M.Com.(ENTREPRENEURSHIP) - University of Madras
M.Com.(ENTREPRENEURSHIP) - University of Madras M.Com.(ENTREPRENEURSHIP) - University of Madras
References: 1 Fisher & Jordan, Security Analysis & Portfolio Management, Prentice Hall of India, 1999.. 2 Elton, Edwin J & Gruber Martin J, Modern Portfolio Theory & Investment Analysis,Wiley & Sons, 1999. 3 Sidney Cottle, Graham & Dodd's Security Analysis, Tata Mcgraw Hill, 1989. 4 J C Francis and S H Arclean, Portfolio Analysis, Prentice Hall of India. 5 Frank J.Fabozzi, “Investment management”, PHI, 1999 6 Robert A.Hangen, “ Modern Investment theory”, PHI,2002 7 V.K.Bhalla. “Investment Management”,sultan Chand, 2000 EDP 622 QUANTITATIVE METHODS FOR BUSINESS ( Credits –3) OBJECTIVE 1. Know the theory of probability and statistical decision theory 2. Learn the sampling techniques 3. Test hypothesis, proportions and means of large sample 4. Know the correlation and regression coefficient and know the bases of multivariate 5. Study the linear programming transportation and assignment Unit – I Theory of probability – probability rules – Baye’s theorem – Probability distribution – Binomial, Poisson and Normal. Statistical decision theory -- Decision environment -- decision making under certainty and uncertainty and risk conditions - EMV, EOL and marginal analysis - value of perfect information - decision tree analysis. Unit – II Sampling-Meaning of random sample - sampling methods - sampling error and standard error - relationship between sample size and standard error Sampling distribution - characteristics- central limit theorem - estimating population parameters -point and interval estimates - estimating proportion, percentage and mean of population from large sample and small sample. Unit – III Testing hypothesis -testing of proportions and means large samples - small samples - one tailed and two tailed tests - testing differences between mean and proportions - errors in hypothesis testing - chi square distribution - characteristics - applications of tests of independence and tests of goodness of fit - inferences - F distribution- testing of population variance- analysis of variance - one way and two way. aaaa 32
Unit – IV Correlation and regression Simple, partial and multiple correlation - simple, partial and multiple regressions - estimation using regression line - standard error of estimate - testing significance of correlation and regression coefficients - interpreting correlation - explained variation and explained variation - coefficient of determination- multivariate analysis - factor, cluster and discriminant analysis. Unit – V Linear programming graphic and simplex models - maximisation and minimization – Transportation – Assignment. Note- The question paper should consist 80% problems and 20% theory questions. References: 1 Richard I.Levin and David S. Rubin, Statistics for Management, Prentice Hall of India, 6th Edn., 1995. 2 S.P.Gupta, Satistical Methods, Sultan Chand, 1990. 3 Sanchetti and Kapoor, Statics, Sultan Chand, 1992. 4 G.C.Beri, “ Statistics for management”, Tata Mc Graw Hill, 2003 5 J.k.Sharma, “ Business Statistics”, Pearson, 2004 6 Anderson Sweeney Williams, “ Statistics for Business and Economics”, Thomson. 2002 7 R.P.Hooda, “ Statistics for Business”, Mc Millan, 2003 aaaa 33
- Page 1 and 2: Appendix - 57(R) UNIVERSITY OF MADR
- Page 3 and 4: THIRD SEMESTER S. NO. COURSE COMPON
- Page 5 and 6: * Project Internal - 50 Marks Exter
- Page 7 and 8: 11. PATTERN OF QUESTION PAPER Part
- Page 9 and 10: Appendix - 57(S) UNIVERSITY OF MADR
- Page 11 and 12: aspects - factors: ambitions, compe
- Page 13 and 14: EDP 607 FINANCING FOR SMALL BUSINES
- Page 15 and 16: SEMESTER - II EDP 602 BUSINESS REGU
- Page 17 and 18: Unit IV Leadership skills and Types
- Page 19 and 20: SEMESTER - III EDP 611 SMALL BUSINE
- Page 21 and 22: Unit - IV The innovation arena and
- Page 23 and 24: SEMESTER - IV EDP 610 RESEARCH METH
- Page 25 and 26: Unit - IV Reports - Accounting Repo
- Page 27 and 28: 3. To study about the techniques fo
- Page 29 and 30: Note: The practical examination wil
- Page 31: 4. Study the portfolio management 5
- Page 35 and 36: 5. Minouti Kamat & R. Krishawathy,
- Page 37 and 38: References : 1. John Egan, “Relat
- Page 39 and 40: Unit - I Total quality management -
- Page 41 and 42: EDP 629 PROJECT APPRAISAL AND MANAG
- Page 43 and 44: Unit - V Financing exports - credit
References:<br />
1 Fisher & Jordan, Security Analysis & Portfolio Management, Prentice Hall <strong>of</strong> India,<br />
1999..<br />
2 Elton, Edwin J & Gruber Martin J, Modern Portfolio Theory & Investment<br />
Analysis,Wiley & Sons, 1999.<br />
3 Sidney Cottle, Graham & Dodd's Security Analysis, Tata Mcgraw Hill, 1989.<br />
4 J C Francis and S H Arclean, Portfolio Analysis, Prentice Hall <strong>of</strong> India.<br />
5 Frank J.Fabozzi, “Investment management”, PHI, 1999<br />
6 Robert A.Hangen, “ Modern Investment theory”, PHI,2002<br />
7 V.K.Bhalla. “Investment Management”,sultan Chand, 2000<br />
EDP 622 QUANTITATIVE METHODS FOR BUSINESS ( Credits –3)<br />
OBJECTIVE<br />
1. Know the theory <strong>of</strong> probability and statistical decision theory<br />
2. Learn the sampling techniques<br />
3. Test hypothesis, proportions and means <strong>of</strong> large sample<br />
4. Know the correlation and regression coefficient and know the bases <strong>of</strong> multivariate<br />
5. Study the linear programming transportation and assignment<br />
Unit – I<br />
Theory <strong>of</strong> probability – probability rules – Baye’s theorem – Probability distribution –<br />
Binomial, Poisson and Normal. Statistical decision theory -- Decision environment -- decision<br />
making under certainty and uncertainty and risk conditions - EMV, EOL and marginal<br />
analysis - value <strong>of</strong> perfect information - decision tree analysis.<br />
Unit – II<br />
Sampling-Meaning <strong>of</strong> random sample - sampling methods - sampling error and<br />
standard error - relationship between sample size and standard error<br />
Sampling distribution - characteristics- central limit theorem - estimating population<br />
parameters -point and interval estimates - estimating proportion, percentage and mean <strong>of</strong><br />
population from large sample and small sample.<br />
Unit – III<br />
Testing hypothesis -testing <strong>of</strong> proportions and means large samples - small samples - one<br />
tailed and two tailed tests - testing differences between mean and proportions - errors in<br />
hypothesis testing - chi square distribution - characteristics - applications <strong>of</strong> tests <strong>of</strong><br />
independence and tests <strong>of</strong> goodness <strong>of</strong> fit - inferences - F distribution- testing <strong>of</strong> population<br />
variance- analysis <strong>of</strong> variance - one way and two way.<br />
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