Graphing with Microsoft Excel

Graphs are critical to understanding quantitative relations. Depending on which version of Excel you have, there may be some variation from what is described here. 

Now you are asked which cells contain the data to be plotted. Identify the x data by writing B5 B12 next to Data Range. Then write a comma and identify the y data by writing C5 C12. The input for Data Range now looks like B5 B12,C5 C12. Click the button to show that data are in columns, not rows. Click Next. 

Now a small graph of your data appears. If it does not look as expected, make sure you selected the correct data, with x before y. The new window asks you for axis labels and an optional title for the graph. For the title, write Density of Water (without quotation marks). For the Jt-axis, enter Temperature (°C) and for the y-axis write Density (g/mL) . Click Next. 

Now you are given the option of drawing the graph on a new sheet or on the same sheet that is already open. For this case, select As object in Sheet 1 . Click Finish and the chart 

Double click on the x-axis and select Patterns. Change the Minor tic mark type from None to Outside. Select Scale and set the maximum to 40, the major unit to 10. the minor unit to 5, and click OK. 

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Figure 2.3 Graph created with Microsoft Excel showing the natural logarithms of the concentrations of DDT in trout from Lake Michigan (see the above table) as a function of time and showing a fitted straight line (using the TrendLine feature). The negative slope of this line is the rate constant.

The property calculation experiment offers a list of 34 molecular properties, including thermodynamic, electrostatic, graph theory, geometric properties, and Lipinski properties. These properties are useful for traditional QSAR activity prediction. Some are computed with MOPAC others are displayed in the browser without units. A table of computed properties can be exported to a Microsoft Excel spreadsheet. 

Virtual instruments such as these are not only useful with respect to modeling and forecasting, but perhaps more importantly, they become a knowledgebase in which interventions and the efficacy of these interventions can be statistically proven. In addition, virtual instruments can employ standard technologies such as Dynamic Data Exchange (DDE), ActiveX, or TCP/IP to transfer data to commonly used software applications such as Microsoft Access or Microsoft Excel . In this way, virtual instruments can measure and graph multiple signals while at the same time send these data to another application which could reside on the network or across the Internet. 

The plot is linear, confirming that the reaction is indeed first order. To obtain the rate constant, fit the data to a line. The slope of the line will be equal to -k. Since the slope of the best fitting line (which is most easily determined on a graphing calculator or with spreadsheet software such as Microsoft Excel) is -2.90 X 10 " s the rate constant is therefore-1-2.90 x 10 " s ... 

Figure 57.3 illustrates a virtual instrument that interactively accesses institutional and department specific indicators and profiles them for comparison. Data sets can be acquired directly from standard spreadsheet and database applications (i.e., Microsoft Access , Excel , Sybase , Oracle , etc.). This capability has proven to be quite valuable with respect to quickly accessing and viewing large sets of data. Typically, multiple data sets contained within a spreadsheet or database had to be selected and then a new chart of these data had to be created. Using PIVIT, the user simply selects the desired parameter from any one of the pull-down menus and this data set is instantly graphed and compared to any other data set. 

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