The objective of this course is to impart students a holistic view of the fundamentals of experimental designs, analysis tools and techniques, interpretation and applications. Upon completion of this course, the students will know (i) the fundamentals of experiments and its uses, (ii) basic statistics including ANOVA and regression, (iii) experimental designs such as RCBD, BIBD, Latin Square, factorial and fractional factorial designs, (iv) application of statistical models in analysing experimental data, (v) RSM to optimize response of interest from an experiment, and (vi) use of software such as Minitab.
PRE-REQUISITES: Probability and statisticsINDUSTRY SUPPORT :
Manufacturing companies like GM, Tata Motors, Tata Steel
Process industries such as ONGC
Week 1: Introduction to design and analysis of experiments with basic concepts and applicationsWeek 2: Basic statisticsWeek 3: Analysis of Variance (ANOVA)Week 4: RegressionWeek 5: Experimental designs: Randomized complete block design (RCBD)Week 6: Experimental designs: Variants of RCBD such as Latin Square, central composite design, etc.Week 7: Experimental designs: Full factorial experimentsWeek 8: Experimental designs: 2k factorial experimentsWeek 9: Experimental designs: Fractional factorial experimentsWeek 10:Experimental designs: 2k-p factorial experimentsWeek 11:Response surface methodology (RSM)Week 12: Introduction to software MINITAB
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Nagraj Shet is taking this course right now, spending 1 hours a week on it and found the course difficulty to be easy.
To apply statistics that deals with planning, conducting, analyzing, and interpreting controlled tests to evaluate the factors that control the value of a parameter or group of parameters. DOE is a powerful data collection and analysis tool that can be used in a variety of experimental situations.