Microsoft® Excel

Discounting can also be performed, of course, using a programmable calculator or a spreadsheet such as Lotus 1-2-3 or Microsoft Excel. 

The text form for parameters uses white space or commas to separate the fields (columns) of the parameter tiles. They can be read by ordinary text editors, w ord processors, etc. In the text form, param eters are easy to m odify but not easy to com pare, stn dy, etc. Many database program s are capable of reading column s of text as a database, h owever. Wh ile spreadsheets are n ot. per se, databases, they can be useful for examining parameter sets. Microsoft Excel, for example, can read the text form of a param eter file and pn t the data in a form easily manipulated as a matrix or a database. The text form of parameters are stored, by default only, in Tart files. 

The dBASEIV (ordBASEIIT) form of th e parameter sets come in ld( /filcs analogous to the Tt,v( files. Th ese dbf files are bin ary files, so yon can t read them directly. They arenot retpiired for the product and are provided only as an option. In most situations where there is no exten sive use of database operation s on parameter sets, the text form is probably more convenient to use. Many spreadsheet programs, including Microsoft Excel, are also capable of reading files. 

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. 

Harris, D. C. Nonlinear Least-Squares Curve Litting with Microsoft Excel Solver, /. Chem. Educ. 1998, 75, 119-121. 

The fractional conversions in terms of both the mass balance and heat balance equations were calculated at effluent temperatures of 300, 325, 350, 375, 400, 425, 450, and 475 K, respectively. A Microsoft Excel Spreadsheet (Example6-ll.xls) was used to calculate the fractional conversions at varying temperature. Table 6-7 gives the results of the spreadsheet calculation and Eigure 6-24 shows profiles of the conversions at varying effluent temperature. The figure shows that die steady state values are (X, T) = (0.02,300), (0.5,362), and (0.95,410). The middle point is unstable and die last point is die most desirable because of die high conversion. 

The Microsoft Excel Spreadsheet (OPTIMUM62.xls) was used to determine T p for varying values of (0.1 < X < 0.99). Table 6-11 gives the results of the spreadsheet calculation, and Figure 6-33 shows the profile of T p against X. Figure 6-33 gives the same profile as Type 1. 

A Microsoft Excel spreadsheet (Example 7-ll.xls) was developed for predicting the jacket temperature required for either heating up or cooling down reactants in a batch reactor. 

A non-linear regression analysis is employed using die Solver in Microsoft Excel spreadsheet to determine die values of and in die following examples. Example 1-5 (Chapter 1) involves the enzymatic reaction in the conversion of urea to ammonia and carbon dioxide and Example 11-1 deals with the interconversion of D-glyceraldehyde 3-Phosphate and dihydroxyacetone phosphate. The Solver (EXAMPLEll-l.xls and EXAMPLEll-3.xls) uses the Michaehs-Menten (MM) formula to compute v i- The residual sums of squares between Vg(,j, and v j is then calculated. Using guessed values of and the Solver uses a search optimization technique to determine MM parameters. The values of and in Example 11-1 are ... 

The charge amount to the reactor is 480 kg. A Microsoft Excel spreadsheet (EXAMPLE12-2.xls) was developed for this example. 

Additionally, solutions to problems are presented in the text and the accompanying CD contains computer programs (Microsoft Excel spreadsheet and software) for solving modeling problems using numerical methods. The CD also contains colored snapshots on computational fluid mixing in a reactor. Additionally, the CD contains the appendices and conversion table software. 

This folder contains three files bnlgener.xls, bnlgener.wql, and referen.txt. The database, bnlgener is an eclectic collection of 1,311 failure rates from 31 references. The database is provided as a spread sheet in the Microsoft Excel 4 format (xls) and in Corel Quatro-Pro format (wql). Tbis information is not provided in ASCII because of format... 

There are various reasons for replacing tabulated values by numerical approximations, chief among them to be able to automate the table look-up to save time and to present aspects that otherwise would go unnoticed. Commercial programs like Microsoft Excel feature many of the important statistical functions the file EXCEL FNC.xls that is provided with this manuscript shows how some functions are applied. The algorithms that are employed are very accurate, but not accessible as such. Eor the applications demonstrated in this work, appropriate approximations are incorporated into the VisualBasic programs that accompany the book. 

A Microsoft Excel (Version 5.0 or higher) spreadsheet template form has been developed which allows the calculation of the complete reaction mass efficiency (RME) according to equation (4.1) and raw material cost (RMC) for any chemical transformation. Lines are numbered and line instructions are embedded in the same manner as a personal income tax form. Green metrics are evaluated to determine the greermess of the experiment in a rigorous quantitative way and to determine the bottom line cost of carrying out the experiment. Formula entries are inserted in appropriate cells to facilitate computation. Any... 

Figure 4.2 Microsoft Excel spreadsheet output of green metrics analysis for the synthesis of diphenyl-methanol using the Crignard methodology.

The amounts of sulfentrazone, SCA (analyzed as DMS), and HMS were quantitated by an external standard calibration method. A computer spreadsheet program (Microsoft Excel) was used for calculation and reporting. 

Concentrations of terbacil and its Metabolites A, B and C are calculated from a calibration curve for each analyte run concurrently with each sample set. The equation of the line based on the peak height of the standard versus nanograms injected is generated by least-squares linear regression analysis performed using Microsoft Excel. 

Famoxadone, IN-JS940, and IN-KZ007 residues are measured in soil (p-g kg ), sediment (p-gkg ), and water (pgL ). Quantification is based on analyte response in calibration standards and sample extract analyses determined as pg mL Calibration standard runs are analyzed before and after every 1 samples in each analytical set. Analyte quantification is based on (1) linear regression analysis of (y-axis) analyte concentration (lagmL Q and (x-axis) analyte peak area response or (2) the average response factor determined from the appropriate calibration standards. The SLOPE and INTERCEPT functions of Microsoft Excel are used to determine slope and intercept. The AVERAGE and STDEV functions of Microsoft Excel are used to determine average response factors and standard deviations. 

Most of the algorithms and formulae discussed in this chapter can be implemented as expressions in computer spreadsheets, and the rest as simple computer programs. Most are also incorporated into the Microsoft Excel spreadsheet program by the Isoplot add-in (Ludwig 1999, in press) as user-available functions and graphical routines (Appendix III). 

Ludwig KR (1999) Using Isoplot/Ex, Version 2.01, A Geochronological Toolkit for Microsoft Excel Berkeley Geochronology Ctr. Spec. Pub. la... 

The objectives in this chapter are two. The first one is to briefly review the essentials of linear regression and to present them in a form that is consistent with our notation and approach followed in subsequent chapters addressing nonlinear regression problems. The second objective is to show that a large number of linear regression problems can now be handled with readily available software such as Microsoft Excel and SigmaPlot . 

Problems that can be described by a multiple linear regression model (i.e., they have a single response variable, 1) can be readily solved by available software. We will demonstrate such problems can be solved by using Microsoft Excel and SigmaPlot . 

Because Microsoft Office is so widely used, it is sometimes necessary for you to import data directly from Microsoft Excel or Microsoft Access. Excel files make for a poor database, however. First, Excel files are almost guaranteed to come from a system that is not compliant with CFR 21 - Part 11. Second, it is often the case that the Excel files were created in such a way that the data are not WYSIWYG ( what you see is what you get ). In other words, each cell in Excel could be entered with a different Excel format, which you would not see until you either reformat an entire column in Excel or try to have some other software like SAS read the contents of the Excel file. For these reasons, it is best not to accept Microsoft Excel data as a data source for clinical trials if at all possible. 

SAS provides several ways to read Microsoft Excel and Access files. We cover many of these import methods here using Microsoft formatted versions of the laboratory normal data used previously in this chapter. The examples here are based on the capabilities found in Base SAS and SAS/ACCESS for PC Files in SAS 9.1. In Microsoft Excel, the lab normal data file might look like the following ... 

Some commonly used SAS tools for importing Microsoft Excel and Microsoft Access data into SAS include the LIBNAME statement, the Import Wizard/PROC IMPORT, the SQL Pass-Through Facility, and SAS Enterprise Guide. 

Program 3.6 Using the LIBNAME Statement to Read Microsoft Excel Data... 

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