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Statistical Programming With R and C
This paper aims at teaching the students to solve the statistical problem using computer software and C language.
Students will be able to:
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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-601 |
Statistical Programming with R and C
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CO 73: Make the program in R and C.
CO 74: Apply programming concept to solve the statistical techniques.
CO 75: Generate statistical problems graphically and interpret them.
CO 76: Handle data in tabular form, fitting and generate results from them.
CO 77: Learn the knowledge of statistical software and interpretation from them. Also helps them in further enhancement in their career. |
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 |
Unit I
Overview of C, Basic structures of c programs, sample c program, programming style, exe.a c program, data types, constants and variables, operators and expression, managing input and output operators.
Unit II
Decision making and branching IF, IF ELSE, NESTED IF ELSE, IF ELSE ladder, SWITCH statement, ?: operator, GOTO statement, Decision making and looping: WHILE statement; DO statement, FOR statement, jumps in loops, Arrays: Introduction to arrays, single dimensional array and two dimensional arrays
Unit III
Introduction of R: History, data types, operators, basic structure of R, Functions for reading, writing and loading and interpretation data. Import and export of data Plot a graph: histograms, frequency polygon, pie chart, ogives, scatter diagrams.
Unit IV
Control Structures: IF, IF ELSE,FOR, WHILE. Calculation of measure of central tendency and dispersion, correlation and lines of Regression. Random number generation and sampling procedures. Fitting of Population Distribution
Unit V
Basics of statistical inference in order to understand hypothesis testing and compute p-values and confidence intervals solution of applications of sampling distributions and Analysis of variance.
- Gardener, M (2012) Beginning R: The Statistical Programming Language, Wiley Publications.
- Braun W J, Murdoch D J (2007): A First Course in Statistical Programming with R. Cambridge University Press. New York
- Kanetkar, Yashwant(2016): Let Us C, BPB Publication.
- Balaguruswami, E.(2003): ‘ANSI C’, Tata McGraw Hill Publication.
SUGGESTED READINGS:
- Rakshit, Sandip(2007):R Programming for Beginners
- Cotton, Richard(2016) Learning R: A Step-by-Step Function Guide to Data Analysis
- Wickham, Hadley(2010): Elegant Graphics for Data Analysis (Use R!)
- Deitel and Deitel(2005): How to Programme C, Pearson’s Edition
- Shubhilall(2003): Structured Programming and computer graphics, University book house pvt
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
