Sunday, 28 August 2011



In order to go from data to information, to knowledge and to wisdom, we need to reduce the complexity of the data.

Analyzing data from online surveys is probably one of the most interesting aspects of the whole "Online Survey" experience. It is important to understand the "Numbers" before you can claim your research to be successful.

Some of the tools that make data analysis easy are:

1) Frequency analysis.

This gives you an "Overall" insight into the responses for your survey. General questions like:-

  • What is the % of people who responded to my survey are males?
  • What is the average age of people who responded to the survey?

2) Cross tabulation analysis or crosstab.

Crosstabs give you more insights into your data. Crosstabs answer questions like: -

  • What % of males made a purchase within the last 2 months?
  • Are males more satisfied with our products than females?

A Crosstab should never be mistaken for frequency distribution because the latter provides distribution of one variable only. A Cross Table has each cell showing the number of respondents which gives a particular combination of replies.

An example of Cross Tabulation would be a 3 x 2 contingency table. One variable would be age group which has three age ranges: 11-21, 22-30, and 31-up. Another variable would be the choice of Tommy Hilfiger Jeans or Cotton Pants. With a crosstab, it would be easy to for a company to see what the choices of Jeans are for the three age groups. For instance, the table would show that 35% of those aged 12-20 prefer Tommy Hilfiger Jeans, while only 10% of those aged 31-up prefer Cotton Pants. With the information, they can come up with moves which will be beneficial to the success of the business.

Cross Tabulations are popular choices for statistical reporting because they are very easy to understand and they are laid out in a clear format. They can be used with any level of data whether the data is ordinal, nominal, interval or ratio because the Crosstab will treat all of them as if they are nominal data. Crosstab tables provide more detailed insights to a single statistics in a simple way and they solve the problem of empty or sparse cells.

Since Cross Tabulation is widely used in statistics, there many statistical process and terms that are closely associated with it. Most of these processes are methods to test the strengths of Crosstabs which is needed to maintain consistency and come up with accurate data because data being laid out using Crosstabs may come from a wide variety of sources.

Companies find the services of a data warehouse very indispensable. But inside the data warehouse can be found billions of data which most of them are unrelated. Without the aid of tools, these data will not make any sense to the company. These data are not homogenous. They may come from various sources, often from other data suppliers and other warehouses which may be coming from other branches in other geographical locations.

Software applications like relational database monitoring systems have Cross Tabulation functionalities which allow end users to correlate and compare any piece of data. Crosstab analysis engines can examine dozens of table very fast and efficiently and these engines can even create full statistical outputs by very clicks of the mouse or keyboards.

Author : Rinzing

Group OPS 3

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