Course Outline
Required Texts
Grade Requirements
Course Calendar
PHONE (312) 413-7274 OFFICE HOURS Appointment  or  Luck (3:00pm)
CLASS TIME Tue./Thu. : 11:00-12:15 CLASS MEETS IN BSB 369 
TA Branislav Seslija TA Office: BSB 1177  E-mail: bseslija@hotmail.com

Course Overview
 Political Data Analysis is a first course in modern methods of data analysis for the social and behavioral sciences. Although to the advanced statistics major this course will appear elementary, you are not required to have any prior exposure to statistics and/or mathematics except insofar as meeting the prerequisites – MATH 090 or MATH 092 or MATH 118. If you do not meet these prerequisites you must obtain my written permission to take this course for credit. 

In this course I have two goals: (a) to provide you with a firm grounding in the rudiments of statistical theories and concepts, and (b) to train you to analyze real world data via computer software routines – chiefly SPSS for Windows. The tools you acquire in this class will become the building blocks for any future interactions you have with statistics in or out of academia. Thus, it is of utmost importance to both your sanity and your post-graduation earnings potential that you inform me as soon as you start feeling lost. Each session builds upon the preceding material and hence missed class sessions and/or incomprehension of any section of the material covered in class will cumulate and confuse you at an increasing rate. Work hard to build a strong foundation and if you do, you will come to see that data analysis can be fun, challenging and financially rewarding. Of course, where would we be if it were not exasperating as well! Consequently, patience, enthusiasm, an open and inquisitive mind, and a willingness to work hard, and a sense of humor will stand you in good stead. 

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
The text listed below is Required Reading for this course, though I will provide you with notes and handouts when necessary -- gratis. The text is available at the UIC BOOKSTORE.
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. You will be able to download these from this webpage. 
Grade Requirements
The grade you earn in this course is strictly 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 ‘n’ homework assignments, two midterm exams, and one final exam. Specifically, 
  •  ‘n’ Homework Assignments together constitute 25 percent of your grade. Unless noted otherwise, each assignment matures at the time of our subsequent class session. Late assignments earn no grade. 
  • The Midterm Exams and the Final exam each contribute 25 percent (for a total of 75 percent) toward your grade. 

  • Note: the exams are not cumulative. Further, 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. 
  • It is in your best interest to submit complete and correct  homework assignments on time.  Should you run into any difficulties while tackling homework assignments please see the TA or set up an appointment with me. DO NOT copy a colleague’s homework; the cnsequences will be self-evidenct come exam day. Practice solving additional problems given at the end of the chapter in the text. 
  • All assignments come due on the specified date. I neither accept late submissions nor offer make-up homework assignments and exams. 
  • I am in the department well nigh five-six days a week and best reached by e-mail. My email address is ruhil@uic.edu. If you do not possess an e-mail account, obtain one immediately. 
  • This webpage serves as the clearinghouse for all course-related information -- for example, solutions to homework problems and answer keys to exams.  Check this webpage often.
  • This webpage (see also the Course Calendar) has links to various online statistics texts and statistics-related applets. I have attempted to arrange some of these links, especially the applets, according to the topic under discussion in class. 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. 
    Course Introduction
    • Syllabus and Questionnaire
     Section 1
     Introduction  to Statistics, Frequency Distributions,Central Tendency and Variation
  • Statistics, Science, and Observations
  • Populations and Samples
  • The Scientific Method and the Design of Experiments
  • Scales of Measurement
  • Discrete and Continuous Variables
  • Statistical NotationFrequency Distribution Tables & Graphs 
  • The Shape of a Frequency Distribution.
  • Mean, Median, & Mode
  • Range, Interquartile Range, Semi-Interquartile Range
  • Variance
  • Standard Deviation
  • Z-scores
  • Using Z-scores to standardize distributions
  • Study Guide 
  • Answer Key 1 
    • Chapter 1 
    • Homework Key 1 
    • Chapter 2 
    • Homework Key 2 
    • Chaptert 3 
    • Homework Key 3 
    • Chapter 4 
    • Homework Key 4 
    • Chapter 5 
    • Homework Key 5 
     Section 2
     Z-Scores, Standardized Distributions, Probability and Sample Means, Hypothesis Tests with Two Samples
  • Introduction to Probability
  • Probability and Normal Distribution
  • Percentiles, Percentile Ranks and Quartiles
  • Samples and Sampling Error
  • The Distribution of Sample Means
  • Probability and the Distribution of Sample Means
  • Introduction to Hypothesis Testing
  • Introduction to the t Distribution
  • The t statistic for an Independent-Measures design 
  • Hypothesis tests with the Independent-Measures t 
  • Assumptions of the Independent-Measures
  • Hypothesis tests for the Related-Measures design 
  • Uses and Assumptions for Related-Samples t tests 
  • Study Guide 
  • Answer Key 2 
  • NES 2000 Data 
    • Handout 6 
    • Homework 6 
    • Handout 7 
    • Homework 7 
    • Handout 8 
    • Homework 8 
    • Handout 9 
    • Homework 9 
    • Handout 10 
    • Homework 10 
    • Handout 11 
    • Homework 11 
     Section 3
     Estimation, ANOVA : Basic and Advanced, Correlation and Regression, The Chi-Square Statistic
  • Estimation with the z-Score 
  • Estimation with the t statistic 
  • Factors affecting the width of a Confidence Interval
  • The Pearson Correlation
  • Using and Interpreting the Pearson Correlation
  • Hypothesis Tests with the Pearson Correlation
  • The Spearman Correlation
  • Introduction to Regression
  • Parametric and Nonparametric Statistical Tests
  • The Chi-Square Test for Goodness of Fit
  • The Chi-Square Test for Independence
  • Assumptions and Restrictions for Chi-Square Tests
  • Study Guide 
  • Formula Sheet 
  • Handout 12 
  • Homework 12 
  • Handout 13 
  • Homework 13 
  • Handout 14 
  • Homework 14 
  • Handout 15 
  • Homework 15 
  • Handout 16 
  • Homework 16