fitting curves, measuring correlation, predicting via regression and analysing categorical attributes — with two worked examples per concept.

Pre-requisite: Courses 1 & 2 (Descriptive Statistics & Theory of Probability). Comfort with summation notation, least squares idea and basic algebra is essential.

Course Outcomes

  1. Estimate future values using curve fitting.
  2. Calculate the relationship between bivariate data.
  3. Find relationships in multivariate data.
  4. Forecast data using regression techniques.
  5. Find associations in categorical data through attributes.

Units in this Course

UNIT 1

Curve Fitting

Bivariate data, principle of least squares, fitting straight line, second-degree polynomial, exponential curves and power curve.

UNIT 2

Correlation

Types of correlation, scatter diagram, Karl Pearson's coefficient, Rank correlation (with & without ties), correlation for bivariate frequency distribution.

UNIT 3

Concurrent Deviation, Multiple & Partial Correlation

Coefficient of concurrent deviation, probable error, coefficient of determination, partial & multiple correlation (3 variables), intra-class correlation, correlation ratio.

UNIT 4

Regression

Linear vs non-linear regression, regression lines and coefficients, angle between regression lines, correlation vs regression, explained & unexplained variation.

UNIT 5

Attributes

Class & ultimate frequencies, consistency of data (2 & 3 attributes), independence, association & colligation; Yule's coefficients.

PRACTICAL

Practical Course (9 Experiments)

Fitting line, parabola, exponential, power curve; correlation & regression for grouped/ungrouped data; partial/multiple correlation; Yule's coefficients.

REFERENCE

Official Syllabus

Course outline, textbooks, references and exam blueprint.

Next course in learning order: Mathematical Analysis Foundations