Statistical Methods and Numerical Analysis

Paper Code: 
STT 202
Credits: 
3
Contact Hours: 
45.00
Max. Marks: 
100.00
Objective: 

This paper aims to familiarize the students with the handling of bivariate data and numerical techniques.

 

Students will be able to:

Course

Learning outcomes (at course level

Learning and teaching strategies

Assessment Strategies

 

Paper Code

Paper Title

STT-202

Statistical Methods

 

CO 20: Demonstrate the knowledge of data reflecting quality characteristics including concepts of independence and association between two attributes.

 

CO 21: Learn how to apply the least square errors method numerically and algebraically to find the curve of best fit.

 

CO 22: Calculate and interpret the correlation between two variables and simple linear regression equation for a set of data.

 

CO 23: Apply simple linear regression model to real life examples.

 

CO 24: Develop the mathematical skills of the students in the areas of numerical methods.

Approach in teaching:

Interactive Lectures,

Group Discussion,

Classroom Assignment

Problem Solving Sessions

 

Learning activities for the students:

Assignments

Seminar

Presentation

Subject based  Activities

 

Classroom Quiz

Assignments

Class Test

Individual Presentation

 

7.00
Unit I: 
Theory of attributes

 Class, class frequencies, order of class frequencies, Ultimate class frequency, Consistency of data (up to order 3). Independence of attributes, contingency table, Association of attributes, Measures of association.

9.00
Unit II: 
Correlation

Correlation, Scatter Diagram, Karl Pearson’s Coefficient of Correlation and its properties. Spearman’s Rank Correlation Coefficient, partial and multiple correlation and their simple questions.

 

9.00
Unit III: 
Curve fitting and Regression

Concept of curve fitting and Principles of Least Squares. Fitting of straight line, Parabola, Power Curves and Exponential Curves. Fitting of Regression Lines, Regression Coefficients with properties.

 

10.00
Unit IV: 
Finite Differences

Operators E, ∇, Δ, their relationship and properties, factorial notation, Difference table and nth order difference of polynomial, Fundamental Theorem of finite differences. Estimation of one and two missing terms.

 

10.00
Unit V: 
Interpolation and Extrapolation

Meaning, uses and assumptions of interpolation and extrapolation. Newton’s Forward and Backward formulae for equal intervals, Lagrange’s formula and numerical problems.

 

Essential Readings: 

●      Goon, A.M., Gupta, M.K. and Dasgupta, B. Das (1991): Fundamentals of Statistics, Volume I, The World Press Pvt Ltd, Calcutta

●      Gupta, S.C. and Kapoor, V.K.: (2000) Fundamentals of Mathematical Statistics, S Chand & Company, New Delhi tenth edition.

             ●       Bansal & Ojha (2015) Numerical Analysis, Jaipur Publishing House, Jaipur

References: 

SUGGESTED READINGS:

 

  • Yule, G. Udny and Kendall, M.G. (1999): An Introduction to the Theory of Statistics,   14th Edition
  • Speigel M.R., (1967): Theory and Problem of Statistics, Schaum’s Series.

 

 

e-RESOURCES:

 

 

JOURNALS:

 

  • Sankhya The Indian Journal of Statistics, Indian Statistical Institute
  • Aligarh Journal of Statistics, Department of Statistics and Operations Research, Aligarh Muslim University
  • Afrika Statistika, Saint-Louis Senega University
  • International Journal of Statistics and Reliability Engineering, Indian Association for Reliability and Statistic
  • Journal of the Indian Society for Probability and Statistics, Indian Society for Probability and Statistics
  • Journal of the Indian Statistical Association, Indian Statistical Association
  • Statistica, Department of Statistical Sciences Paolo Fortunato, University of Bologna
  • Statistics and Applications, Society of Statistics, Computer and Applications
  • Stochastic Modeling and Applications, MUK Publications and Distributions

 

Academic Year: 
2022-2023
  • Printer-friendly version
  • PDF version