Education 160

Introduction to Statistical Methods in Education

Fall Quarter, 2007

Course Text

Welkowitz, J., Cohen, B. & Ewen, R. Introductory Statistics for the Behavioral Sciences. 6th Edition. John Wiley & Sons..

Statistical Package for the Social Sciences (SPSS)..

Course Description

Kenji Hakuta, Professor

e-mail hakuta@stanford.edu 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.

 

Stephen Newton , Teaching Assistant

e-mail: spnewton@stanford.edu

Jon Shemwell, Teaching Assistant (Cubberley 333)

e-mail :jshemwell@stanford.edu

The primary objective of the course is to introduce you to the major basic concepts in descriptive and inferential statistics, 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, SPSS. The 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, to be 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 take-home exams during the course, with problems similar to those found in the homework problems. These exams are under the honor code. Students may not discuss the problems with others until the problems have been turned in.

Grading. Since this is a prerequisite course for the statistics sequence, the intent is to enable all students who put in the effort to pass. The course will be graded pass/no pass. Homework assisngment and exams will be graded in such a way as to give feedback on your command of the materials. Instructors are committed to alerting students who are in trouble, and to suggest corrective steps.

Week of
Main Topics

Class Slides, Data Sets, Homework Assignments, Announcements

 

9/24

Tour of statistics and measurement, research design. Ch. 1; Frequency Distributions. Ch. 2

Lecture 1 Slides

New York Times Article; National Snow and Ice Data Center report on Arctic Ice

Lecture 2 Slide

Education Week article on NAEP scores

State-by-State 4th Grade Reading scores

NAEP state data

10/1 Central Tendency and Variability. Ch. 3, 4, 5.

Hands data

Lecture 3 Slides (Central Tendency)

Lecture 4 Slides (Variability)

10/8 Data Transformation and Graphical Displays. Ch. 6, 7.

Lecture 5 Slides (Transformations)

NYT: For Schools: No Lucky Number

Lottery data (xls)

Lecture 6 Slides (Graphical Displays)

SPSS Workshop 1, October 10
10/15

Normal Distribution and Statistical Inference. Ch. 8, 9.

Lecture 7 Slides (Hypothesis Testing and the Normal Distribution)

Lecture 8 Slides (Sampling Distribution)

Wine project ideas

High School and Beyond dataset (xls)

10/22

Testing for Differences between Means. Ch. 10, 11.

Lecture 9 Slides (t-distribution)

Lecture 10 Slides (independent samples t-test)

SPSS Workshop 2, October 24
Take Home Examination #1: Handed out Monday, October 22, due October 29, 5:00 PM
10/29 Correlation and Regression. Ch. 12, 13.

Lecture 11 Slides (correlation)

11/5 Regression, Continued.

Lecture 12 Slides (example)

Heights data

Lecture 13 Slides (Regression)

11/12 More correlation, regression, and Power Analysis (Ch. 14).

Lecture 13.5 (Regression continued)

Lecture 14 (Power Analysis)

SPSS Workshop 3, November 14
11/19 Thanksgiving week - NO CLASSES - Happy Thanksgiving! review sheet (Jon et al's) and Brian's picture from whiteboard
11/26 One-Way Analysis of Variance and Multiple Comparisons (Ch. 15, 16) Simple Factorial Design. Ch. 17

Lecture 15 (ANOVA)

Financial Times article on 10 top ideas in science

SPSS Workshop 4, November 28
Take Home Examination #2: Handed out Decmeber 3, due December 10, 5:00 PM
12/3 Nonparametric Statistics. Ch. 19, 20; Review and Looking Ahead.

Lecture 16 (Factorial ANOVA)

Lecture 17 (Nonparametric statistics)