![]() Note the grainy, pixelated appearance (e*.png to save this image. Note the grainy appearance and compare to the PDF version (link for download is below). Plot of pump calibration data as created by the default MATLAB settings. A PNG file of the plot at this stage is shown in Figure 1.įigure 1. The legend is critical when more than one data series is shown don't forget it! The box around the plot area ( set(gca,'box','on')) is helpful in the final report to distinguish between report text and figure text. (4) predicts a linear relationship where the slope is equal to \(A_wS_a\) from which we conclude \(A_w S_a = 4.6 \textrm, 'Location', 'NorthWest') Example: The solid line is a linear best-fit regression of the data error bars were calculated by propagation of error from experimental apparatuses. These highlights could include any regression analyses, the interpretation of the data, and any outliers or unusual data. An additional one or two sentences describing the highlights of the plot.Example: Mass fraction of salt in the permeate stream (\(x_p\)) as a function of transmembrane pressure (\(\Delta P\)). A short phrase to describe what is being plotted.The caption to any figure should be descriptive merely stating "Figure 3. See the Statistics wiki for information on how to calculate error (uncertainty). All experimentally determined values have error and it's critical that you communicate you degree of certainty to the reader through error bars. Experimental measurements are represented as data points (circles, dots, etc) continuous functions such as theoretical predictions or regression analyses are represented as continuous lines. The axes are typically square unless the x-axis represents a significantly wider range than the y-axis ( e.g., DLS data are usually asymmetric with a longer x-axis). The labels should always include units unless the value being plotted is dimensionless or is a qualitative metric. The reader needs to know what data are being shown and the axis labels achieve this. Since the goal of any plot is to communicate the results of some experiment or analysis to the reader, the following items and features are common to nearly all plots: A means to show the relationship between three variables, these plots are rarely used in this lab except in the LPCVD experiment. ![]() Regression analyses, which are combinations of the above two cases.Continuous functions for which you have some method of generating arbitrarily spaced data ( e.g., analytic functions or results from numerical calculations).You'd like to display three or more of quantitative data pairs.The most common plot style, scatter plots are commonly used in the following cases: Your x-axis is best represented as a qualitative category instead of a number.These are typically used in one of the following cases: There are three basic plot types that you'll probably use at some point in CENG 176: Warning! Simply inserting a screen-shot or other low-resolution version of a plot will cost you points! It's too easy to make decent plots for you to skimp on such a critical feature of your report. ![]()
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