Fitting a polynomial to data
[DOC File]New Chapter 3
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Find the best-fitting polynomial model to this data and explain why the model you chose is the best model. (Solution We will let the independent variable, x, represent the year, where the value of x is given as the number of years since 1972. (i.e. 0 represents the year 1972). The dependent variable, y, will represent the interest rate.
[DOC File]COMPUTER PROBLEM-SOLVING IN
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In this exercise you will use least-squares curve fitting to develop two equations to model the data given. Using these equations, we will predict the function values for two inputs and evaluate the prediction made by each of the curves and linear interpolation. Part A. X 5 10 15 20 25 30 35 40 45 50 Y 17 25 31 33 38 37 39 42 44 46 Using the
[DOC File]MatLab POLYFIT function
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Curve fitting is a useful tool for representing a data set in a linear or quadratic fashion. MATLAB has two functions, polyfit and polyval, which can quickly and easily fit a polynimial to a set of data points. A first order polynomial is the linear equation that best fits the data. A polynomial can also be used to fit the data in a quadratic ...
[DOC File]I
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Fitting an nth degree polynomial to a table of (x,y) points. If the number of data points is m, then n must be m-1 or less, and greater than 0. p=polyfit(x,y,n) Fitting to functions other than polynomials is done by rewriting the function in terms of a straight line, for instance by taking the log of both sides, etc. b. Interactive fitting
[DOC File]Mathematics 385
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Fitting linear and exponential functions to data. Fitting polynomial functions to data. An extended analysis of the “box problem” Projects. References. Chapter 5: Integers and polynomials 8. Unit 5.1 – Natural Numbers, Induction, and Recursion. From recursive to explicit descriptions. Mathematical induction. More applications of ...
[DOC File]Polynomial and Interaction Regression Models in R
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We then have the following plot of the data with the fitted regression function: This is the best second-degree polynomial fit to the data, yet it is obviously not an appropriate model, as confirmed by the summary table. We can also run an interaction model (8.29) involving all three of our predictor variables and the same response variable.
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