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tutorials.iq.harvard.edu

Data Management in Stata

http://tutorials.iq.harvard.edu/Stata/StataDatMan/StataDatMan.html

Data Management in Stata. Opening Files in Stata. Generating and replacing variables. Basic Data Manipulation Commands. Exercise 1: Generate, Replace, Recode and Egen. Exercise 1 prototype    prototype. By prefix vs. by options. Bulk Conversion to Missing Values. Converting to and from Strings. Converting Strings to Date/Time. Formatting Numbers as Dates. Exercise 2: Missing Values, String Conversion, and by Processing. Exercise 2 prototype    prototype. Merging, appending, and joining. This is the direc...

tutorials.iq.harvard.edu

Introduction to Stata

http://tutorials.iq.harvard.edu/Stata/StataIntro/StataIntro.html

Materials and setup    labsetup. General Stata command syntax. Commenting and formatting syntax. How to start every do-file. Getting data into Stata. A note about path names. What if my data is not a Stata file? What if my data is from another statistical software program? Exercise 1: Importing data. Exercise 2: Descriptive statistics. Variable and value labels. Exercise 3: Variable labels and value labels. Generating and replacing variables. Exercise 4: Manipulating variables. On the board to your left.

tutorials.iq.harvard.edu

Regression Models in R

http://tutorials.iq.harvard.edu/R/Rstatistics/Rstatistics.html

Regression Models in R. Materials and Setup    labsetup. Launch RStudio    labsetup. Load the states data. Examine the data before fitting models. Plot the data before fitting models. Why is the association between expense and SAT scores negative. The lm class and methods. Exercise 0: least squares regression. Regression with categorical predictors. Setting factor reference groups and contrasts. Exercise 1: interactions and factors. Regression with binary outcomes. Exercise 2: logistic regression. Extrac...

tutorials.iq.harvard.edu

RCE Quick-Start

http://tutorials.iq.harvard.edu/RCEintro/RCEintro.html

What is the RCE? Power at your fingertips. Project folders and shared space. Getting your data on and off the RCE. Launching applications on the interactive nodes. Available RCE powered applications. Using multiple CPUs in interactive jobs. Using multiple CPUs in interactive R programs. Using multiple CUPs in Python. Using multiple CPUs in other programming languages and applications. Preparing for batch submission. Batch example: Simple power simulation in R. Monitoring and manageing submitted batch jobs.

tutorials.iq.harvard.edu

Statistics and graphics in Stata

http://tutorials.iq.harvard.edu/Stata/StataStatGraph/StataStatGraph.html

Statistics and graphics in Stata. Download workshop materials    setup. Fitting models in Stata. Opening Files in Stata. Steps for Running Regression. Univariate Regression: SAT scores and Education Expenditures. Exercise 1: Multiple Regression. Exercise 2: Regression, Categorical Predictors, and Interactions. Exporting and saving results. Saving and exporting regression tables. Axis Titles and Labels. Basic Graphing: Single Categorical Variables. Exercise 1: Histograms Bar Graphs. Lab computer log in:.

tutorials.iq.harvard.edu

Python: A Hands-on Introduction

http://tutorials.iq.harvard.edu/Python/PythonIntro

Python: A Hands-on Introduction. 11 Who am I? 12 What is this page? 212 Wing IDE 101. 22 Further Python Resources. 231 Basic Text Handling. 232 Indexing and Slicing. 233 Including Other Packages. 234 Objects and methods. 272 Writing to CSV. 273 A Note on File Objects. 31 A first example. 311 What the code does. 33 Other helpful regex tools. 41 Example: Egypt Independent / المصري اليوم. 5 Web scraping technology. 52 Running on a schedule. 53 Using an API. 54 Web scraping: selenium. 55 Web scraping: lxml.

tutorials.iq.harvard.edu

Mining Twitter Data For Research

http://tutorials.iq.harvard.edu/Python/twitter

Mining Twitter Data For Research. 11 Who am I? 12 What is this page? 212 Wing IDE 101. 22 Further Python Resources. 231 Basic Text Handling. 232 Indexing and Slicing. 233 Including Other Packages. 234 Objects and methods. 272 Writing to CSV. 273 A Note on File Objects. 3 Aspects of Twitter. 31 Anatomy of a Tweet. 311 This is a tweet. 32 Anatomy of a Twitter User. 33 How Twitter has changed. 342 Limitations of Twitter API. 343 JSON and API searches. 41 Getting Started on Twitter. 414 The "OAuth Dance".

tutorials.iq.harvard.edu

Introduction to R Graphics with

http://tutorials.iq.harvard.edu/R/Rgraphics/Rgraphics.html

Introduction to R Graphics with. Laptop users: You should have R installed –if not:. Everyone: Download workshop materials:. Starting At The End. What Is The Grammar Of Graphics? VS Base for simple graphs. For more complex graphs:. Geometric Objects And Aesthetics. Aesthetic Mapping VS Assignment. Mapping Variables To Other Aesthetics. Setting Statistical Transformation Arguments. Changing The Statistical Transformation. Scales: Controlling Aesthetic Mapping. Using different color scales. In R, type.

tutorials.iq.harvard.edu

Screen Scraping: A Hands-on Introduction

http://tutorials.iq.harvard.edu/Python/scraping

Screen Scraping: A Hands-on Introduction. 11 Who am I? 12 What is this page? 212 Wing IDE 101. 22 Further Python Resources. 231 Basic Text Handling. 232 Indexing and Slicing. 233 Including Other Packages. 234 Objects and methods. 272 Writing to CSV. 273 A Note on File Objects. 31 A first example. 311 What the code does. 33 Other helpful regex tools. 41 Example: Egypt Independent / المصري اليوم. 5 Web scraping in python. 521 Installing a Package. 525 Solutions to exercise. Make python seem less scary.