Spreadsheet Summary

Spreadsheet Summary In Chapter 2 oi Applications of Microsoft Excel in Analytical Chemistry, we introduce the use of Excel s Analysis ToolPak to compute the mean, standard deviation, and other quantities. In addition, the Descriptive Statistics package finds the standard error of the mean, the median, the range, the maximum and minimum values, and parameters that reflect the symmetry of the data set. 

Spreadsheet Summary In Chapter 2 of Applications of Microsoft Excel in Analytical Chemistiy, we develop a worksheet to calculate the pooled standard deviation of the data from Example 6-2. The Excel function DEVSQO is introduced to find the sum of the squares of the deviations. As extensions of this exercise, you may use the worksheet to solve some of the pooled standard deviation problems at the end of this chapter. You can also expand the worksheet to accommodate more data points within data sets and larger numbers of sets. 

Spreadsheet Summary In Chapter 2 of Applications of Microsoft Excel in Analytical Chemistry, v/e explore the use of the Excel function CONFIDENCEO to obtain confidence intervals when a is known. The 80% and 90% confidence intervals are obtained for one result and for seven results. 

Spreadsheet Summary In the first exercise in Chapter 3 of Applications of Microsoft Excel in Analytical Chemistry, we use Excel to perform the t test for comparing two means assuming equal variances of the two data sets. We first manually calculate the value of t and compare it with the critical value obtained from Excel s function TINV(). We obtain the probability from Excel s TDIST() function. Then, we use Excel s built-in function TTEST() for the same test. Finally, we employ Excel s Analysis ToolPak to automate the t test with equal variances. 

Spreadsheet Summary In Chapter 3 of Applications of Microsoft Excel in Analytical Chemistiy, we use Excel s Analysis ToolPak to perform the paired t text on the data of Example 7-7. We compare the results obtained with those found without pairing. 

Spreadsheet Summary In Chapter 3 of Applications of Microsoft Excel in Analytical Chemistry, the use of Excel to perform ANOVA procedures is described. There are several ways to do ANOVA with Excel. First, the equations from this section are entered manually into a worksheet, and Excel is invoked to do the calculations. Second, the Analysis ToolPak is used to carry out the entire ANOVA procedure automatically. The results of the five analysts from Example 7-9 are analyzed by both these methods. 

Spreadsheet Summary Chapter 4 of Applications of Microsoft Excel in Analytical Chemistry introduces another way to perform a least-squares analysis. The Analysis ToolPak Regression tool has the advantage of producing a complete ANOVA table for the results. A chart of the fit and the residuals can be produced directly from the Regression window. An unknown concentration is found with the calibration curve, and a statistical analysis is used to find the standard deviation of the concentration. 

Spreadsheet Summary In Chapter 4 of Applications of Microsoft Excel in Analytical Chemistiy, a multiple standard additions procedure is illustrated. The determination of strontium in sea water with inductively coupled plasma atomic emission spectrometry is used as an example. The worksheet is prepared, and the standard additions plot is made. The unknown Sr concentration and its standard deviation are obtained. 

Spreadsheet Summary In the first three exercises in Chapter 5 of Applications of Microsoft Excel in Analytical Chemistry, we explore the solution to the types of equations found in chemical equilibria. A general purpose quadratic equation solver is developed and used for equilibrium problems. Then, Excel is used to find iterative solutions by successive approximations. Excel s Solver is next employed to solve quadratic, cubic, and quartic equations of the type encountered in equilibrium calculations. 

Spreadsheet Summary In Chapter 5 of Applications of Microsoft Excel in Analytical Chemistry, we explore the solubility of a salt in the presence of an electrolyte that changes the ionic strength of the solution. The solubility also changes the ionic strength. An iterative solution is first found, in which the solubility is determined by assuming that activity coefficients are unity. The ionic strength is then calculated and used to find the activity coefficients, which in turn are used to obtain a new solubility. The iteration process is continued until the results reach a steady value. Excel s Solver is then used to find the solubility directly from an equation containing all the variables. 

Spreadsheet Summary In the fmst exercise in Chapter 6 of Applications of Microsoft Excel in Analytical Chemistry, we explore the use of Excel s Solver to find the concentrations of Mg, OH, and H3O+ in. the Mg(OH)2 system of Example 11-5. Solver finds the concentrations from the mass-balance expression, the solubility product of Mg(OEl)2, and the ion product of water. Then Excel s built-in tool Goal Seek is used to solve a cubic equation for the same system. The final exercise in Chapter 6 uses Solver to find the solubility of calcium oxalate at a known pH (see Example 11-7) and when the pH is unknown (see Feature 11-1). 

Spreadsheet Summary In some chemical problems, two or more 3 simultaneous equations must be solved to obtain the desired result. Example 12-3 is such a problem. In Chapter 6 of Applications of Microsoft Excel in Analytical Chemistry, the method of determinants and the matrix inversion method are explored for solving such equations. The matrix method is extended to solve a system of 4 equations in 4 unknowns. The matrix method is used to confirm the results of Example 12-3. 

T Spreadsheet Summary In the final three exercises in Chapter 7 of —I Applications of Microsoft Excel in Analytical Chemistry, we first use Excel to plot a simple distribution of species diagram (a plot) for a weak acid. Then, the first and second derivatives of the titration curve are plotted to better determine the titration end point. A combination plot is produced that simultaneously displays the pH versus volume curve and the second-derivative curve. Finally, a Gran plot is explored for locating the end point by a linear regression procedure. 

Spreadsheet Summary In Chapter 8 of Applications of Microsoft Excel in Analytical Cheniistiy, we extend the treatment of neutralization titration curves to polyfunctional acids. Both a stoichiometric approach and a master equation approach are used for the titration of maleic acid with sodium hydroxide. 

Spreadsheet Summary The titration curve for a difunctional base being titrated with a strong acid is developed in Chapter 8 of Applications of Microsoft Excel in Analytical Chemistry. In the example studied, ethylene-diamine is titrated with hydrochloric acid. A master equation approach is explored, and the spreadsheet is used to plot pH versus fraction titrated. 

Spreadsheet Summary The final exercise in Chapter 8 ofApplica% tipns of Microsoft S Excel in Analytical CMmAtry dptisiders the titration of an ainphiprotic species, phenylalanine. A spreadsheet is developed to plot the titration curve of this arninp acid, and the isoelectric pH is calctikited. 

Spreadsheet Summary In the first exercise in Chapter 9 of Applications of Microsoft Excel in Analytical Chemistry, a values for the Cu(II)/NH3 complexes are calculated and used to plot distribution diagrams. The a values for the Cd(II)/Cl system are also calculated. 

Spreadsheet Summary Ligands that protonate are treated in Chapter 9 of Applications of Microsoft Excel in Analytical Chemistry. Alpha... 

Spreadsheet Summary In the second exercise in Chapter 10 of Applications of Microsoft Excel in Analytical Chemistry, cell potentials and equilibrium constants are calculated. A spreadsheet is developed for simple reactions to calculate complete cell potentials and equilibrium constants. The spreadsheet calculates -Engim E ceii. -Eceii.log Kstf ahdl . q. ... 

Spreadsheet Summary in Chapter 10 of Applications of Microsoft Excel in Analytical Chemistry, Excel is used to obtain a values for redox species. These show how the species concentrations change throughout a redox titration. Redox titration curves are developed by both a stoichiometric and a master equation approach. The stoichiometric approach is also used for a system that is pH dependent. 

Spreadsheet Summary In the first experiment in Chapter 11 of Applications of Microsoft Excel in Analytical Chemistry, numerical integration methods are investigated. These methods are used to determine the charge required to electrolyze a reagent in a controlled-potential coulometric determination. A trapezoidal method and a Simpson s rule method are studied. From the charge, Faraday s law is used to determine the amount of analyte. 

Spreadsheet Summary Amperometric titrations are the subject of the final exercise in Chapter 11 of Applications of Microsoft Excel in Analytical Chemistry. An amperometric titration to determine gold in an ore sample is used as an example. Titration curves consisting of two linear segments are extrapolated to find the end point. 

Spreadsheet Summary Polarography is considered in the voltammetry exercise in Chapter 11 o( Applications of Microsoft Excel in Analytical Chemistry. A polarographic calibration curve is constructed first then an accurate determination of half-wave potential is made. Finally, the formation constant and formula of a complex are deteimined from polarographic data. 

Spreadsheet Summary In Chapter 12 of Applications of Microsoft Excel in Analytical Chemistry, spreadsheets are presented for modeling the effects of chemical equilibria and stray light on absorption measurements. Chemical and physical variables may be changed to observe tlieir effects on instrument readouts. 

Spreadsheet Summary In Chapter 12 ot Applications of Microsoft Excel in Analytical Chemistry, we investigate the multiple standard additions method for determining solution concentration. A least-squares analysis of the data leads to the determination of the concentration of the analyte as well as the uncertainty of the measured concentration. 

Spreadsheet Summary In Chapter 13 of Applications of Microsoft Excel in Analytical Chemistry, the first exerci,se explores the properties of first- and second-order reactions. The time behavior of both types of reactions is considered, and linear plotting methods are studied. Conditions needed to obtain pseudo-first-order behavior are also investigated. 

Spreadsheet Summary The second exercise in Chapter 13 of Applications of Microsoft Excel in Analytical Chemistry involves enzyme catalysis. A linear transformation is made so that the Michaelis constant, K, and the maximum velocity, can be determined from a least-squares procedure. The nonlinear regression method is used with Excel s Solver to find these parameters by fitting them into the nonlinear Michaelis-Menten equation. 

S Spreadsheet Summary In the final exercise of Chapter 13 of Appli-"II cations of Microsoft Excel in Analytical Chemistry, the initial-rate method is explored for determining the concentration of an analyte. Initial rates are determined from a linear least-squares analysis and are used to establish a calibration curve and equation. An unknown concentration is determined. 

O Spreadsheet Summary Chapter 15 of Applications of Microsoft si Excel in Analytical Chemistry begins with an exercise treating the resolution of overlapped Gaussian peaks. The overlapped chromatogram, the response, is modeled as the sum of Gaussian curves. Initial estimates are made for the model parameters. Excel calculates the residuals, the difference between the response and the model, and the sum of the squares of the residuals. Excel s Solver is then used to minimize the sum of the squares of the residuals, while displaying the results of each iteration. 

Spreadsheet Summary In Chapter 15 of Applications of Microsoft Excel in Analytical Chemistry, capillary electrophoresis data are used to determine the mobilities of inorganic ions. Measurements of the anival times of ions at the detector are used with the known mobility of Na" to determine mobilities. Capillary electrophoresis results are also used to determine pK values of several weak organic acids. Linear regression analysis is used to find the pK values from measurements of arrival times at different buffer pH values. 

Spreadsheet Summary In the final exercise in Chapter 15 of Applications of Microsoft Excel in Analytical Chemistry, xnict] a.r electroki-netic capillary chromatography is used to determine the critical micelle concentration (CMC) of a surfactant. An equation is developed to relate the retention factor to the CMC. Measured retention times are then used to determine the CMC from a regression analysis. 

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