Information Techniques

Information Techniques are not to be confused with Information Technologies. Information Technology, usually based on computer systems, refers only to the technological component of an Information System.

So what is an Information System?

An Information System is a system comprised of a collection of processes to extract required information for the user or organization.

The extraction processes are either manual or automated, or a combination of both. The automated processes are usually computer based and referred to as Information Technologies.

On the other hand the Information Techniques refer to a collection of methodologies or tools to produce useful information using data from various resources. They involve identifying data sources, designing surveys to gather data systematically, analyzing collected data, and producing inferences for the project or organization. So it is easy to see why Information Techniques predominantly use statistical tools.

Information System = Information Techniques + Information Technologies.

Let us explain this with an example of an Information System - where Information Technologies and Information Techniques have an equally important role to play. Consider the popular Geographical Information Systems.

The geographical information systems are used to integrate, store, edit, analyze, share, and display geographical information. Here some processes are automated - for example, storing and sharing data. This requires the setting up of the Information Technological systems.

on the other hand some processes in geographical information systems use statistical tools to analyze geographical data to produce useful information to users or businesses. For example, average height of hills in a given location. These statistical tools are what we are interested in this website.

Frequently used Statistical Techniques

So what are the frequently used statistical techniques? If you think carefully you will notice that most of the the statistical techniques would either describe a population using samples drawn from that population or provide judgments about the present or future states of the populations using samples. The former group of techniques is called Descriptive Statistics and the latter class of techniques is known as Inferential Statistics.

Descriptive statistics is mainly used to describe populations using random samples of data collected from those populations. It provides a statistical summary of the sample with a view to understand the population that the sample represents. Central Tendency and Dispersion (spread) measures are essential components of the descriptive statistics.

Inferential Statistics goes one step further to draw inferences from the sample, largely using the central tendency and dispersion measures, about the population from which it has been drawn. This extension of our knowledge from a particular random sample to the whole population is called inductive or statistical inference.

Statistical Inference includes parameter estimation and hypothesis testing. It plays an important role in making decisions often with insufficient and uncertain information. Quantification of uncertainty is an essential technique for Business Decision making processes.

We have also included topics on Econometrics and Financial Mathematics. Econometrics topics include linear regression, time-series analysis, and cross-sectional analysis. Financial Mathematics covers a wide range of topics, including stochastic calculus, derivatives, brownian motion, put-call parity, Black-Scholes pricing option, value-at-riskmeasures, and pricing weather derivatives.

An introduction to Business Statistics and Business Intelligence is also provided. More in-depth topics in these disciplines with numerical examples will be added later. Current financial news items are provided in the Finance News page.

What is this website all about?

Here we aim to provide a detailed description of some of the frequently used statistical techniques in Finance, Economics, Business and Industrial sectors. The emphasis is on the detail and completeness, rather than on the coverage.

We hope anyone using statistical techniques in their work would find this site informative and useful. We think this site would be especially helpful for high school students and non quantitative science graduates and PhD scholars.

Statisticians looking for jobs in the fields of Finance, IT, Statistics, and Mathematics can find job vacancy information in the stat/math jobs page. Please post your comments or questions in the blog section (also accessible from the left navigation panel).

We hope to help students with their statistical problems, especially those requiring to use statistical information techniques, such as estimation and hypothesis testing, for the completion of their PhD Theses or Masters degree Projects.

Students can also email their questions to us. We will try to provide as much information as possible to help you. However please note that we cannot guarantee a timely response, or assume any responsibility for any loss you may incur by using this site or our personal assistance service (see our disclaimer).