Index Number and Time Series

Paper Code: 
24DSTT601(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

Course Outcomes

Learning and teaching strategies

Assessment Strategies

Course Code

Course Title

24DSTT601(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: 
2024-2025
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