EDB 9080: Quantitative Methods I

Syllabus for Spring 2020



Instructor: Dr. Satish Nargundkar 
Office: RCB 727, 35 Broad St., ATL

Office Hours:  By appointment 

E-Mail: snargundkar@gsu.edu    

Phone: (678) 644 6838  


Links to lecture slides, assignment details, and other resources will be added over time.

Changes to this schedule may be necessary based on class progression – any changes will be communicated to the class as appropriate.






January Residency

Jan 24:


Course Overview

Data Types, Basic Terminology, Dependent and Independent variables

Descriptive Statistics

Burns & Burns: 7, 8, 10

Standard Deviation Exercise


Excel Spreadsheet


Lung Capacity Data

Read Piketty et al paper before class


Questions to think about as you read the paper


Jan 25:


Sample Variance (why n-1?)

Principal Components / Factor Analysis -

Interpreting SPSS Output

(Dr. Todd Grande, Youtube)

Factor Data


Burns & Burns, 18

UCLA Digital Research and Education, Stat Consulting


Statsoft.com online textbook


Satish & Milind Paper

Read this paper

(Is Big 5 Universal?)

Related Survey

(Big 5 Inventory)


February Residency

Feb 28:


Inferential Statistics

CLT and Conf Intervals

CLT Simulation by Satish



Burns & Burns:10, 12, 13, 14

Central Limit Theorem

(Data Science Video)


Hypothesis Tests (G. Martin)

Choosing a Test (XLSTAT)

Assignment 1 due: Description, Factoring


Read this paper

(ANOVA on Social Media Metrics)

Feb 29:


Hypothesis Testing Intro


Chi-square Goodness of Fit test (zedstatistics)

Power and Sample Size


Statistical vs Practical Significance

One Sample t-test in SPSS

Paired Sample t-test

Independent 2-sample t-test

Chi-square indepence test in SPSS

Ethics of Hyp.Testing:

p-Hacking (Veritasium)

p-Hacking (John Oliver)

Another paper using ANOVA to read

March Residency

Mar 27:


Regression Analysis

Shoe Size Example

     Shoe Size Data

Lung Capacity Example

     Lung Capacity Data

Burns & Burns: 15-16

Paper – False Recall

Death to Dichotomizing


Notes by Satish 1

(Simple Regression)

Notes by Satish 2

(Multiple Regression)

Assignment 2 due: Hypothesis Testing

Mar 28:


Special Cases in Regression


1.   Hair Color – Dummy Variables

2.   Employee Errors – Multicollinearity data set

3.   Interaction Effect (Moderation) Data


Interaction New Example

Multicollinearity Ht. Data 

Heteroscedasticity Data


Why SEM?


Moderation Paper to read.


April Residency

Apr 24:



Mediation Effects

Mediation Effect Example


Questionnaire Design & Sampling

Burns & Burns: 9, 19-20


Mediation Methods Paper (Hayes 2009)


Moderation in SPSS Video

Mediation in SPSS Video

(Both with Hayes’ Process)

Assignment 3 due: Regression



Apr 25:


Team Project Presentations

Burns & Burns: 21

Project written report due by Apr. 28th.