What are the basic tools for Data Interpretation?

Data is typically the result of measurements and can be the basis of graphs, images or observations of a set of variables. It is the lowest level of abstraction from which information and subsequently knowledge are derived. Data is collected by various agencies for different purposes. Once the job of data collection is completed, then it is analyzed through different tools of data interpretation. Initially, data cleaning is required. The collected data may contain some irrelevant information which may not be useful. Such data is removed and kept aside during the process of data cleaning.

The basic tools of data interpretation are as follows:—

Statistical Programs

Statistical programs have got their own typical command languages to allow users to write additional procedures. The data is manipulated by the user to suit his needs by deleting points or by merging files or by selecting points. These programs have command options that let the user input data, select statistical operations and create a variety of plots, reports or summaries. Some of the popular software that aid in data analysis are COTS—commercial-off-shelf software. Two powerhouses, especially in business and the life sciences, are SPSS and SAS. Other very well known programs include Systat, Minitab, and Stata. Public domain programs are also excellent tools for data interpretation. Examples include R and Open Stat. The drawback, as is often the case with open source, is that the user support is normally not as good as that of commercial entities, and exists mainly in the community itself.

Mathematical Software

To perform tasks in subjects such as linear algebra, calculus and different equations, mathematical software is specifically created. This software has got graphing capabilities for visualizing both data and functions and can also behave like a calculator. Similar to statistical programs, mathematical software has a proprietary language that allows the user to extend its performance. The user can also save files in various formats such as images or text. The most popular COTS programs favored by researchers are Mathematic, Maple and Matlab. Popular open source software includes Scilab, Octave, and SciPy. Other forms of mathematical software focus on procedures that stress data analysis and curve fitting.

Spreadsheets

Spreadsheets are tools that save data in the form of rows and columns, or tables. They include regular statistical routines that users can add to languages such as Visual Basic. However, spreadsheets have a limitation in terms of the amount of data they can process and convert. Despite this, spreadsheets are popular because they are relatively easy to learn, and can help the user do quick and simple data analysis. Some examples are Microsoft Excel, Microsoft Works, Quattro Pro, Lotus 1-2-3, Open Spread and Open Office Calc.