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首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >A step-by-step guide to non-linear regression analysis of experimental data using a Microsoft Excel spreadsheet.
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A step-by-step guide to non-linear regression analysis of experimental data using a Microsoft Excel spreadsheet.

机译：使用Microsoft Excel电子表格对实验数据进行非线性回归分析的分步指南。

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摘要

The objective of this present study was to introduce a simple, easily understood method for carrying out non-linear regression analysis based on user input functions. While it is relatively straightforward to fit data with simple functions such as linear or logarithmic functions, fitting data with more complicated non-linear functions is more difficult. Commercial specialist programmes are available that will carry out this analysis, but these programmes are expensive and are not intuitive to learn. An alternative method described here is to use the SOLVER function of the ubiquitous spreadsheet programme Microsoft Excel, which employs an iterative least squares fitting routine to produce the optimal goodness of fit between data and function. The intent of this paper is to lead the reader through an easily understood step-by-step guide to implementing this method, which can be applied to any function in the form y=f(x), and is well suited to fast, reliable analysis of data in all fields of biology.
机译：本研究的目的是介绍一种简单易懂的方法，用于基于用户输入函数进行非线性回归分析。尽管使用简单函数（例如线性或对数函数）拟合数据相对简单，但使用更复杂的非线性函数拟合数据则更加困难。可以使用商业专家程序来执行此分析，但是这些程序很昂贵，而且学习起来也不直观。此处描述的另一种方法是使用无处不在的电子表格程序Microsoft Excel的SOLVER函数，该函数采用迭代最小二乘拟合例程来生成数据与函数之间的最佳拟合优度。本文的目的是引导读者逐步了解实现此方法的逐步指南，该指南可以应用于y = f（x）形式的任何函数，非常适合快速，可靠分析生物学所有领域的数据。

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