This course is a survey of advanced features of the python programming language that are relevant to data analysis. This includes exposure to some of the most powerful features of python, such as functional and object-oriented programming. In addition, we will learn how to use inspection to learn about the undocumented features of new modules and data structures.
Have you always wanted to learn a programming language, but not sure how to get started? This workshop teaches the basic grammar of the python programming language, a powerful but easy to use tool for getting more out of your computer. Little to no knowledge of python or programming is assumed. Instructor: Kareem Carr
This hands-on, intermediate course will guide you through a variety of programming functions in the open-source statistical software program, R. It is intended for those already comfortable with using R for data analysis who wish to move on to writing their own functions. To the extent possible this workshop uses real-world examples. Concepts will be introduced as they are needed for a realistic analysis task. In the course of working through a realistic project we will lean about interacting with web services, regular expressions, iteration, functions, control flow and more.
Prerequisite: basic familiarity with R, such as acquired from an introductory R workshop.
Get an introduction to R, the open-source system for statistical computation and graphics. With hands-on exercises, learn how to import and manage datasets, create R objects, install and load R packages, conduct basic statistical analyses, and create common graphical displays. This workshop is appropriate for those with little or no prior experience with R.
This workshop is free for Harvard and MIT affiliates.
This class will provide a hands-on introduction to Stata. You will learn how to navigate Stata’s graphical user interface, create log files, and import data from a variety of software packages. We will also share tips for getting started with Stata including the creation and organization of do-files, examining descriptive statistics, and managing data and value labels. This workshop is designed for individuals who have little or no experience using Stata software.
This introduction to the popular ggplot2 R graphics package will show you how to create a wide variety of graphical displays in R. Topics covered included aesthetic mapping and scales, faceting, and themes. This is an intermediate level workshop appropriate for those already familiar with R. Participants should be familiar with importing and saving data, data types (e.g., numeric, factor, character), and manipulating data.frames in R.
This hands-on, intermediate R course will demonstrate a variety of statistical procedures using the open-source statistical software program, R. Topics covered include multiple regression, multilevel models, and multiple imputation. We expect that users enrolled in this course are already familiar with the statistical processes that we cover and are interested in learning how to run these procedures in R. Prerequisite: Basic familiarity with R, such acquired through an introductory R workshop.
This course is a survey of advanced features of the python programming language that are relevant to data analysis. This includes exposure to some of the most powerful features of python, such as functional and object-oriented programming. In addition, we will learn how to use inspection to learn about the undocumented features of new modules and data structures. Instructor: Kareem Carr