Introduction to Statistical Methods in Education
Fall Quarter, 2010
Welkowitz, J., Cohen, B. & Ewen, R. Introductory Statistics for the Behavioral Sciences. 6th Edition. John Wiley & Sons..
STATA (not required but recommended).
Kenji Hakuta, Professor
e-mail email@example.com Office Hours: by appointment (send e-mail), Cubberley 228
I will generally be in the Big Tree classroom a half-hour before each lecture, and will hang around after class to answer questions.
Daniel Klasik, Teaching Assistant
The primary objective of the course is to introduce you to the major basic concepts in descriptive and inferential statistics, explore applications in educational research, and to prepare you for subsequent statistical courses in multivariate statistics and beyond. (If you do not intend on taking subsequent statistics courses, you should register for Education 150). This course begins with methods to describe and summarize frequency distributions. This is followed by various methods to describe the relationships between two variables. Finally, we provide an introduction to probability theory methods to draw inferences about the relationship between samples used in studies to the universe from which the samples were drawn. You will also be introduced to a statistical software program, STATA. You are required to concurrently take the workshop course on STATA (Education 401B) unless you are already familiar with it. This course is meant to be informative and fun (yes, fun!), and we guarantee everyone that after this course, you will want to know more, and that the world of statistical thinking will never seem the same.
Homework exercises. Most weeks, you will be given problems posted on this website to complete. We very much encourage you to do these problems in groups so that you can have a chance to discuss them and pose questions. You should come to the discussion section held on Fridays with your answers. The sections will discuss the problems and answers, and you may annotate your homework answer during the sections, at the end of which you will be asked to hand them in. Each homework will be graded as pass/no pass, but the primary intent of the homework is to assess your on-going learning and to guide our own instructional efforts. So, on your homework sheets, please feel free to include questions and comments that can help us teach you better.
Exams. There will be two open-book exams during the course, with computational problems similar to those found in the homework problems, as well as conceptual questions.
Grading. This course will be letter-grade only. The final grade will consist of the following: 25% midterm exam; 50% final exam; 25% homework.
Class Slides, Data Sets, Homework Assignments, Announcements
Tour of statistics and measurement, research design.
The correlation coefficient as a bivariate descriptive statistic.
Readings: Ch. 1, 2, 3.
Components of r : the Mean, SD, and z-score.
Distributions and transformations to handle data weirdness.
Readings: Ch. 4, 5, 6, 7.
Regression and prediction
Readings: Ch. 12
Non-parametric techniques (Ch 21: pp. 449-452)
Probability distributions (Ch. 8)
In-class exam (open book) on 10/18
Inferences about the population mean from a sample (Ch. 9)
|Lecture 10/20 slides on sampling distributions, and z and t distributions|
Determining confidence intervals for a population mean (Ch. 10)
Testing for the significance of the difference between two means (Ch. 11)
Testing for the significance of the difference between two means - continued.
Appreciating the size of the difference between means, etc.
Power analysis (Ch. 14)
One-way Analysis of Variance and post-hoc comparisons (Ch. 15-16).
Simple Factorial Design (Ch. 17)
Repeated measures ANOVA (Ch. 18)
|11/22||Thanksgiving week - NO CLASSES - Happy Thanksgiving!||
|11/30||Nonparametric Statistics, and Review (Ch. 19-21)|