Statistical Analysis with R

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This is a two day workshop in R which  is a free and open source environment for data analysis and statistical computing.  While R contains many built-in statistical procedures, a powerful feature of R is the facility for users to extend these procedures to suit their own needs.  Excellent graphing capability is another reason R is gaining wide popularity.

  • How to Obtain R
  • Help Tools
  • Importing / Exporting Data
  • Data Management
  • Descriptive and Exploratory Statistics
  • Common Statistical Analyses (t-test, Regression Modeling, ANOVA, etc.)
  • Graphics
  • Creating Functions

Registration

To register for CSCAR Workshops, call the CSCAR front desk at (734) 764-7828 or come to the office in person with cash or check or a UM department shortcode:

OFFICE HOURS

9:00 a.m. – 5:00 p.m., Monday through Friday
Closed 12pm – 1:00 p.m. every Tuesday for staff meeting.
Voice: (734) 764-7828 (4-STAT from a campus phone)
Fax: (734) 647-2440

ADDRESS

Center for Statistical Consultation and Research (CSCAR)
The University of Michigan
3550 Rackham
915 E. Washington St.
Ann Arbor, MI 48109-1070

Generalized Additive Models

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This workshop will introduce participants to generalized additive models (GAM) as a means to extend their efforts beyond the usual glm setting.  In addition, extensions and connections to other models will be noted (e.g. mixed and spatial).  Demonstration will be conducted with R, and the mgcv package in particular.

Please note room change

Statistical Analysis with R

By | | No Comments

This is a two day workshop in R which  is a free and open source environment for data analysis and statistical computing.  While R contains many built-in statistical procedures, a powerful feature of R is the facility for users to extend these procedures to suit their own needs.  Excellent graphing capability is another reason R is gaining wide popularity.

  • How to Obtain R
  • Help Tools
  • Importing / Exporting Data
  • Data Management
  • Descriptive and Exploratory Statistics
  • Common Statistical Analyses (t-test, Regression Modeling, ANOVA, etc.)
  • Graphics
  • Creating Functions

Registration

To register for CSCAR Workshops, call the CSCAR front desk at (734) 764-7828 or come to the office in person with cash or check or a UM department shortcode:

OFFICE HOURS

9:00 a.m. – 5:00 p.m., Monday through Friday
Closed 12pm – 1:00 p.m. every Tuesday for staff meeting.
Voice: (734) 764-7828 (4-STAT from a campus phone)
Fax: (734) 647-2440

ADDRESS

Center for Statistical Consultation and Research (CSCAR)
The University of Michigan
3550 Rackham
915 E. Washington St.
Ann Arbor, MI 48109-1070

Regular Expressions II

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Regular expressions are perfectly suited for people who like puzzles. Regular expressions are a sequence of characters used to define a search pattern. They are commonly used to do “find” and “find and replace” string operations. They are also used to validate strings like phone numbers, passwords, etc. in data entry. Regular expression capabilities can be found in a variety of programming languages and software like ArcGIS, Java, Javascript, Matlab, Perl, PHP, Python, R, Visual Basic, etc. and some text editors. This workshop will cover more advanced topics like captured groups, backreferences and assertions, as well as practical data problems. The workshop will consist of hands-on example problems. Basic understanding of regular expressions is required. You should be able to understand expressions like “\w{3,}-\d{1,2}-\d{4}“ and “des+e?rt”. The tutorials will be conducted using Python. A basic programming background is helpful but not required for this workshop.

Matching with R: Strategies for larger data

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As we move beyond simple propensity score pair matching and into optimal and/or full matching, performance can suffer. This workshop will discuss strategies to improve both runtime of matching algorithms and quality of the matches. Prior experience with R will be assumed, and exposure and matching (of any sort) will be beneficial but not required.

Location Analysis with ArcGIS and Python

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Scope:  Location analysis plays a central role in a variety of situations such as identifying potential breeding areas for mosquitoes, finding the best path for emergency evacuation, demarcating suitable area for a national park, and identifying the hot spots of air-pollution and green-house gas emissions. This workshop will help you develop a solid foundation in location analytics with ArcGIS and Python. We will primarily focus on vector data (points, lines, and polygons) analyses, but will also touch upon situations where raster (remotely sensed observations) and vector data can be combined to get a better handle on a problem.

Pedagogy: The workshop will follow a problem-based learning approach where real life examples play a central role. We will use appropriate moments and opportunities provided by examples to discuss and learn about fundamental concepts in GIS, computational geometry, and spatial statistics. The workshop will also emphasize and help you appreciate systematic trial and error as a central tenet of algorithmic problem solving.

Prerequisites: Interests in location analysis and exposure to GIS.  If you do not have any previous experience with GIS, consider taking Geospatial Analysis with Python, a free workshop offered by CSCAR on November 2, 2016.

This is an introductory workshop. Future workshops will build on this and include intermediary and advanced tools required to solve location related problems in a variety of policy, scientific, and business contexts.

Engaging the Web with R

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Well known for its statistical capabilities, R can also be used for web-scraping, connecting with websites via APIs, html documents and presentations, interactive visualizations, dashboards, and even building entire, possibly interactive, websites.  This talk will provide an overview of web-based use of aàR. Conceptual introductions, package synopses, and small demonstrations will be presented.

Using RStudio

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This talk will serve as an introduction to what RStudio can offer for those that do not use it, as well as a showcase for more advanced use for those who use it only for scripting purposes.

Topics include:

  • Scripting shortcuts
  • Customization
  • Using Projects
  • Document generation
  • Interactive Visualization
  • Addins
  • Package Development
  • Debugging and Profiling
  • Version Control

Note that this is not a hands-on workshop, just a demonstration of what is possible within the RStudio environment. However, attendees are encouraged to bring a laptop to try some things out as we go along, and get assistance afterward.

Ceci n’est pas une %>%: Exploring Your Data with R

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R is an extremely powerful tool for data modeling, visualization, and general programming.  In many practical applications of statistics, the vast majority of time is spent preparing the data for eventual analysis. However, this also where many practitioners who use R often have relatively little training.  In recent years, a variety of packages have become available to make data wrangling, summarizing, generation and other common operations more straightforward, and easier to read for future use (e.g. via piping and clearer syntax).  In addition, some newer visualization packages work these approaches, allowing one to go quite seamlessly from raw data to interactive graphics.  This workshop will introduce participants to a handful of tools that can make their data exploration and analytical flow more streamlined and reproducible.