![]() Worksheet 03f is set up to calculate true strain from engineering strain data collected on a tensile test machine. This section covers three example problems that use these functions. Double-click the vertical axis.Excel features many of the common mathematical functions that you’ll encounter in engineering: logarithms, exponentials, square roots and factorials. To do so, go to the original graph in your worksheet (see Figure 6 or Figure 7). This last expression is the formula for the regression line in Figure 10 - which confirms that the exponential trend curve is actually derived from the regression line.Īnother way to see a logarithmic plot of the data is to use a logarithmic scale on the vertical axis. ![]() If we take the natural log of the right-hand side of this formula, we find that In the preceding section we saw that the exponential trend curve has the formula. Natural Logarithm of Consumer Price Index and Linear Trend Line The result should resemble Figure 10.įigure 10. Select Display R squared value on chart and Display equation on chart. Īfter drawing the graph, click Chart, Add Trendline, Linear.Ĭlick Options. In the table just made, select Columns B and D: Use the Control key and click Columns B and D. (On a Macintosh computer, use the Apple or Command key.) Ĭlick the Chart icon, and draw the graph as you did on. To graph the logarithmic data, follow these steps: The result should look like the table in Figure 9, but extended all the way to the last year in the table.įigure 9. The natural logarithm is then calculated for cells C3, C4, and so on. Move the pointer to the lower right corner, so that a cross appears in place of the black box in the lower right corner of Figure 8. The formula appears at the top of the worksheet, next to the = sign - see the red rectangle in Figure 8.Ĭopy the formula down the page: Click on cell D2. (The = symbol is used for any calculation in Excel.) You should see the result 2.292535, the natural logarithm of 9.9 (the number in cell C2). In cell D1 of your current table, write Ln Annual CPI. Here is the way to calculate natural logarithms of a data column in Excel: ![]() But if we work with logarithms of the CPI, our graph can show details of the entire history. The standard xy-graph does not do justice to the details of change over such a large range. ![]() The CPI rose from 2.3 in 1913 to 179.9 in 2002, a change of two orders of magnitude. Furthermore, it is often more revealing to work with the logarithm of data than the data itself. We can, of course, do that linear regression directly by taking natural logarithms of the y data. In the preceding section we observed that the exponential trend curve is determined by doing a linear regression with data points of the form. ![]()
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