Statistics for (non-mathematical) trade analysts

I teach a ‘sum­mer inten­sive’ grad­u­ate course in Trade Research Meth­ods at the Uni­ver­si­ty of Ade­laide. In five days we cov­er every­thing from the role of evi­dence in pub­lic pol­i­cy to how to write a report that your boss will read (and even understand).

Most of my stu­dents have no for­mal train­ing in sta­tis­tics (or eco­nom­ics). At most they’ve been using sta­tis­ti­cal reports for years with­out think­ing about them much. Maybe a bit of cyn­i­cism and cau­tion: at least, I hope so.

But pub­lic pol­i­cy — and espe­cial­ly trade — in the past few decades has become a data-dri­ven study. You must be able to read sta­tis­ti­cal reports with a crit­i­cal eye.

So in the one-day I spend on the tools of infer­en­tial sta­tis­tics I try to give them a non-math­e­mat­i­cal intro­duc­tion to a few con­cepts that will help them to read aca­d­e­m­ic papers on trade.

In prepa­ra­tion for this year’s sum­mer course (mid-Feb­ru­ary), I’ve writ­ten a cou­ple of (short) e‑book chap­ters on Evi­dence in pub­lic pol­i­cy and on Sta­tis­tics. You can down­load the drafts here.

Please take a look. Let me know about the errors or con­fu­sions you find. I’d appre­ci­ate your help.

PS: Please ignore the cov­er image: it’s only a place­hold­er tak­en from my nar­rat­ed “Don Juan” iBook 

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