Index Number and Time Series

Paper Code: 
25DSTT601(A)
Credits: 
4
Contact Hours: 
60.00
Max. Marks: 
100.00
Objective: 

Index Number and Time Series Analysis is to explore the use of index numbers and time series methods for analyzing economic data.

 

Course Outcomes: 

Course

Course Outcomes

Learning and teaching strategies

Assessment Strategies

Course Code

Course Title

25DSTT601(A)

Index Number and Time Series
(Theory)

CO 67: Interpret and use a range of index numbers to understand their importance in the various sectors.

CO 68: Explain tests and error analysis techniques to evaluate the accuracy and reliability of index numbers, and demonstrate the ability to convert fixed-based to chain-based index numbers and vice versa.

CO 69: Evaluate and different components of time series data and apply decomposition techniques to separate them.

CO 70: Apply time series methods for forecasting values of a time series at future time points and also apply them on real world models.

CO 71: Acquire proficiency in applying deseasonalization techniques in time series analysis, and explain the methods for analyzing random components in time series data.

CO 72: Contribute effectively in course-specific interaction.

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.

 

12.00
Unit I: 
Index Numbers-I

Definition, construction of index numbers and problems thereof for weighted and unweighted index numbers including Laspeyre, Paasche, Drobish and Bowley, Edgeworth-Marshall, Fisher, Walsch and Kelly.

 

12.00
Unit II: 
Index Numbers-II

Tests and Errors for Index Numbers, Chain index numbers, conversion of fixed based to chain based index numbers and vice-versa. Consumer price index numbers.

 

12.00
Unit III: 
Time Series

Introduction to times series data, application of time series from various fields. Components of a times series, Decomposition of time series. Trend: Estimation of trend by free hand curve method, method of semi averages, fitting a various mathematical curve, and growth curves.

12.00
Unit IV: 
Measurement of Components of Time Series

Method of moving averages. Detrending. Effect of elimination of trend on other components of the time series. Seasonal Component: Estimation of seasonal component by Method of simple averages.

12.00
Unit V: 
Measurement of Seasonal and Random Component

Ratio to Trend. Ratio to Moving Averages and Link Relative method, Deseasonalization. Random Component: Variate component method. 

 

Essential Readings: 
  • Goon, A.M., Gupta, M.K. and Dasgupta, B. (1991): Fundamentals of Statistics, Volume II, The World Press Pvt Ltd, Calcutta
  • Gupta, S.C. and Kapoor, V.K. (2000): Fundamentals of Applied Statistics, S Chand & Company, New Delhi

 

SUGGESTED READINGS:

  • Croxton, F.E. and Cowden, D.J. (1969): Applied General Statistics, Prentice Hall Of India
  • Srivastava, O.S. (1998): A Textbook of Demography, Vikas Publishing.
  • Shrinivasan, K. and Srinivasan, K. (1998): Basic Demographic Techniques and Applications.
  • Anderson, T.W. (1971): The Statistical Analysis of Time Series, Wiley, N.Y.
  • Montgemory, D.C. and Johnson, L.A. (1977): Forecasting and Time Series Analysis, McGraw Hill.
  • Kendall, Sir Maurice and Ord, J.K. (1990): Time Series (Third Edition), Edward Arnold.
  • Brockwell, P.J. and Davis, R.A. (1991): Time Series: Theory and Methods (Second Edition), Springer- Verlag.
  • Fuller, W.A. (1976): Introduction to Statistical Time Series, John Wiley, N.Y.
  • Granger, C.W.J. and Newbold (1984): Forecasting Econometric Time Series, Third Edition, Academic Press.
  • Priestley, M.B. (1981): Spectral Analysis & Time Series, Griffin, London.
  • Kendall, M.G. and Stuart A. (1966): The Advanced Theory of Statistics, Volume 3, Charles Griffin, London. 

 

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: 
2025-2026
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