|Course Archives Statistical Quality Control & Operations Research Unit|
Course: Statistics for Decision Making I
Time: Currently not offered
| Syllabus |
Syllabus: Introduction: Definition of Statistics, Descriptive and Inferential Statistics, Basic Objectives, Applications to various disciplines with examples, Impact of Computer on data analysis.
Collection of Data: Internal and external data, Primary and secondary Data, Population and sample, Representative sample, Types of data continuous and discrete data, Planning and execution of data collection, errors in the process of data collection.
Descriptive Statistics: Scrutiny, classification and tabulation of univariate data, Graphical representation, Frequency distribution, Histogram, Box Plot, Dot Plot, Pareto Diagram. Descriptive measures central tendency and dispersion. Skewness and Kurtosis of a frequency distribution. Bivariate data, Summarization of bivariate data, Marginal and conditional frequency distribution, Scatter diagram, Linear regression and correlation, Least squares method, Rank correlation, Association of attributes. Multivariate data, multiple linear regression, multiple and partial correlation, Coefficient of multiple determination.
Simulation of Probability models: Random numbers and pseudorandom numbers, Generation of random samples from Uniform, Normal, Bivariate Normal, Exponential, Gamma, Poisson and other distributions.
Sampling Techniques: Random sampling, Bias and its sources, Sampling from finite and infinite populations, Estimates and standard error (sampling with replacement and sampling without replacement), Sampling distribution of sample mean, Stratified random sampling, proportional and optimum allocation, Systematic sampling, Cluster Sampling.
Sampling distribution: Sampling distributions related to standard univariate probability models Binomial, Poisson, Normal, Exponential, Gamma, etc.
For all the topics above: Examples and Exercises with use of software packages like Minitab / JMP/ SPSS/ Statistica/ Systat/excel etc.
1. Probability and Statistics for Engineers (7th Edition, 2005) : By I. Miller, J. Freund and R. A Johnson, Prentice Hall.
2. Statistical Theory with Engineering Application: By A. Hald., Textbook Publishers,2003.
3. Statistical Concepts & Methods : By G.K. Bhattacharyya and R.A. Johnson., Wiley , 1977.
4. Introduction to Linear Regression Analysis : By D.C. Montgomery , E.A.Peck & Vining.G.G, Wiley,2006.
5. Introduction to the Theory of Statistics : By A.M. Mood, F.A. Graybill & D.C. Boes. , Tata McGraw Hill, 1974 (RP 2008).
6. Applied Regression Analysis : By N. R.Draper & H. Smith, Wiley,1981.
7. Basic Statistics: By Dick A. Leabo, C.Frank Smith, R. D. Irwin,1968.
8. Beginning Statistics: By R. Lowell Wine , Winthrop Publishers , 1976.
9. Operations Research An Introduction: By Hamdy A . Taha , Prentice Hall, 1997.
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[Indian Statistical Institute]