McGraw MATLAB, R Statistical Computing & LaTeX Workshops!

Are you an undergraduate student? Need help with MATLAB? Scratching your head over plotting in R? Lost in the syntax of LaTeX? Check out the McGraw Center series workshops at the New Media Center, Writing Center, and Rocky/Mathey starting Monday, February 16! Click the titles for information and registration!

MATLAB-Perplexed-EmailMATLAB-Reacquainted-EmailMATLAB for the Perplexed
Monday, February 16
7pm – 9pm, NMC
Click title for description & registration:

Getting Reacquainted with MATLAB
Weds, February 18
7pm – 9pm, NMC
Click title for description & registration.

MATLAB-Work4-Email

Making MATLAB Work for You
Weds, February 25
7pm – 9pm, NMC
Click title for description & registration.


Statistical Programming with R

Series 1:
Part 1: Introduction
Tuesday, February 17
Part 2: Intermediate
Tuesday, February 24

Series 2:
Part 1: Introduction

Monday, February 23
Part 2: Intermediate
Monday, March 2

All sessions 7pm – 9pm 
NMC
Click title for description &
registration.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

LaTeX-All-Email
Introduction to LaTeX

Thursday, February 26, 4:30pm – 5:30pm
The Writing Center, Whitman College
Co-sponsored by the Princeton Writing Program and the McGraw Center for Teaching and Learning.

LaTeX for Beginners and Non-beginners
Tuesday, March 17, 7:00pm – 8:00pmRocky Classroom, Rockefeller College
Co-sponsored by Rockefeller and Mathey Colleges, Princeton Writing Program, and the McGraw Center for Teaching and Learning.

Useful Tools for Your LaTeX Document
Tuesday, March 24, 7:00pm – 8:30pm
New Media Center (NMC), 130 Lewis Library

Co-sponsored by the Princeton Writing Program and the McGraw Center for Teaching and Learning.

Want to check out workshop descriptions and registration links from one location? Check out the PURC (Princeton Undergraduate Research Calendar)!

R programming language: course available 24-7 online!

RData-segment_2bData Analysis and Visualization Using R: an introductory R programming course available online 24-7 through Princeton Coursera to current Princeton University community members around the globe.

Sometimes you need an R programming lesson on a Tuesday at 12:00am, or 1:00pm on a Sunday. What to do? Princeton Quantitative and Computational Biology graduate students David Robinson and Neo Christopher Chung, in association with Princeton Online/Princeton University Coursera, have created a multi-lesson searchable course based on the successful introductory R programming workshops taught by both Robinson and Chung over the past two years for the McGraw Center for Teaching and Learning and the J Street Library and Media Center.

The course is currently only available to current Princeton University members with a NetID, and does not appear on the Princeton University Coursera webpage.  Check out the course using the Princeton link, and login using your NetID and password.

Princeton Peer 2 Peer: Call for Undergraduate Teachers & Learners

UNDERGRADUATES!!

Do YOU have a particular set of skills? Test4-P2Pc

STUDENT GROUPS:
Need to provide hands-on training for your members?
Did you know NMC staff can populate our lab computers with your exercise files?

INDIVIDUALS:
Have an idea for a workshop?
Need a space for training & A/V projection?

SHARE YOUR SKILLS IN:
Graphic Design, Video/Audio Production, 3D Modeling, Programming, Web Development

A BRIEF SELECTION OF NMC Software:
Apple Final Cut Pro, Adobe Illustrator, Adobe Photoshop, Adobe Premiere & After Effects, Adobe InDesign. Adobe Dreamweaver, Blender…and much more!

INTERESTED? QUESTIONS?
Contact Us to Schedule a Workshop or Training!
newmedia@princeton.edu  
609-258-6009

The New Media Center (NMC), a McGraw Center for Teaching and Learning Lab, has projection, A/V support, a 26 seat media lab, and an audio room for your use. Our lab and audio room are available for all undergraduates regardless of academic concentration, and for projects academic, creative, and personal. We are open 1:00pm – 11:00pm 7 days per week during the academic year, with student and professional staff available to assist you.

MATLAB Introductory Workshop, 10/15, 7pm – 9pm

“MATLAB® is a high-level language and interactive environment for numericalMatlab_Logo computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications.”  – MathWorks

 

 

Workshop Description
This workshop provides an introduction to MATLAB® interface. The workshop is intended for students with no programming experience, and is designed to assist students to learn basics of programming with MATLAB. The MATLAB interface, variables, arrays, conditional statements, loops, and plots are among the topics that will be explained. At the end of the workshop, students should be able to use MATLAB for their course work, and be ready to advance their programming skills on their own.

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Statistical Programming with R Workshop Series (Two Sessions!)

R is the de facto standard for statistical analysis in a wide range of disciplines such as 450985571v3computational biology, finance, sociology, political science and digital humanities. This two-part workshop will help participants to get started with R’s abilities, ranging from data structure to visualization. Designed for students without any programming experience, this course will better prepare you for introductory statistics courses and quantitative research at Princeton.

Part 1: Introductory Workshop in Statistical Computing with R
In the first session, you will become familiar with the R programming environment and learn how to work with variables, vectors and data frames. You’ll learn how to import data from a file, to filter it, and to extract summary statistics. You’ll then learn how to use the powerful ggplot2 package to visualize your data, including scatter plots, histograms and boxplots.

Part 2: Intermediate Workshop in Statistical Computing with R
In the second session, you’ll be introduced to R’s tools for statistics and exploratory data analysis. You’ll learn to use R’s built-in statistical functions to test hypotheses about your data, including computing correlations, comparing two samples, and performing linear regressions. You’ll then learn further methods of manipulating and summarizing data using the dplyr package, and learn the basics of exploratory data analyses.

PLEASE NOTE: The best way to learn R is to attend both sessions. The second session will assume students are familiar with both R data structures and the ggplot2 package. To meet the goals of each session, and out of respect for those who enrolled in both, the Instructor will not be able to review material for students not present for Part 1. If you absolutely must miss the first session, reviewing the material in Lessons 1 and 2 of the online course, and passing the corresponding interactive quizzes, would help acquire the necessary basis for Part 2.

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