There is an analyst in everyone especially those who make wise decisions. Right from how to invest our income smartly to family planning to planning weekend getaways, an analyst will always try to optimise the situation at hand. Statistics is the foundation of Analytics application in the real world. Statistics does not have to be a set of complicated equations but it is something that can change our thinking for better and make us smarter in dealing with real life situations. Yes, Statistics can be simple and very interesting especially to those who love numbers.

Jigsaw Analytics is doing a great job in bridging the gap between academics and the practical world of Analytics where businesses which are fairly complex ask for implementable solutions.
The name of the Statistics module in Jigsaw Courses can actually be changed to ‘Applied Business Statistics’ for a better interpretation of what it has to offer.

While both the fundamental theory of Statistics and its application, is important to know, especially for the enthusiasts, what counts for the most part is what are we are actually doing with the theory.
I remember the topics that interested me the most during my post graduation were Actuarials or Econometrics because they helped me in understanding where the theorems can be actually put to practise in day to day world.

Another perspective of looking at this – Real life business cases are never ideal. In a Masters program, one may learn theoretically the kind of problems that appear while running a regression equation. In Jigsaw courses one will work hands on solving real life business problems and learn to deal with these. For example – In MSc one could learn the causes of multicollinearity, a graphical representation of what happens when two variables are correlated with each other, the ways to rectify multicollinearity from a strictly theoretical perspective. In a business situation you may have to deal with such a problem very often especially in marketing effectiveness studies. It rarely happens that a product will have a single campaign running at a given point in time. To have a high impact on sales, typically multiple campaigns are strategically targeted for maximising return on investment. Such a situation inevitably leads to multicollinearity which in essence may overstate the impact of a particular ad stream. To avoid this we typically have to drop and manipulate different campaigns. We cannot tell the client that if you have spent a million dollars on TV, that it has not shown any results but radio on which one tenth of the budget was spent has been more effective than television because we are unable to capture the impact of Television due to multicollinearity. How will one deal with a situation like this which can take a completely different outlook in practise given the theory?

Essentially the best solution in theory is not always the best solution in practise. What we learn in MSC Statistics is theory. What we learn in Jigsaw Courses is hands on practise.

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