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

Didem Tetik Küçükelçi; Atıf Evren

doi:10.30931/jetas.336853

Research Article

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

Year 2017, Volume: 2 Issue: 2, 91 - 100, 09.10.2017

Didem Tetik Küçükelçi Atıf Evren

https://doi.org/10.30931/jetas.336853

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

Non-Linear Regression, SPSS, NCSS

References

[1] Bates, D.M., Watts, D.G., Nonlinear Regression Analysis and Its Applications, New York, John Wiley&Sons, (1988).
[2] Bevington,P.R., Robinson,D.K., “Data Reduction and Error Analysis for the Physical Sciences”, McGraw Hill, Third edition, (2003) 148-151.
[3] Billo, E.J., EXCEL for Scientists and Engineers Numerical Methods,Wiley- Interscience, John Wiley&Sons, (2007).
[4] De Levie, R., Advanced Excel for Scientific Data Analysis, Oxford University Press, (2004).
[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] 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] Neter J., Wasserman W., Kutner M. H., “Applied Linear Statistical Models”, Second edition,Illinois, Richard D. Irwin. (1985). 466-490.
[8] Ross, G.J.S., Nonlinear Estimation, Springer Series in Statistics , Springer-Verlag, (1990).
[9] Seber G.A.F., WILD C.J., “Nonlinear Regression”, USA, John Wiley&Sons., (1989) 91-102.
[10] http//itl.nist.gov/div898/strd/nls/nls_main.shtml

Year 2017, Volume: 2 Issue: 2, 91 - 100, 09.10.2017

Didem Tetik Küçükelçi Atıf Evren

https://doi.org/10.30931/jetas.336853

Abstract

References

[1] Bates, D.M., Watts, D.G., Nonlinear Regression Analysis and Its Applications, New York, John Wiley&Sons, (1988).
[2] Bevington,P.R., Robinson,D.K., “Data Reduction and Error Analysis for the Physical Sciences”, McGraw Hill, Third edition, (2003) 148-151.
[3] Billo, E.J., EXCEL for Scientists and Engineers Numerical Methods,Wiley- Interscience, John Wiley&Sons, (2007).
[4] De Levie, R., Advanced Excel for Scientific Data Analysis, Oxford University Press, (2004).
[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] 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] Neter J., Wasserman W., Kutner M. H., “Applied Linear Statistical Models”, Second edition,Illinois, Richard D. Irwin. (1985). 466-490.
[8] Ross, G.J.S., Nonlinear Estimation, Springer Series in Statistics , Springer-Verlag, (1990).
[9] Seber G.A.F., WILD C.J., “Nonlinear Regression”, USA, John Wiley&Sons., (1989) 91-102.
[10] http//itl.nist.gov/div898/strd/nls/nls_main.shtml

There are 10 citations in total.

Details

Primary Language	English
Subjects	Engineering
Journal Section	Research Article
Authors	Didem Tetik Küçükelçi Atıf Evren
Publication Date	October 9, 2017
Published in Issue	Year 2017 Volume: 2 Issue: 2

Cite

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	Tetik Küçükelçi D, Evren A. A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models. JETAS. October 2017;2(2):91-100. doi:10.30931/jetas.336853
Chicago	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 2, no. 2 (October 2017): 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	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, 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 2017), 91-100. https://doi.org/10.30931/jetas.336853.
JAMA	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, 2017, pp. 91-100, doi:10.30931/jetas.336853.
Vancouver	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.