9th International Science Congress (ISC-2019).  International E-publication: Publish Projects, Dissertation, Theses, Books, Souvenir, Conference Proceeding with ISBN.  International E-Bulletin: Information/News regarding: Academics and Research

Applications of Modeling and Statistical Regression Techniques in Research

Author Affiliations

  • 1Department of AEM, University of Swaziland, Swaziland, Luyengo M205, SWAZILAND
  • 2Department of AEM, University of Swaziland, Swaziland, Luyengo M205, SWAZILAND

Res. J. Mathematical & Statistical Sci., Volume 1, Issue (6), Pages 1-6, July,12 (2013)


Applied statistics in research have an important role to play in the collection, compilation, analysis and interpretation of the data. In view of the day to day rapid changes in the research spectrum, the scenario is becoming interesting for a researcher. A Model is defined as abstraction of real situations, which aim to give the empirical content to relationships of variable and their interpretation. Modeling techniques are very common in basic as well as multidisciplinary research. This paper discusses the modeling and regression techniques for specific circumstances. Regression analysis technique explains the importance of variables and amount of change in exogenous variables if explanatory variables change with one unit. In this paper also describes the multiple and limited dependent variables especially logistic regression


  1. Smith A., An inquiry in to the nature and causes of the wealth of nation, Edwin Cannan, ed. 1904, Library of Economics andLiberty (www.ecolib.org/library) (1904)
  2. Frees Edward W. and Chow L. Martin, Stochastic life contingencies with solvency considerations, Transaction of the Societyof Actuaries, XLII, 91-148 (1990)
  3. Hald Andres and De Movire, The Doctrine of changes, 1718, 1738, 1756, History of Probability and Statistics and theirApplictions before 1750, Wiley Series in Probability and Statistics, Wiley Inter-science, 397 (1990)
  4. Schneider Lvor and A. De Moivre, The Doctrine of chances (1718, 1738, 1756) in Grattan, Guinness, L., Landmark Writingsin Western Mathematics, 1640-1940, Amsterdam: Elsevier, 105-120 (2005)
  5. Fleckenstein J.O. and Bernouli N.I., Dictionary of Scientific Biography 2, New York: Charles Scribner’s Sons, 56-57 (1980)
  6. Lange O., The scope and Method of Econometric, Review of Economic Studies, 13(1), 19-32 (1994)
  7. Holcombe R., Economic Models and Methodology, Greenwood Press, New York (1989)
  8. Samuelson Paul A., The simple mathematics of income determination, in Metzeler L. loyed., Income, Employment andPublic Policy; easy in honor of Alvin Hansen, New York (1948)
  9. Stephen M. Stigler, The history of statistics, Harvard University Press, Chapter 3 (1986)
  10. James J. Heckman and James M. Synder, Linear probability models of the demand for attributes with an empiricalapplications to estimating the preferences of legislators, National Bureau of Economic Research, WP. No. 5785 (1996)
  11. Itzhak Gilboa, Andrew W. Postlewaite and David Schmeidler, Probability and uncertainty in economic modeling, Journal ofEconomic Perspective, 22(3), 173-188 (2008)
  12. Bergstrand Jeffrey H., The Heckscher-Ohlin-Samuelson Model, the Linder Hypothesis and the Determinants of BilateralIntra-industry Trade, Economic Journal, 100(403), 1216-29 (1990)
  13. Davidson J.E.H., Hendry D.F., Siba F. and Yeo J.S., Economic Journal, 88, 661-692 (1978)
  14. Bennett R.M., Preventive Veterinary Medicine, 13(1), 63-76 (1992)
  15. Ruerd R. and Arjan, R., Technical coefficients for bio-economic farm household: a Meta modeling approach with applicationfor Southern Mali. Ecological Economics, 36(3), 427-441 (2001)
  16. Power B., Rodriguez D. deVoll P., Harris G. and Payero J., Field Crops Research, 124, 171-179 (2011)
  17. Harville D.A., Maximum likelihood approaches to variance component estimation and to related problems, Journal of theAmerican Statistical Association, 72(358), 320-338 (1977)
  18. Emanuelson U., Danell B. and Philipsson J., Estimate of the genetic parameters for clinical mastitis, somatic cell counts, andmilk production estimated by multiple-trait restricted maximum likelihood, Journal of Dairy Science, Elsevier, 71(2), 467-476 (1988)
  19. Lui K.J., Darrow W.W and Rutherford G.W., A model-based estimate of the mean incubation period for AIDS inhomosexual men, 3rd– Science, New York, USA (1988)
  20. Mishra R.N., Srivastava P.K. Singh A.S. and Bhardwaj S.D., A probability model of first conceptive delay and itsapplication, Proc. of 10th annual convention of ISMS (1992)
  21. Singh A.S., Some analytical models for human fertility behavior and its applications Ph. D. Thesis, IMS, BHU, Varanasi,India (1992)
  22. Allison P.D., Missing data: Quantitative applications in the social sciences, British Journal of Mathematical and StatisticalPsychology, 2002 - Wiley Online Library (2002)
  23. Stem N., The economics of climate change: The Stem Review, Cambridge University Press, Cambridge, (2007)
  24. Eboli F., Parrado R. and Roson R., Climate change feedback on economic growth: exploration with a dynamic generalequilibrium model. Paper presented at XIth annual conference on global economic analysis, Helsinki, June. (2008)
  25. Adams P.D., Insurance against catastrophic climate change: how much will an emissions trading scheme cost Australia?, TheAustralian Economic Review, 40(4), 432-452 (2007)
  26. Hyashi F., Econometrics, Princeton University Press (2000)
  27. Russel D. and MacKinnnon J.G., Econometric Theory and Methods, New York: Oxford University Press, (2004)
  28. Wooldridge J., Introductory Econometrics: A modern approach, Thomson South-Western (2003)
  29. Hosmer David W., Lemeshow, Stanley. Applied Logistic Regression (2nd ed.), Wiley (2000)
  30. Cohen Jacob, Cohen Patricia, West Steven G. and Aiken Leona S., Applied Multiple Regression/Correlation Analysis for theBehavioral Sciences (3rd ed.) Routledge, (2002)
  31. Menard Scott W., Applied Logistic Regression (2nd ed.), SAGE (2002)
  32. Singh G., Bhardwaj S.D. and Singh A.S., Fertility analysis by linear regression model, Health and Population-Perspectiveand Issues, 13, 68, (1990)
  33. Mishra R.N, Singh A.S., Mohapatra S. C. and Bhardwaj, S. D., Impact of couple protection rate on birth rate: stochasticlinear regression model, Indian J. Community Medicine, XVII, 55, (1992)
  34. Baade Robert and Dye Rechard F., Studied with help of the regression technique impact of stadiums and professional sportson metropolitan area development, Growth and Change, 21(2), 1-14 (1990)
  35. Connolly C., The use of multiple regression analysis in employment discrimination cases”, Population Research and PolicyReview, 10(2), 117-135 (1991)
  36. Amoako A. Ben, Rashid M. and Stebbins M., Evaluate the differential effect on stock price reaction to the introduction andreduction of capital gains tax exemption, Journal of Banking and Finance, 16(2), 275-287 (1992)
  37. Pilotte E., Growth opportunities and the stock price response to new financing, Journal of Bussiness, 65(3), 371-374 (1992)
  38. Bartov E., Open Market Stock Repurchases as Signals for Earnings and Risk Changes, Journal of Accounting andEconomics, 14(3), 275-294 (1991)
  39. Dayhoff Debra A., High School and College Freshmen Enrollments: The Role of Job Displacement, Quarterly Review ofEconomics and Business, 31(1), 91-103 (1991)
  40. Edwards, Steven F., Evidence of Structural Change in Preferences for Seafood, Marine Resource Economics, 7(3), 141-151(1992)
  41. Kang Han Bin and Reichert Alan K., An Empirical Analysis of Hedonic Regression and Grid Adjustment Techniques in RealEstate Appraisal, American Real Estate and Urban Economics Association Journal, 19(1), 70-91 (1991)
  42. Maki Dennis, Ng Ignace, Effects of Trade Unions on the Earnings Differential between Males and Females: CanadianEvidence, Canadian Journal of Economics, 23(2), 305-311 (1990)
  43. Singh A.S., Impact of bio- demographic factors on fertility: Stochastic regression model, Research Dimension, 2(1), 1-6(2011)
  44. Singh A.S., Factors affecting Infant mortality in India: Statistical interpretation by regression analysis, JP Journal ofBiostatistics, 6(2), 109-120 (2012)