Introductory Statistics for Educational Research (EDUC 6777-005)
Fall 2025
Time: Every Wednesday 4:45 pm-7:15 pm
Location: 3700 Walnut Street Room 201
Instructor: Dr. Ji Eun Park
Email: jiparke@upenn.edu
Office Hours: By appointment (Virtual)
Course Description
The primary goal of this course is to build strong foundation in understanding of statistical
concepts and applications of statistical methods used in quantitative education research.
Topics we will cover include understanding different types of data, using descriptive
statistics to summarize data, inferential statistics to form and test your research
hypotheses and effectively communicating the results. Students will also gain basic R
coding experience to empirically analyze data. This course is the first course in statistics
in education research and there are no prerequisites for the course. Upon completion of
the course, students will have a good understanding of foundational statistical methods
used in education research, be able to conduct basic descriptive and inferential analyses
using R, and interpret the results in academic writing.
Textbook and Software

Howell, D. C. (2017). Fundamental statistics for the behavioral sciences (9th ed.).
Boston, MA: Cengage Learning.

R and R Studio, which can be downloaded for free
https://posit.co/download/rstudio-desktop/

Other class materials will be posted on Canvas as needed
Course Grading
Class Participation (20%): Students are expected to attend every class and engage in
classroom discussions. If you need to miss a class due to unavoidable circumstances,
please let me know by email in advance.
Problem Sets (50%): There will be five graded problem sets, which will focus on the topics
covered in class and applications using R. You are encouraged to discuss the problem sets
with your classmates, but need to submit your own, individual work. Each problem set will
be posted on Canvas and must be submitted via Canvas by the deadline. No late
assignments will be accepted.
Final Exam (30%): The final exam will be a take-home exam that covers cumulative
materials.
Technology in Classrooms
Using laptop in classroom is allowed but only for taking notes and using R. I also ask that
you do not use your cellphone during class except for urgent communications.
Academic Integrity
Students must abide by university’s code of academic integrity
https://catalog.upenn.edu/pennbook/code-of-academic-integrity/
Course Schedule (Tentative)
Dates
Topics
Textbook Readings
Aug 27
Introduction
Ch 1, Ch 2
Review Syllabus
Basic Concepts
Sep 3
Describing Distributions
Ch 3
Introduction to R
Plotting Data
Sep 10
Central Tendency
Ch 4, Ch 5
Variability
Sep 17
Correlation
Ch 9
Sept 24
Regression
Ch 10, Ch 11
Oct 1
Design of Experiments
Oct 8
Probability
Random variables
Sampling Distributions
Ch 7
Oct 9 – Oct 12
Fall Break
Oct 15
Density curves
Ch 6
Normal Distribution, t-distribution
Oct 22
Significance tests
Ch 8, Ch 12
(One-sample)
Oct 29
Significance tests
Ch 13, Ch 14
(Two related sample, independent
samples)
Nov 5
Power
Ch 15
Nov 12
Chi-square test
Ch 19
Nov 19
One-Way Analysis of Variance
Ch 16, Ch 17
Nov 26
Happy Thanksgiving!
(No Class, Thu-Fri class schedule on Tue-Wed)
Dec 3
Last Day of Class
Topics TBD
Dec 15
Final Take Home Exam