CONG WANG, PH.D.
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Mini-lectures: Educational Data Analysis in R

This series of mini-lectures is an introduction to analyzing real-world educational data using R. It is designed for people with basic knowledge of quantitative methods and are interested in using R to address educational and psychological research questions. In the mini-lecture videos, I will introduce basic concepts and functions in R; however, this is NOT an R programming course. 
Videos ​
1. Data Import in R (12 mins): https://youtu.be/fMPLkObZUqQ
2. Removing Invalid Data in R (7 mins): https://youtu.be/iq4Q1IHbdcc

3. Renaming Multiple Variables in R (8 mins): https://youtu.be/46CqOXy1Wdk
4. Removing Unneeded Columns (Variables) in R (9 mins): https://youtu.be/_Ek5CLDGTcc
5. How to merge multiple data files in R (9 mins): https://youtu.be/OhE2rqw5IcU
6. How to recode likert scale items in R (8 mins): 
https://youtu.be/bsOrBu1vucQ  
7. How to recode multiple-choice items in R (3 mins): https://youtu.be/FIzsJS6JYws  
8. How to calculate Cronbach's alpha in R (4 mins): 
https://youtu.be/1uRdUTHcotE​
9. How to create composite scores in R (4 mins): 
https://youtu.be/wH91U9tRszA
​
​Upcoming: How to check normality in R
​Lecture Notes​
1. Data Import in R
2. Removing Invalid Data in R
3. Renaming Multiple Variables in R
4. Removing Unneeded Columns (Variables) in R
5. How to merge multiple data files in R

6. & 7.  How to recode likert scale items and multiple-choice items in R
8.  How to calculate Cronbach's alpha in R
​9. How to create composite scores in R
Sample Data
1. 
1_Understanding_your_data.csv
​
2. PreLearningClimate.xlsx
3. PostLearningClimate.xlsx
​4. mydata.recoded

Courses that I can teach

Undergraduate level

Educational & Psychology-related
Elementary Psychology 
Educational Psychology
​Learning & Motivation
​
Statistical & Methodology-related
Elementary Statistical Methods 
Quantitative Data Analysis Methods in Education
Introduction to Statistics in Psychology/Education

Graduate level

Educational & Psychology-related
Advanced Educational Psychology
Advanced Motivation Theory


Statistical & Methodology-related
Factor Analysis 
Structural Equation Modeling
Multilevel Modeling
Multivariate Analysis in Educational Research​
Research Procedures in Education

Syllabi

Structural Equation Modeling
This course is an introduction to structural equation modeling procedures.  It focuses on various applications of SEM procedures.  Students will develop skills to conduct SEM research and critically review use of SEM in research.
 


edps_632_applied_structural_equation_modeling_syllabus_2019_spring.pdf
File Size: 449 kb
File Type: pdf
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Multilevel Modeling
This course is an introduction to hierarchical linear modeling, which is designed to provide students with an understanding of both the statistical underpinnings and the application of hierarchical linear models (HLMs) in educational research. The course doesn't focus on the mathematical mechanism of statistical methods.  Emphasis is placed on the conceptual understanding of models, the interpretation of model results, and the applications of HLM in empirical studies. 


mlm_syllabus__spring_2016_revision.pdf
File Size: 617 kb
File Type: pdf
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