Course Outline
Required Texts
Grade Requirements
Course Calendar
PHONE (312) 413-7274 OFFICE HOURS By Appointment or Luck
CLASS TIME Tu./Th.:  6:00-7:15 CLASS MEETS IN  4133 BSB
TA E. Muhlenberg TA E-MAIL TBA ...
Course Overview
 This is a first course in modern methods of data analysis. Although the course is elementary in the level of mathematics required and in the statistical procedures covered, it will provide you with both an understanding of the main ideas of statistics and some crucial skills for working with real world data. The tools you will acquire in this class are the building blocks for any future interactions you have with statistics. Thus, it is of utmost importance to your health and well-being that you inform me as soon as you start feeling lost. Work hard to build a strong foundation and if you do, you will come to see that data analysis can be fun, challenging and rewarding. Of course, where would we be if it were not exasperating as well! Consequently, patience, enthusiasm, a willingness to work hard, and a sense of humor will stand you in good stead. I assume you come to class with an open and inquisitive mind. 

If you have any conditions or challenges that may make it difficult for you to meet the requirements of this course or that may lead you to require extra time on assignments, let me know so that we can make the necessary arrangements.

Texts and Other Requirements
  Required Texts & Related Materials

Alan Agresti and Barbara Finlay. 1997. Statistical Methods for the Social Sciences. (3rd Edition). New Jersey: Prentice Hall.

The text is NOT in the bookstore so you can buy a used copy online. If you don't know how, ask me.

You are also required to possess a couple of 3.5 floppy disks (or some other storage media), as well as a calculator capable of performing basic mathematical and statistical calculations (usually costs under $10). You must hold an active on-campus or off-campus email account. I usually broadcast answer keys, handouts, and other relevant data via the course website, and issue email alerts about the same. The webpage for the course is active, and I hope you will utilize this resource as well since I will rely on applets to complement standard instructional technology i.e., the chalk-and-blackboard. The URL for the webpage is:
  Recommended Texts 
Although not mandatory for this course, I urge you to have a look at Gonick, Larry and Woolcott Smith. 1993. The Cartoon Guide to Statistics. HarperCollins. ($12.00). This text has been described as a lifesaver for students plagued by numerophobia because it explains, with humor, the meaning of Bernoulli trials, p-values, and other statistical concepts. 

There are also a growing number of online statistics texts that explain the innards of statistics in an easy-to-understand manner, using everyday language and examples. A few of the better online statistics texts are linked below. You may be surprised at their usefulness. 

Internet Glossary of Statistical Terms
Statistics at Square One
Introductory Statistics: Concepts, Models, and Applications
The Data Analysis Briefbook
Statistics: The Study of Stability in Variation
Introduction to Probability
Virtual Laboratories in Probability and Statistics
HyperStat Online
The Statistics Homepage
The Statlets at Duke
More Applets

Resources for learning STATA
  Datasets & Codebooks 
From time to time I will provide you with data sets and codebooks. These data will be used either for in-class  exercises and/or for homework assignments. When these data are made available you will be able to download them from this space. In addition to these data Agresti and Finlay provide particular datasets that will prove useful for us. These data files may be downloaded from the following URL

A Random Number Table
Grade Requirements
   Grade Composition
The grade you earn in this course is a function of your ability to work hard and to persevere. Practice, practice, and practice; there is no other way known to mankind that bestows thorough understanding of the mechanics underlying the seemingly oblique formulae, or, for that matter, how they shed light on the phenomena of interest to us, researchers.  Four elements combine to fashion your grade a set of homework assignments and three exams. Specifically, 
  • the N homework assignments contribute 25 percent of your grade. Unless noted otherwise, each assignment will mature at the time of our next meeting. Unheralded late assignments will not be accepted for grade. 
  • each exam contributes 25 percent toward your course grade (for a total of 75 percent). The exams are not cumulative
Note: No points are awarded for class attendance since I assume you will not abscond without giving me prior notice of both the cause and date(s) of your absence(s). Failure to follow this convention will result in a penalty against your grade.
  A Few Things to Bear in Mind 
  • The problems featured on the exams will be identical (only in terms of the underlying logic) to those assigned for homework. It will, therefore, prove to your advantage if you complete the homework problem sets and in doing so, understand the concepts at hand. Should you run into any difficulties while tackling homework assignments please see the TA or set up an appointment with me. DO NOT opt to copy a colleagues homework; doing so will only guarantee a poor grasp of statistics. I also urge you to tackle the problems at the end of each chapter. 
  • Unless I grant a personal exception, all assignments come due on the specified date. I neither accept late submissions nor offer make-up homework assignments and exams. Exceptions to this policy are rare indeed. To qualify for the exception you must inform me in advance of planned absences and submit appropriate documentation upon returning to the fold. 
  • I am best reached by email : If you do not possess an e-mail account, please obtain one immediately. 
  • The course web page will serve as the clearinghouse for all course-related information -- for example, solutions to homework problems and answer keys to exams and homes. I broadcast an email message to all students enrolled in the course whenever new information is posted on the web page or if the page is updated for some other reason(s). Therefore, please acquire the habit of checking your email and the web page for this course every Wednesday evening and Thursday afternoon. This web page (see also the Course Calendar) has links to various online statistics texts and statistics-related applets. These tools have the potential to significantly enhance your learning process and I urge you to make full use of them. 
  • Course Calendar
    Since the emphasis in this course is on giving you a thorough understanding of rudimentary statistical theory, we shall set our own pace. Hence in the calendar below I do not demarcate specific portions of time during which particular topics will be covered. 
    • Syllabus and Introduction to STATA 7
    • Statistics, Science, and Observations
    • Populations and Samples
    • The Scientific Method & Experimental Design
    • Scales of Measurement
    • Discrete and Continuous Variables
    • Statistical Notation
    • Frequency Distribution Tables. 
    • Frequency Distribution Graphs 
    • The Shape of a Frequency Distribution.
    • Mean, Median, Mode
    • Range, Interquartile Range, Semi-Interquartile Range
    • Variance and Standard Deviation
    • Probabiltiy Distributions: Discrete & Continuous
    • The Normal Probability Distribution
    • Sampling Distributions
    • Sampling Distributions of Sample Means
    • Population, Sample, and Sampling Distributions
    • Point Estimation
    • Confidence Interval for a Mean
    • Confidence Interval for a Proportion
    • Choice of Sample Size
    • Elements of a Significance Test
    • Significance Tests for Means, and for Proportions
    • Decisions and Type I and Type II Errors
    • Small Sample Inference for a Mean (Students t)
    • Small Sample Inference for a Proportion (Binomial) 
    • Quantitative Data: Comparing Two Means
    • Qualitative Data:   Comparing Two Proportions
    • Small-Sample Inference for Means and Proportions
    • Comparing Dependent Samples
    • Nonparametric Statistics; Contingency Tables
    • Chi-Squared Test of Independence
    • More on Testing Independence
    • Measuring Association in 2 x 2 Tables
    • Association Between Ordinal variables
    • Inference for Ordinal Associations
    • Measuring Association: PRE
    •  Linear Relationships
    • The Principle of Least Squares 
    • The Linear Regression Model
    • Measuring Linear Association - The Correlation
    • Inference for Slope and Correlation
    • Model Assumptions and Violations
    • Association, Causality and Control Variables
    • Types of Multivariate Relationships
    • Inferential Issues in Statistical Control
    • Multiple Regression Model
    • Multiple Correlation and R-Squared
    • Inference for Multiple Regression Coefficients
    • Modeling Interaction