Normalization and the CAT exam make strange bedfellows. When CAT comes around every year ‘normalization’  follows but not a pleasant twosome they make.  This year, however normalization will not exactly be  a topic of debate  –  thanks to the fact that the exam is going to be held over two slots only.

What is normalization? According to the CAT 2015 website and generally, Normalization is an established practice for comparing candidate scores across multiple Forms and is similar to those being adopted in other large educational selection tests conducted in India such as Graduate Aptitude Test in Engineering (GATE). For normalization across sections we shall use a sort of percentile equivalence.

The good news is that since there are going to be only two forms (read two exams), the comparison of scores between candidates will be restricted.

Normalization has been an issue ever since CAT went online in 2009 and the exam slots spread over days. From more than a month to under a month, to two days and now a single day with two slots. Reduction in slots means reduction in normalization fears.

PaGaLGuY spoke to a number of CAT coaching people and also past CAT takers and they all agreed that in the event of just two forms, normalization will not create a furore this year.

The only issue of debate among people was the CAT website mentioning that  – The Normalization process to be implemented shall adjust for location and scale differences of score distributions across different forms.

The ‘location’ according to some experts meant either location of the CAT centres (meaning remote areas) or an effort to be fair to the newer IIMs. Thankfully, Prof Tathagat Bandyopadhyay, CAT 2015 CAT Convenor put all fears to rest. He assured that ‘location’ by no remote sense meant geographical location. “What it means is different forms. One will look at the mean, median, mode of the  two exams being held on the same day and then take the average keeping all factors in mind.”

Well, then that kind of settles whatever dust was about to gather. Almost no normalization to worry about.