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Managing Data with R - Eastern Time (TRA-26)

Revolution Analytics, Inc.

Friday, June 21, 2013 from 10:00 AM to 2:00 PM (PDT)

Managing Data with R - Eastern Time (TRA-26)

Registration Information

Registration Type Sales End Price Fee Quantity
General Admission Ended $400.00 $9.95
Academic Admission Ended $300.00 $8.49
Student Admission Ended $200.00 $5.99

Share Managing Data with R - Eastern Time (TRA-26)

Event Details

This is a 1-day virtual course offered on June 21th
from 13:00-17:00 Eastern DaylightTime

Managing Data with R

Before you can analyze data, it must be in a form you can analyze. That is where we typically spend most of our time. This 4-hour workshop shows how to perform the most commonly used data management tasks in R. For many topics we will cover both the standard built-in approach and then perform the same task using add-on packages that are often much easier to use.

We will devote most of our time to working through examples that you may run simultaneously on your computer. However, handouts will include each step and its output if you prefer instead just relax and take notes. Most examples come from the extensive data management examples in R for SAS and SPSS Users, R for Stata Users, and http://r4stats.com. That makes it easy to review what we did later with full explanations, or to learn more about a particular subject by extending an example which you have already learned. (No coverage of SAS, SPSS or Stata is included in this workshop.)

At the end of the workshop, you will receive a set of practice exercises for you to do on your own time, as well as solutions to the problems. The instructor will be available via email to address these problems or any other topic in the workshop.

Prerequisites

Attendees should know basic R programming, including how to read data files and call functions.

Learning Outcomes

When finished, you will be able to prepare most data sets for analysis.

Presenter

Robert A. Muenchen is the creator of the web site http://r4stats.com and is the author of the books, R for SAS and SPSS Users, and, with Joseph Hilbe, R for Stata Users. A consulting statistician with 30 years of experience, Bob is currently the manager of Research Computing Support (formerly the Statistical Consulting Center) at the University of Tennessee. Bob has served on the advisory boards of SPSS Inc., the Statistical Graphics Corporation and PC Week Magazine. His suggested improvements and/or programming code have been incorporated into SAS, SPSS, JMP, STATGRAPHICS and several R packages.

Course Outline (Data management topics have been moved to a separate workshop)

1.      Missing values

2.      Mean substitution

3.      Why the attach function is dangerous

4.      Transforming variables – within, transform, mutate

5.      Mathematical and statistical operators

6.      The “apply” family of functions and the plyr package

7.      Variable length vs. n of valid observations

8.      Adding function results to data frames

9.      Conditional transformations

10.  Sorting data (sort, order, arrange functions)

11.  Recoding variables

12.  Renaming variables

13.  Keeping and dropping variables

14.  Stacking/concatenating/adding cases to data sets

15.  Joining/merging/adding variables to data sets

16.  Creating summary/aggregate data sets to analyze further

17.  Reshaping data (wide to long and vice versa)

18.  “Casting” aggregates with the reshape package

19.  Character string manipulations using the stringr package

20.  Date / time manipulations using the lubridate package

  


 

Disclaimer:

We have the right to cancel the event for any reason at any time. Revolution Analytics will refund all monies paid for ticket sales in full in the event of a cancellation.  We are not responsible for any travel related expenses incurred by attendees for this event. This includes but not limited to transportation, hotel accommodations or any other travel related expenses secured by the attendee, due to a cancellation on our part.

Cancellation Policy

30 days from event date                                                    Full refund less 10% of the paid ticket price

21 days from event date                                                    50% of paid ticket price

Within 15 days of event date                                             Non refundable

 


Note:

- discount offers cannot be combined

- A student ID Number is not a proof of full time university enrollment to get the student’s discount.  Proof of enrollment in 9 units or more on a current academic registration document will be required to receive the student's discount.

Have questions about Managing Data with R - Eastern Time (TRA-26)? Contact Revolution Analytics, Inc.

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