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Basic Statistics and Probability
This paper is designed to acquaint the students with the fundamental statistical techniques, to understand the role of statistics for analyzing and interpreting data meaningfully.
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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-102 |
Basic Statistics and Probability |
CO 5: Ability to define and use the basic terminology of statistics.
CO 6: Able to classify the data and prepare various diagrams and graph.
CO 7: Good understanding of exploratory and descriptive data analysis.
CO 8: Understand the concept of elementary probability theory and its application.
CO 9: Ability to identify the problem and apply appropriate laws of probability and Bayes theorem.
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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
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Classroom Quiz Assignments Class Test Individual Presentation |
Definition, scope, and limitations of statistics, Concept of statistical population. Types of data- Primary and Secondary data, Univariate and Bivariate data. Census and Sample Survey. Qualitative and Quantitative classification, discrete and continuous classification, Geographical and Chronological classification. Construction of frequency tables, frequency distribution for continuous and discrete data, cumulative frequency distributions (inclusive and exclusive methods.
Graphical presentation of data: Histogram, Frequency Polygon, Frequency curve and Ogives. Univariate Data – Measures of Central Tendency – Definition, different measures of Central Tendency, merits and demerits. Measure of Dispersion- Definition, different measures of Dispersion, merits and demerits. Coefficient of variation. Relative dispersions.
Central moments and Non-central moments and their computation from data. Absolute and Factorial moments. Concept of Quartiles, deciles and percentiles. Measure of Skewness and Kurtosis, Sheppard’s, Correction for moments (without proof)
Set Theory, Power set, De- Morgan Law, Random Experiment, Trial, Events and their types. Classical, Statistical and Axiomatic definition of probability and its properties (simple).Addition theorem of probability and their application.
Multiplication theorems of Probability and their application, Conditional Probability and complete, Independent and pairwise events. Baye’s theorem and its application (simple questions).
1. Goon, A.M., Gupta, M.K. and Dasgupta, B. (1991): Fundamentals of Statistics,
Volume I, The World Press PvtLtd , Calcutta
2. Gupta, S.C. and Kapoor, V.K.: (2000) Fundamentals of Mathematical Statistics, S Chand & Company, New Delhi, tenth edition.
3. Mood Alexander M., Graybill Frankline and Boes Duane C. (2007): Introduction to Theory of Statistics, McGraw Hill & Company Third Edition
1. Gupta, O.P.: Mathematical Statistics, Kedarnath Publication, Meerut
2. Yule, G. Udny and Kendall, M.G. (1999): An Introduction to the theory of Statistics,
14th Edition.
3. Hooda, R.P. (2002): Introduction to Statistics: Macmillan India Ltd. 1st edition.
4. Speigel M.R., (1967): Theory and Problem of Statistics, Schaum’s Series.
5. Meyer, P.L.(1970) : Introductory Probability and Statistical Application, Addision
Wesley.
6. Rohatgi, V.K. and Saleh, A.K. Md. Ehsanes (2009): An Introduction to Probability
Theory and Statistics, Second Edition, John Wiley and Sons.
7. Bhat, B.R (1981): Modern Probability Theory, New Age Publishers, Third edition,
