The students will be introduced to the R programming
language, a programming language that was
specifically developed for analyzing data, and
is today widely used in most organizations that
conduct data analysis. The students will learn how
to explore datasets in R, using basic visualization
tools and summary statistics, how to run different
kinds of regressions and analyses, and how to
perform statistical inference in practice, for example
how to test certain hypotheses regarding the data or
how to compute confidence intervals for quantities
of interest. The students will also learn how to use R
in order to conduct simulations, an extremely useful
tool that can fulfill a wide range of analytical tasks.
Simulation techniques covered will include Monte
Carlo, importance sampling and rejection sampling.
Finally, the students will learn how to estimate the
precision of computed sample statistics using
resampling methods. The course uses a hands-on
approach, with nearly half the work done in the lab.
Outcome: Not Provided
