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Workshop Materials

Materials for the Data Science Services. Statistical software workshops from the Institute For Quantitative Social Science. Introduction to R graphics with ggplot2. Introduction to regression models in R. Introduction to R programming. Python: A Hands-on Introduction. Screen Scraping: A Hands-on Introduction. Mining Twitter Data For Research. Intro to data management in Stata. Intro to statistics and graphics in Stata. Introduction to the Research Computing Environment.

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Materials for the Data Science Services. Statistical software workshops from the Institute For Quantitative Social Science. Introduction to R graphics with ggplot2. Introduction to regression models in R. Introduction to R programming. Python: A Hands-on Introduction. Screen Scraping: A Hands-on Introduction. Mining Twitter Data For Research. Intro to data management in Stata. Intro to statistics and graphics in Stata. Introduction to the Research Computing Environment.
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Workshop Materials | tutorials.iq.harvard.edu Reviews

https://tutorials.iq.harvard.edu

Materials for the Data Science Services. Statistical software workshops from the Institute For Quantitative Social Science. Introduction to R graphics with ggplot2. Introduction to regression models in R. Introduction to R programming. Python: A Hands-on Introduction. Screen Scraping: A Hands-on Introduction. Mining Twitter Data For Research. Intro to data management in Stata. Intro to statistics and graphics in Stata. Introduction to the Research Computing Environment.

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tutorials.iq.harvard.edu tutorials.iq.harvard.edu
1

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.

2

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".

3

Introduction To Programming In R

http://tutorials.iq.harvard.edu/R/RProgramming/Rprogramming.html

Introduction To Programming In R. Workshop overview and materials. This is an intermediate/advanced R course appropriate for those with basic knowledge of R. It is intended for those already comfortable with using R for data analysis who wish to move on to writing their own functions. Prerequisite: basic familiarity with R, such as acquired from an introductory R workshop. This workshop uses the tidyverse. Package which provides more consistent file IO ( readr. Data manipulation ( dplyr. It is common for...

4

Introduction to SAS

http://tutorials.iq.harvard.edu/SAS/SASintro/SASintro.html

11 Documents for Today    labsetup. 15 The SAS Environment. 2 Data Import and Export. 21 Working With SAS Data. 22 Libraries and Datasets. 23 What if my file is not a SAS file? 24 Where is my data? 25 How do I get my data out of SAS? 26 Exercise 1: Importing Data. 31 Means, standard deviations, etc. 33 Correlation and Regression. 34 Exercise 2: Correlation and regression. 4 Variable and Value Labels. 41 Variable and Value Labels. 43 Creating Value Labels. 44 Using Value labels. 46 SAS variable names.

5

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.

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Workshop Materials

Materials for the Data Science Services. Statistical software workshops from the Institute For Quantitative Social Science. Introduction to R graphics with ggplot2. Introduction to regression models in R. Introduction to R programming. Python: A Hands-on Introduction. Screen Scraping: A Hands-on Introduction. Mining Twitter Data For Research. Intro to data management in Stata. Intro to statistics and graphics in Stata. Introduction to the Research Computing Environment.

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