In the recent statistical literature, the difference between explanatory and predictive statistical models has been emphasized. One of the tenets of this dichotomy is that variable selection methods should be applied only to predictive models. In this paper, we compare the effectiveness of the acquisition strategies implemented by Google and Yahoo for the management of innovations. We argue that this is a predictive situation and thus apply lasso variable selection to a Cox regression model in order to compare the Google and Yahoo results. We show that the predictive approach yields different results than an explanatory approach and thus refutes the conventional wisdom that Google was always superior to Yahoo during the period under consideration.
Matlab, Python and R have all been used successfully in teaching college students fundamentals of mathematics & statistics. In today’s data driven environment, the study of data through big data analytics is very powerful, especially for the purpose of decision making and using data statistically in this data rich environment. MatLab can be used to teach introductory mathematics such as calculus and statistics. Both Python and R can be used to make decisions involving big data. On the one hand, Python is perfect for teaching introductory statistics in a data rich environment. On the other hand, while R is a little more involved, there are many customizable programs that can make somewhat involved decisions in the context of prepackaged, preprogrammed statistical analysis.