2019 Summer Statistical Institute

This year, the Center for Research Methods and Data Analysis and the Achievement and Assessment Institute (AAI, in the School of Education) are partnering on the Summer Stats Camp.

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

3. 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 several establishments.  The Country Inn & Suites (785) 749-6010 offers an $89 nightly rate IF you mention you are with KU/CRMDA.  Also we have good experience with 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.

Parking

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. W. Jake Thompson, Psychometrician AAI and Dr. Paul Johnson, CRMDA Director and Professor, Political Science

  • Introduction to R and RStudio
  • Data Visualization
  • Data Manipulation

Day 2 05/21

Working with Data

Instructor: Dr. W. Jake Thompson, Psychometrician AAI and Dr. Paul Johnson, CRMDA Director and Professor, Political Science

  • Data Types
  • Importing Data
  • Tidying Data

Day 3 05/22

Statistical Analysis

Instructor: Dr. W. Jake Thompson, Psychometrician AAI and Dr. Paul Johnson, CRMDA Director and Professor, Political Science

  • Modeling Data (Regression & ANOVA)
  • Tidying Models
  • Visualizing Models

Day 4 05/23

R Toolkit for Interacting with Data

Instructor: Dr. W. Jake Thompson, Psychometrician AAI and Dr. Paul Johnson, CRMDA Director and Professor, Political Science

  • Iteration
  • Working with multiple models
  • Creating R functions to customize projects

Day 5 05/24

Reproducible Documents

Instructor: Dr. W. Jake Thompson, Psychometrician AAI and Dr. Paul Johnson, CRMDA Director and Professor, Political Science

  • Introduction to R Markdown
  • Multiple R Markdown Documents
  • CRMDA's R package "stationery"

 

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. Jacob Fowles, CRMDA Faculty Fellow, Associate Professor of Public Administration

  • 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. Paul Johnson, CRMDA, and others

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

Day 4 05/31

Working with Internet Data

Instructor: Charles Redmon, CRMDA GRA and KU Dept. of Linguistics, Longcan Huang, CRMDA GRA and KU Dept. of Linguistics, and others

  • 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: Dr. Paul Johnson, CRMDA

  • 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: Chong Xing, CRMDA GRA and Dept. of Communication Studies

  • 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: Dr. Paul Johnson, CRMDA, Chong Xing, CRMDA GRA and Dept. of Communication Studies, and others
  • Missing Data: Full Information Maximum Likelihood (FIML) versus Multiple Imputation
  • Mediation: Path Models

Day 5 06/07

New Modeling Opportunities 

Instructor: Chong Xing, CRMDA GRA and Dept. of Communication Studies

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

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