Correlation coefficient and Excel graphing. Synthetic data are given below for a calibration curve in which random

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Correlation coefficient and Excel graphing. Synthetic data are given below for a calibration curve in which random Gaussian noise with a magnitude of 80 was superimposed on y values that follow the equation y = 26.4x + 1.37. This exercise shows that a high value of R2 does not guarantee that data quality is excellent.
(a) Enter concentration in column A and signal in column B of a spreadsheet. Prepare an XY (Scatter) chart of signal versus concentration without a line as described in Section 2 11. Use LINEST (Section 4-7) to find the least-squares parameters including R2.
(b) Now insert the Trend line by following instructions in Section 4-9. In the Options window used to select the Trend line, select Display Equation and Display R-Squared. Verify that Trend line and LINEST give identical results.
(c) Add 95% confidence interval y error bars following the instructions at the end of Section 4-9. The 95% confidence interval is ± tsy, where sy comes from LINEST and Student's t comes from Table 4-2 for 95% confidence and 11 - 2 = 9 degrees of freedom. Also, compute t with the statement "TINV(0.05,9)"
Correlation coefficient and Excel graphing. Synthetic data are given below
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