BUEC
333: Statistical Analysis of Economic
Data
Fall 2016
- Classes: Lectures are on Mondays 2.30 to 4.20 in BLU10021 and
Wednesdays 2.30 to 3.20 in C9000. Tutorials start 2nd week of
class.
- Required textbook: “Introduction to
Econometrics” by J. Stock and M. Watson, 3rd
edition, 2014 (updated). ISBN: 9780133486872
- Book webpage includes practice exercises
and data.
- Course webpage: the complete course webpage will be
available on CANVAS at the beginning of the semester.
- Get ready for this class:
This class is challenging in part because it combines
probability & statistical theory with computer-based
data analysis. But, that is also what makes it so
interesting, because for the first time you will be able to test economic
theories and models using real data! Be sure to come to this class
as prepared as you can!
- Theory: our theoretical analysis uses
foundations from probability theory and statistical analysis.
- review the material from your introductory stat
courses;
- read chapters 1 to 3.
- Data analysis: to conduct data analysis, we
will use the statistical software R which is free and can be
installed on any computer.
- install the software R and R studio: follow the
steps 1 to 2 at http://swirlstats.com/students.html
- start using R to conduct data analysis: follow steps 3 to
6 at http://swirlstats.com/students.html
- The following Swirl courses are recommended:
- Beginner: R programming;
- Beginner: Data Analysis;
- Beginner: Open Intro.
- Regression models
- attend the R tutorials during the 1st week of class.
- to help you download the software on your
computer (both R and R studio), and/or get started with
the above online R courses and tutorials.
- R tutorials have been scheduled during the 1st week
of class (Sept. 6-7th) at the same time as the
regular tutorials. Space is limited and sign-up sheets
will be provided early Sept.
Why do we use R software rather than another commercial
software? 3 main reasons:
- R is an open source software, which means that it is freely
available, which means that there is no need to purchase a
license to install it on your personal computer or laptop...
Open source also means that there are many contributors around
the world who write codes and programs to implement many
(sophisticated) econometric and statistical techniques; there is
also a lot of help available online: if you do not know how to
do something, google it and something will come up!
- This also means that when you graduate and start working,
should you need to conduct some data analysis, you will be
able to use R!
- R is becoming more and more popular in economics. If you go to
grad school, it is likely you will use it again.
- We have received very good feedback from former students:
employers seem to value data analysis skills, and they value it
even more when the software you know is free and can be
used at your new job!
R can be a little bit intimidating at the beginning, and it
takes time to become familiar with it, so don't delay looking
into it and practicing.