Education 160
Introduction to Statistical Methods in Education
Fall Quarter, 2001
Kenji Hakuta, Professor Phone: 725-7454 / e-mail hakuta@stanford.edu/ Office Hours: by appointment (send e-mail), CERAS 238 I will generally be in the Big Tree classroom a half-hour before each lecture, and will hang around after class to answer questions. |
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Taylor Martin, Teaching Assistant Office Hours: Wednesday 12-1 / CERAS 225 e-mail taylor.martin@stanford.edu
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Course Text
Welkowitz, J., Ewen, R. & Cohen, J. Introductory Statistics for the Behavioral Sciences. 5th Edition. Harcourt Brace College Publishers.
Statistical Package for the Social Sciences (SPSS).
Course Description
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 general linear modelling (Ed 250A), analysis of variance (Ed 250B) and beyond.. The 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. Every week, you will be given problems posted on this website to complete. You should come to the discussion section, to be held on Thursdays, 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. The final grade will be based on four equal weightings of the homework excercises, the two take-home exams, and a final project (to be announced).
Week of |
Main Topics
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Data Sets (for homeworks, see Taylor's Resources page). |
9/24 |
Tour of statistics and measurement, research design. Ch. 1. No class on Thursday, Sept. 27 in observance of Jewish holiday. 9/26 |
District STAR dataset |
10/1 | Frequency Distributions, Central Tendency, and Variability. Ch. 2, 3, 4, 5. 10/1 10/2 10/3 |
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10/8 | Data Transformation and Graphical Displays. Ch. 6, 7. 10/8 10/9 | |
SPSS Workshop 1, October 10, 11
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10/15 |
Normal Distribution and Statistical Inference. Ch. 8, 9. 10/15 10/16 10/17 |
Homework hours data ; Financial Times GMAT article |
10/22 |
Testing for Differences between Means. Ch. 10, 11. 10/22 10/23 |
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Take Home Examination #1: Handed out October 24,
due October 29, 5:00 PM
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10/29 | Correlation and Regression. Ch. 12, 13 10/29-30 10/31 | |
SPSS Workshop 2, October 31, November 1
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11/5 | Regression, Continued. Ch. 14 11/6 | |
11/12 | Power Analysis (Ch. 14); One-Way Analysis of Variance. Ch. 15 11/12 | |
SPSS Workshop 3, November 14, 15
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11/19 | One-Way Analysis of Variance. 11/13-11/18 | Check out group project: sex differences in hand size estimation |
11/26 | Simple Factorial Design. Ch. 16 11/26 | 3by3 dataset |
SPSS Workshop 4, November 28, 29
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Take Home Examination #2: Handed out November 28,
due December 3, 5:00 PM
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12/3 | Nonparametric Statistics. Ch. 17; Review and Looking Ahead. 12/4 12/5 | |
SPSS Workshop 5, December 5, 6
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