2019 CRMDA Stats Camp: Summer Statistical Institute

Graduate students, faculty, staff, government agencies, corporations and others are invited to attend the KU Stats Camp. CRMDA is offering three weeks of sessions about R, Python Data Science and Structural Equation Modeling. KU Stats Camp begins the fourth week of May and continues into the first week of June. 

Registration Open!

Registration process depends on the source of funding and the participant's identity. Please choose the one that fits your situation.

1. KU Affiliate (faculty, staff, or student) using Grant or Departmental Funds, CLICK HERE to register and an invoice will be generated.

2. KU Student Early Bird Rate (available until April 12), CLICK HERE to register and pay with credit card.

3. Faculty and students from any educational institution (including KU), employees of non-profits, or government agencies, CLICK HERE to register and pay with credit card.

4. Industry or commercial clients, CLICK HERE to register and pay with credit card.

If you need special consideration or needs, please contact CRMDA at crmda@ku.edu.

Can't attend in person? Attend remotely using Zoom!

If you are a student, faculty member or staff at KU, go to kansas.zoom.us to access your account. If you are not affiliated with KU, Zoom is a free web conferencing service. To sign up for an account, go to zoom.us.


Hotel/Housing Info

If you are an out of town guest, CRMDA has cooperative relationships with local hotels. We refer guests to the Double Tree by Hilton Hotel (785-841-7077) and to the Halcyon House Bed Breakfast (785-841-0314). When calling to make a reservation you should inquire about the KU rates. There is a limited number of rooms in KU Guest Housing. Space is filled on a first-come-first-serve basis. Nightly rates are $55 to $70 for available one and two bedroom apartments. Visitors who intend to stay in campus housing must check in between 3 p.m. and 5 p.m. and must check out by 10 a.m. The Student Housing Office is located at Corbin Hall, 422 W 11th Street, Suite DSH and is open from 8 a.m. to 5 p.m. Monday-Friday. Reservations must be made through the CRMDA office. Please email crmda@ku.edu or phone: 785-864-3353 to request a campus accommodation.


Our sessions are on the main campus of KU. Weekly parking passes are available from the KU Parking Department located in the Allen Fieldhouse Garage on the 3rd level (1501 Irving Hill Road, Lawrence, KS 66045). This would allow guests to park in any unmarked stall in Gold, Blue, Red, or Yellow lots. To obtain a pass, it is necessary for visitors to go to the Parking office. They are open from 7:30 a.m. to 5:00 p.m. Monday thru Thursday and close at 4:30 p.m. on Fridays. The Parking office recommends visitors call ahead (785-864-7275) so the paperwork and payment is completed in advance. Tell them you are with the CRMDA Summer Statistical Institute to receive the reduced price for a weekly pass.


CRMDA 2019 Summer Institute Course Descriptions

Sessions daily 9 a.m. - 12 p.m. & 1:30 p.m. - 4 p.m.

Week 1: R
Wescoe Hall, Room 4066 (EGARC: Ermal Garinger Academic Resource Center)

Day 1 05/20

Getting to Know R

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

  • R User Interface, accessing documentation, code preparation, help pages
  • Line Art: publication quality illustration and technical drawings

Day 2 05/21

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 05/22

Statistical Analysis the R Way

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

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

Day 4 05/23

R Toolkit for Interacting with Data

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

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

Day 5 05/24

Monte Carlo Programming & Power Analysis

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

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


Week 2: Python Data Science
Wescoe Hall, Room 4066 (EGARC: Ermal Garinger Academic Resource Center)

Day 1 05/28

Getting Started in Python

Instructor: Dr. Jonathan P. Lamb, CRMDA Faculty Fellow, Associate Professor of English

  • What is Python?
  • Installing Python and Anaconda
  • Navigating around Jupyter Notebooks
  • Discuss basic features and functions of Python

Day 2 05/29

Working with Text Data

Instructor: Dr. Jonathan P. Lamb, CRMDA Faculty Fellow, Associate Professor of English

  • Work with texts and the question of data
  • Introduce National Language Toolkit (NLTK)
  • Discuss key functions and basic text analysis using NLTK
  • ​Advanced Text Analysis, Corpus Analysis and Sentiment Analysis
  • Topic modeling and measuring document similarity

Day 3 05/30

Data Science

Instructor: Dr. Jonathan P. Lamb, CRMDA Faculty Fellow, Associate Professor of English

  • Introduce Pandas
  • Discuss various functions of Pandas
  • Perform statistical analysis

Day 4 05/31

Working with Internet Data

Instructor: TBD

  • Scrape data from the Internet
  • Understand web data formats
  • Turn webpages into datasets
  • Analyze Internet datasets

Week 3: Structural Equation Modeling (SEM)
Watson Library, Room 455


Day 1 06/03

Introduction to Structural Equation Modeling

Instructor: Dr. Ed Merkle, University of Missouri, Department of Psychological Sciences

  • From Regression to SEM
  • Confirmatory Factor Analysis
  • Estimation and Evaluation
  • Advanced Topics: Multiple groups, Measurement Invariance

Day 2 06/04

Creating Models and Fitting Them (Part 1)

Instructor: CRMDA Staff

  • Brief R Overview, including the bootstrap
  • Estimating SEM with the lavaan package
  • Moderators in SEM: Multi-group Models
  • The SEM Example Collection: Overview
  • The Examples fitted with lavaan

Day 3 06/05

Creating Models and Fitting Them (Part 2)

Instructor: CRMDA Staff

  • Introduction to Mplus
  • ​Ordinal Logistic Regression
  • SEM with Ordinal Data
  • Problems associated with Chi-Square Difference Tests
  • Presenting Results: The CRMDA semTable Function

Day 4 06/06

SEM Advanced Topics

Instructor: CRMDA Staff
  • Missing Data: Full Information Maximum Likelihood (FIML) versus Multiple Imputation
  • Mediation: Path Models

Day 5 06/07

New Modeling Opportunities 

Instructor: CRMDA Staff

  • Multi-Level Modeling and SEM
  • Formative Constructs: Rethinking CFA

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