Data Analysis Tools

The work of Matthies et al. [22] collects the current issues, methods, and tools for DSS, and that of Argent et al. [23] describes a DSS generator within which users are able to select and link models, data, analysis tools, and reporting tools to create specific DSS for particular problems, and for which new models and tools can be created and, through software reflection (introspection), discovered to provide expanded capability where required. This system offers a new approach within which environmental systems can be described in the form of specific DSS at a scale and level of complexity suited to the problems and needs of decision makers. 

There are two ways in which data can be analyzed using the MARS system. The first is through use of the general data analysis tools which are part of the standard MARS shell. The second is by means of specialized data analysis programming which can be invoked by the MARS shell. 

TABLE 6.1 Network Building and High-Throughput Data Analysis Tools... 

We have been developing cutting-edge data analysis tools for the pharmaceutical industry for over a decade, with a particular focus in the fields of cheminformatics and bioinformatics. We now describe how our insights apply to these areas. 

Several statistical, quality management, and optimization data analysis tools, aimed at exploring records of measurements and uncover useful information from them, have been available for some time. However, all of them require from the user a signifieant number of assumptions and a priori decisions, which determine in a very strict manner the validity of the final results obtained. Furthermore, these classical tools are guided... 

Partial least squares (PLS) projections to latent structures [40] is a multivariate data analysis tool that has gained much attention during past decade, especially after introduction of the 3D-QSAR method CoMFA [41]. PLS is a projection technique that uses latent variables (linear combinations of the original variables) to construct multidimensional projections while focusing on explaining as much as possible of the information in the dependent variable (in this case intestinal absorption) and not among the descriptors used to describe the compounds under investigation (the independent variables). PLS differs from MLR in a number of ways (apart from point 1 in Section 16.5.1) ... 

Biochips produce huge data sets. Data collected from microarray experiments are random snapshots with errors, inherently noisy and incomplete. Extracting meaningful information from thousands of data points by means of bioinformatics and statistical analysis is sophisticated and calls for collaboration among researchers from different disciplines. An increasing number of image and data analysis tools, in part freely accessible ( ) to academic researchers and non-profit institutions, is available in the web. Some examples are found in Tables 3 and 4. 

This chapter introduced application of simple variographic experiments as a basis for problem-dependent deliberations as to an optimal deployment of increment/sample sampling rate, r, and/or compositing using Q increments/sample. The variographic experiment constitutes the most powerful process sampling data analysis tool available. 

Progressive companies use a more structured and comprehensive team approach to identify root causes. Scientific principles and concepts are applied to determine root causes and make recommendations to prevent recurrence. Effective investigations should use tested data analysis tools and methodologies to seek the identification of multiple causes. To be repeatable, the investigation should use a systematic approach, which may also be prescriptive. As a rule, the benefits of this systematic approach result from two actions ... 

Stratification This technique is used to separate data into groups based on categories or characteristics. It is the basis for the application of other tools or it can be used with other data analysis tools such as scatter diagrams. 

Finally, the Add Ins. .. of the Data Analysis Tools gives the three methods (paired, means with equal variance, and means with unequal variance) as menu-driven options (see spreadsheet 2,4), Access Data Analysis. . . from the Tools menu (if it is not there, the Analysis ToolPak needs to be installed via the Add-Ins. . . menu, also found in the Tools menu). 

In Excel, there are three options for ANOVA one factor, two factor without replication, and two factor with replication. The different options in the Data Analysis Tools menu are shown in spreadsheet 2,6,... 

Spreadsheet 2.4. (a) The Add-In menu, (b) The Data Analysis Tools menu showing the three t test options, (cj Menu for the t test assuming equal variances. 

Independent experimental variables, such as elemental components and process conditions, are often constrained by economic, safety, or physical limits. Incorporating these constraints into the library design can significantly reduce the number of samples to be screened, and in the case of safety are essential. Such constraints are ideally suited to be incorporated into software library design tools and data analysis tools so that sufficiently unattractive experiments can be given lower priority than more attractive experiments. 

LINEST is a function that is included in almost every spreadsheet software, including Microsoft Excel, OpenOffice.org Calc, and Google Docs Spreadsheet. LINEST accepts a table of values for a dependent variable (experimental activity) and any number of independent variables (such as parameters for use in a Hansch equation). LINEST then outputs the best-fit coefficients for the independent variables and certain statistical parameters for the regression. While Excel s Regression option in the Data Analysis tool is more user friendly, LINEST is much more widely available. 

Merlin (exploratory data analysis tools) Daylight Chemical Information Systems, Inc. 123 http //www.daylight.com/... 

HTS is an integrated process, where a large amount of input samples are distilled into a few valuable ones through the use of appropriate biological (the assays), mechanical (the robots), and statistical (data analysis) tools. The desired outcome of HTS is usually a molecule endowed with a desired bioactivity whose structure could not be predicted a priori. The success of... 

The one thing at which Excel does not excel is statistical analysis. The (very basic) level of material covered in this chapter is about at (if not beyond) the limit of its capabilities. It can be used to generate means, medians, SDs and quartiles, but while the first three are OK, the quartile values generated are somewhat unconventional and will not be pursued further. The mean, median and SD of a data set can be generated by using either worksheet functions or the Data Analysis tool. 

To use the Data Analysis tool, enter the data as above and then proceed through the menus Tools then Data Analysis, then select Descriptive Statistics. In the box labelled Input Range , enter A2 B11 and tick the box for Summary statistics . The mean, median and standard deviation will be shown for both data sets, but you will probably need to widen the columns to make the output clear. 

However, computers are quicker (and more reliable). Excel does not offer the SEM as a standard worksheet function, but it is included in the output from the Data Analysis tool (see Chapter 2). Both Minitab and SPSS include it in their Descriptive Statistics routines. 

With most packages you will simply enter the data into a column, call up the appropriate routine and identify the column containing the data. You will then be supplied with a point estimate for the mean and the upper and lower limits of the confidence interval. Good old Excel and its Data Analysis tool half does the job it provides a figure that needs to be added to/subtracted from the mean to obtain the limits of the interval. 

Histograms are commonly and effectively used for final data presentation, but as working data analysis tools they suffer from several limitations. In one direction, their appearance is fairly sensitive to the data grouping done to make them, and it is usually not possible to recover from a histogram the exact data values used to produce it, should one wish to try other groupings. In another direction, histograms are somewhat unwieldy,... 

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