I have been busy working on syllabuses for my Spring 2014 courses at NYU, and that's why posting has been more haphazard than usual. I don't think I have said much about my teaching here on the blog, so let me take this opportunity to introduce the classes that I teach.

**Statistics For Management I (link)**

This is an introductory statistics course with a business/management emphasis. Many students take this course as a bridge from undergraduate to graduate schools (MBA, policy school, social sciences, etc.). There are also working people who just need to use statistics in their work. While the curriculum stays close to the usual Stats 101, I use a very different style of teaching. Much more time is spent on conceptual understanding, and interpretation of data than usual; I use a form of "case method" made famous by Harvard Business School (see this post).

I never assign problems such as "what is the confidence interval of...?"; instead, the question will look like "tell me how the decision-maker should interpret the test data, and recommend a course of action. Explain how you arrive at the decision." I also tailor the schedule to emphasize materials that are widely used in practice like linear/logistic regression, which often get short-changed.

You can learn more about the course and sign up **here**.

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**The Art of Data Visualization (link)**

This is a first-ever offering and the first course of this type that I know of. The entire course is dedicated to working and reworking a data visualization project of the student's choice, and it will be run along the lines of a creative writing workshop. If you follow Junk Charts, you know what I'm talking about. It's a course on the *craft* of visualizing data, and visualization *criticism*. I have put the syllabus on Junk Charts (link) for you to look at.

You can sign up for the course here.

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**Business Analytics and Data Visualization using SAS (link)**

This course is part of the M.S. in Integrated Marketing program. Business analytics (aka Big Data) is a rapidly evolving field that is facing a dearth of skilled talent. The students who take this course will find a world of opportunities opening up for them when they graduate. We will introduce the hot trends in business analytics and Big Data as well as teach analytics skills using SAS software (JMP and Enterprise Guide), such as cleaning up data, data mining techniques and graphing. I will emphasize also the interpretation of data analyses (i.e. numbersense) and awareness of data quality issues.

You can learn more about the course and sign up here.

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Please contact me if you'd like to tailor courses for your organization.

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