2016 Stats Camp: Summer Statistical Institute

Graduate students, faculty, post doctoral fellows, staff, and others are invited to attend the KU Stats Camp. We are using a weekly topic framework (along with daily pricing for participants). Registration is open to non-KU folks, as well, whether students or faculty in other institutions, or employees of the private or public sectors.

2016 Stats Camp: Summer Statistical InstituteWeek-long or Daily Workshop Format

KU Stats Camp runs May 23rd - 27th (R Track), May 31st - June 3rd (Stata Track), and June 7th - 10th (Multilevel Regression Track). Each week will have a focus, and participants are encouraged to enroll for all classes in each week.  Please see an in-depth description of each Stats Camp Track below.

Each four day course is $200 for KU affiliates and $280 for non-KU affiliates.

For KU students and faculty, the daily price of attendance is $50. For people who are not KU affiliated, the daily charge is $70.

Housing Options for Out-of-Town Attendees:

Campus Housing is available on a limited and first-come-first-serve basis.  Rates are $50/night for a one bedroom apartment. 

The CRMDA also has reduced rates available at the Double Tree by Hilton for approximately $119/night and at the Mariott - Spring Hill Suites for $107/night.  Please contact Roxie Lytle via email or phone: 785-864-3353 for reservations for either campus or hotel accommodations. Please note that you cannot use the respective websites to book these special rates. 

If you're ready to enroll for the KU Stats Camp: Summer Statistical Institute, please click on the appropriate box.

 

  

There will be 40 seats open in each workshop.  Enrollment (as well as refund eligibility) will cease at the close of business (5pm CST) May 20th 2015.  If classes reach capacity, priority will be given to those participates that have chosen to enroll in the full four (4) day course.  If you need special consideration, please contact the CRMDA at crmda@ku.edu.

CRMDA 2016 Summer Institute Course Descriptions:

9am to 4pm , with a long lunch

Watson Library, Room 455

Week 1: R Track

Due to overwhelming interest, we’ve had to close enrollment in the R track (May 23rd – 27th) of the Summer Statistical Institute: KU Stats Camp.  If you wish to be placed on the waitlist, please email me at crmda@ku.edu

Day 1 05/23

Installation & Getting to Know R

Instructor: Dr. Paul Johnson, CRMDA Director and Professor, Political Science

  • User Interface demonstrations.
  • Illustrating Functions.
  • Publication quality Line art & Graphics.

Day 2 05/24

Establishing a Replicable Research Process

Instructor: Dr. Paul Johnson, CRMDA Director and Professor, Political Science

  • Data Import, recoding
  • graphical exploration.
  • Exporting tables for reports.

Day 3 05/25

Statistical Analysis the R Way

  • Regression & ANOVA,
  • Structural Equation Modeling
  • Moderation and Mediation

Day 4 05/26

R Toolkit for Interacting with Data

  • Matrix Algebra with R
  • Iteration, data subsets.
  • Creating R functions to customize projects

Day 5 05/27

Monte Carlo Programming & Power Analysis

Instructor: Ben Kite

  • Monte Carlo simulation in R
  • Power analysis: definition and implications
  •  Using Monte Carlo simulation to estimate power

Week 2 - Stata Track

 

Day 6 05/31

An Introduction to Stata for Statistical Analysis

Instructor: Dr. Jacob Fowles, CRMDA and School of Public Affairs and Administration

  • Learn important concepts and best practices for quantitative analysis in the social sciences.
  • Demonstrate how these conventions can be implemented using Stata.
  • Review the Stata interface, beginning with point and click menus and progressing to basic programming.

Day 7 06/01

Reliable and Reproducible Workflows Using Stata

Instructor: Dr. Jacob Fowles, CRMDA and School of Public Affairs and Administration

  • Lean to write and debug simple Stata programs using built-in do-file editor. 
  • Demonstrate best practices in writing do-files and simple options for identifying and correcting common do-file errors.
  • Learn common routines for cleaning, importing and merging data; generating, recording and labeling variables; and generating descriptive data tables and plots.

Day 8 06/02

Automating Common Tasks in Stata

Instructor: Dr. Jacob Fowles, CRMDA and School of Public Affairs and Administration

  • Demonstrate how Stata's pre-canned capabilities can be extended to user-written ado-files.
  • Learn to write code to automate data cleaning, organization and analytic tasks.
  • Introduce simple code to download data from the web using Stata.

Day 9 06/03

Data Visualization in Stata

Instructor: Dr. Jacob Fowles, CRMDA and School of Public Affairs and Administration

  • Review Stata's pre-canned programs for creating plots, charts, and graphs. 
  • Introduce common syntax for customizing graphics using Stata's suite of graphing commands.
  • Learn to use Stata's "margins" and "marginsplot" commands for visualizing regression results.

Week 3 - Multilevel Regression Track

 

Day 10 06/07

Multi-Level Regression - Day 1

Instructor:  Dr. Paul Johnson

  • Overview of Multilevel Models (MLM)
  • Regression foundations review
  • Matrix algebra notation and concepts for MLM
  • Random Intercepts: introduction and visualization

Day 11 06/08

Multi-Level Regression - Day 2

Instructor: Dr. Paul Johnson

  • Random Intercepts: the Z matrix
  • Fixed versus random effect models: clash of paradigms
  • Comparing estimation procedures in R, Stata, and others
    Random Slopes: The "two step" formulation of the MLMs: introduction and visualization
  • Visualizing random intercepts.
  • Comparing estimation procedures in SAS, R, and Stata. 
  • Testing hypotheses.

Day 12 06/09

Multi-Level Regression - Day 3

Instructor:  Dr. Paul Johnson

  • Hypothesis testing
  • Specification decisions
  • Worked examples

Day 13 06/10

Multi-Level Regression - Day 4

Instructor:  Dr. Paul Johnson

  • Overview: Generalized Linear Mixed Models (GLMM).
  • Overview: Longitudinal (short panel) model
If you're ready to enroll for the KU Stats Camp: Summer Statistical Institute, please click on the appropriate box.

  

 

  

 

 


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