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

Multicollinearity Ht. Data

Heteroscedasticity Data


Why SEM?


Moderation Paper to read.


April Residency

Apr 24:



Questionnaire Design & Sampling

Burns & Burns: 9, 19-20

Assignment 3 due: Regression



Apr 25:


Team Project Presentations

Burns & Burns: 21

Project written report due by Apr. 28th.