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Parametric and Non Parametric Test (Generic Elective Course)
This paper is designed to familiarize the students with concept of testing of parametric and Non- Parametric Inference.
Students will be able to:
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Course |
Course Outcomes |
Learning and teaching strategies |
Assessment Strategies |
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Paper Code |
Paper Title |
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GSTT 401 |
Parametric and Non parametric Test |
CO 1: To analyse the behavior between various samples
CO 2: To estimate the parameters of numerical as well as ordinal data
CO 3: To make the inference about population on the basis of sample data
CO 4: To identify the characteristics of samples
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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
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Procedure of testing of hypotheses. Parametric test and non-parametric test: Introduction, concept, advantages and limitations. Comparison between Parametric and Non Parametric Test
Application of chi-square test- goodness of fit, independence of attributes, application of t test- single mean, difference of mean, paired test, application of f-test- difference of two population mean.
ANOVA- one way classification and two way classification. One Sample test- Wald Wolforwitz run test, test for rank correlation coefficient- sign test
Comparisons of two population- median test, mann whitney U test, wilcoxon signed rank test for paired observation
Comparison of several population- median test for several samples, kruskal walli’s test
● Goon, A.M., Gupta, M.K. and Dasgupta, B. Das (1991): An Outline of Statistics,Volume II, The World Press Pvt Ltd, Calcutta
● Gupta, S.C. and Kapoor, V.K.(2000): Fundamentals of Mathematical Statistics, S Chand & Company, New Delhi.
● Mood Alexander M., Graybill Frankline and Boes Duane C.(2207): Introduction to Theory of Statistics, Mc Graw Hill & Company Third Edition
SUGGESTED READINGS
● Rohatgi, V.K.(1967): An Introduction to Probability Theory and Statistics, John Wiley And Sons.
● Casella,G. and Berger, Roger L.: Statistical Inference, Duxbury Thompson Learning , Second Edition.
● Snedecor, G.W. and Cochran, W.G. (1967): Statistical Methods, Iowa State University Press.
● Gibbons, J. Dickinson and Chakraborthy, S.: Nonparametric Statistical Inference, CRC, Fourth Edition.
● Rohatgi, V.K. and Saleh, A.K. Md. Ehsanes (2001): An Introduction to Probability Theory and Statistics, Second Edition, John Wiley andSons.
e-RESOURCES:
● https://epgp.inflibnet.ac.in/
● https://www.youtube.com/watch?v=z09hret40eI&list=PLyqSpQzTE6M-YZKVfuVSYq...
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
