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Statistical Methods
This paper aims to familiarize the students with the handling of bivariate data and numerical techniques.
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Course |
Learning outcomes (at course level |
Learning and teaching strategies |
Assessment Strategies
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Paper Code |
Paper Title |
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STT-202 |
Statistical Methods
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CO 18: Students will demonstrate the knowledge of data reflecting quality characteristics including concepts of independence and association between two attributes.
CO 19: Able to apply the least square errors method numerically and algebraically to find the curve of best fit.
CO 20: Able to calculate and interpret the correlation between two variables and simple linear regression equation for a set of data and know the basic assumptions behind regression analysis.
CO 21: Able to develop the mathematical skills of the students in the areas of numerical methods and apply interpolation methods and finite difference concepts to the numerical data. |
Approach in teaching: Interactive Lectures, Group Discussion, Classroom Assignment Problem Solving Sessions
Learning activities for the students: Assignments Seminar Presentation Subject based Activities
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Classroom Quiz Assignments Class Test Individual Presentation |
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.
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.
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.
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.
Meaning, uses and assumptions of interpolation and extrapolation. Newton’s Forward and Backward formulae for equal intervals, Lagrange’s formula and numerical problems.
- 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.
- 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.
