Research Article

A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models

Volume: 2 Number: 2 October 9, 2017
EN

A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models

Abstract

In this study we have tried to compare the results obtained by Microsoft Excel Solver program with those of NCSS and SPSS in some nonlinear regression models. We fit some nonlinear models to data present in http//itl.nist.gov/div898/strd/nls/nls_main.shtml by the three packages. Although EXCEL did not succeed as well as the other packages, we conclude that Microsoft Excel Solver provides us a cheaper and a more interactive way of studying nonlinear models.

Keywords

References

  1. [1] Bates, D.M., Watts, D.G., Nonlinear Regression Analysis and Its Applications, New York, John Wiley&Sons, (1988).
  2. [2] Bevington,P.R., Robinson,D.K., “Data Reduction and Error Analysis for the Physical Sciences”, McGraw Hill, Third edition, (2003) 148-151.
  3. [3] Billo, E.J., EXCEL for Scientists and Engineers Numerical Methods,Wiley- Interscience, John Wiley&Sons, (2007).
  4. [4] De Levie, R., Advanced Excel for Scientific Data Analysis, Oxford University Press, (2004).
  5. [5] Huet,S., Bouvier,A., Gruet,M., Jolivet,E., Statistical Tools for Nonlinear Regression: A Practical Guide with S-Plus Examples, Springer-Verlag, New York, Springer Series in Statistics, (1996).
  6. [6] Motulsky, H., Christopoulos, A., Fitting Models to Biological Data Using Linear and Nonlinear Regression: A Practical Guide to Curve Fitting, USA, Oxford University Press, (2004).
  7. [7] Neter J., Wasserman W., Kutner M. H., “Applied Linear Statistical Models”, Second edition,Illinois, Richard D. Irwin. (1985). 466-490.
  8. [8] Ross, G.J.S., Nonlinear Estimation, Springer Series in Statistics , Springer-Verlag, (1990).

Details

Primary Language

English

Subjects

Engineering

Journal Section

Research Article

Publication Date

October 9, 2017

Submission Date

September 8, 2017

Acceptance Date

October 2, 2017

Published in Issue

Year 2017 Volume: 2 Number: 2

APA
Tetik Küçükelçi, D., & Evren, A. (2017). A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models. Journal of Engineering Technology and Applied Sciences, 2(2), 91-100. https://doi.org/10.30931/jetas.336853
AMA
1.Tetik Küçükelçi D, Evren A. A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models. JETAS. 2017;2(2):91-100. doi:10.30931/jetas.336853
Chicago
Tetik Küçükelçi, Didem, and Atıf Evren. 2017. “A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models”. Journal of Engineering Technology and Applied Sciences 2 (2): 91-100. https://doi.org/10.30931/jetas.336853.
EndNote
Tetik Küçükelçi D, Evren A (October 1, 2017) A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models. Journal of Engineering Technology and Applied Sciences 2 2 91–100.
IEEE
[1]D. Tetik Küçükelçi and A. Evren, “A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models”, JETAS, vol. 2, no. 2, pp. 91–100, Oct. 2017, doi: 10.30931/jetas.336853.
ISNAD
Tetik Küçükelçi, Didem - Evren, Atıf. “A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models”. Journal of Engineering Technology and Applied Sciences 2/2 (October 1, 2017): 91-100. https://doi.org/10.30931/jetas.336853.
JAMA
1.Tetik Küçükelçi D, Evren A. A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models. JETAS. 2017;2:91–100.
MLA
Tetik Küçükelçi, Didem, and Atıf Evren. “A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models”. Journal of Engineering Technology and Applied Sciences, vol. 2, no. 2, Oct. 2017, pp. 91-100, doi:10.30931/jetas.336853.
Vancouver
1.Didem Tetik Küçükelçi, Atıf Evren. A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models. JETAS. 2017 Oct. 1;2(2):91-100. doi:10.30931/jetas.336853