**THEORY**

*Culture 1*: Algorithm + Theory: the role of theory is to justify or confirm.

*Culture 2*: Theory + Algorithm: From confirmatory to constructive theory, explaining the statistical

*origin*of the algorithm(s)–an explanation of where they came from. Culture 2 views “Algorithms” as the derived product, not the fundamental starting point [this point of view separates statistical science from machine learning].

**PRACTICE **

*Culture 1*: Science + Data: Job of a Statistician is to confirm scientific guesses. Thus, happily play in everyone’s backyard as a confirmatist.

*Culture 2*: Data + Science: Exploratory nonparametric attitude. Plays in the front-yard as the

*key player*in order to guide scientists to ask the “right question”.

**TEACHING **

*Culture 1*: It proceeds in the following sequences: for (i in 1:B) { Teach Algorithm-i; Teach Inference-i; Teach Computation-i } By construction, it requires extensive bookkeeping and memorization of a long list of disconnected algorithms.

*Culture 2*: The pedagogical efforts emphasize the underlying fundamental principles and statistical logic whose

*consequences*are algorithms. This “short-cut” approach substantially accelerates the learning by making it less mechanical and intimidating. Should we continue to conform to the confirmatory culture or It’s time to reform? The choice is ours and the consequences are ours as well.]]>