Introduction to Chemical Engineering Processes/MATLAB

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Introduction to MATLAB[edit | edit source]

Inserting and Manipulating Data in MATLAB[edit | edit source]

Importing Data from Excel[edit | edit source]

Performing Operations on Entire Data Sets[edit | edit source]

Graphing Data in MATLAB[edit | edit source]

Polynomial Regressions[edit | edit source]

MATLAB is able to do regressions up to very large polynomial orders, using the "polyfit" function. The syntax for this function is:

polyfit(XDATA, YDATA, Order)

The x data and y data must be in the form of arrays, which for the purposes of this application are simply comma-separated lists separated by brackets. For example, suppose you want to perform the same linear regression that had been performed in the "linear regression" section. The first step is to define the two variables:

>> XDATA = [1.1,1.9,3.0,3.8,5.3];
>> YDATA = [559.5,759.4,898.2,1116.3,1308.7];

Then just call polyfit with order '1' since we want a linear regression.

>> polyfit(XDATA, YDATA, 1)
ans = 1.0e+002 *
  1.77876628209900   3.91232582806103

The way to interpret this answer is that the first number is the slope of the line (1.778*10^2) and the second is the y-intercept (3.912*10^2).

Nonlinear Regressions (fminsearch)[edit | edit source]