Advanced Educational Statistics (Elective)
Advanced Educational Statistics
Instructor: Wei-Ting Chen
Office: 609 Administration Building
Office Hours: after class and by appointment
Telephone: 02-27321104 ext. 85052
Course Description and Objectives:
This course introduces the logic and methods of statistics and how they relate to educational and behavioral sciences. Initial discussions center on the role of statistics in science, statistical designs, measurement and how to obtain internal and external validity. The area of descriptive statistics enables students to present results and data in meaningful ways. Graphical methods and summary measures such as mean, median, standard deviation or correlation coefficients, will be discussed. Probability concepts then lay the foundation for determining whether apparent differences in measures are likely a chance occurrence given the natural variability present in the real world. These probability concepts will be formalized into methods for drawing inferences about populations based on samples of data. The inferential procedures covered includes methods for use in a variety of experimental designs.
Agresti, A. (2018). Statistical methods for the social sciences (5th ed.). Boston, MA: Pearson.
Readings should be completed prior to the class for which they have been assigned (see course schedule).
- Check-Ups (40%): Four times during the semester lecture will begin with a short in-class Check-Up. Each Check-Up will consist of five total questions from the lectures and readings covered since the previous Check-Up.
- Projects (60%): You must complete two projects for the course. The first project will require you to examine the methodology and statistics of a published research article of your own choosing. The second project will be similar but the focus will be on a research question developed by you. Further details on the projects will be provided during the semester.
- You are expected to attend and actively participate (i.e., ask thoughtful questions, contribute to discussions, relate concepts from class to your experience) in every class. You are responsible for all material covered in class.
- No late paper will be accepted and no make-up Check-Ups will be given except in extreme circumstances (i.e., family funeral, serious illness) and with very advance notice.
- You are expected to honor National Taipei University of Educational policies on academic honesty. Cheating in any form (e.g., copying answers, plagiarism, helping ad classmate cheat) will not be tolerated and will be dealt with in accordance with University policies.
- No texting, instagramming, facebooking, tweeting, etc. during class! These behaviors are distracting and disrespectful to me and your classmates.
- Your success in this class is important, and I wish to fully include all students in this course. Please inform me if you need special accommodations in the curriculum, instruction, or evaluation procedures in order for you to participate fully.
- Week 1: Introduction/Syllabus
Reading: Ch 1
- Week 2: Sampling and Measurement
Reading: Ch 2 (skip 2.4)
- Week 3: Descriptive Statistics
Reading: Ch 3
- Week 4: Probability Distributions
Reading: Ch 4
- Week 5: Check-Up #1; Statistical Inference: Estimation
Reading: Ch 5
- Week 6: Spring Break
- Week 7: Statistical Inference: Significance Tests
Reading: Ch 6 (skip 6.6~6.7)
- Week 8: Check-Up #2; Comparison of Two Groups
Reading: Ch 7 (skip 7.5~7.7)
- Week 9: Analyzing Association between Categorical; Variables: Chi-Square
Reading: Ch 8 (skip 8.5)
- Week 10: Linear Regression and Correlation
Reading: Ch 9
- Week 11: Check-Up #3; Introduction to Multivariate Relationships
Reading: Ch 10
- Week 12: Multiple Regression and Correlation
Reading: Ch 11.1~11.4
- Week 13: Multiple Regression and Correlation
Reading: Ch 11.5~11.8
- Week 14: Regression with Categorical Predictors: ANOVA Methods
Reading: Ch 12.1~12.3
Assignment: Project #1 (Due in Class)
- Week 15: Regression with Categorical Predictors: ANOVA Methods
Reading: Ch 12.4~12.7
- Week 16: Check-Up #4; Multiple Regression with Quantitative and Categorical Predictors: ANCOVA
Reading: Ch 13
- Week 17: The Do’s and Do Not’s of Model Building
Reading: Ch 14
- Week 18: Introduction to Advanced Topics in Quantitative Methods; Course Evaluation and Wrap Up
Assignment: Project #2 (Due on July 3, 2018)