HISTORY 595: QUANTITATIVE ANALYSIS OF HISTORICAL DATA

History 595 is a "how to" course. It teaches you how to use statistical analysis to answer historical questions. Although I do not assume that you have a knowledge of statistics or any math beyond algebra, you have to use some algebra to understand the statistics. The course also will make use of the SPSS data analysis program and a computer for computations. So you will need to understand how to use one of the programs and how to interpret the output. While the questions, data, and applications we will examine will be historical, you will be able to use the skills you learn to analyze all types of quantitative questions. These skills will be important to you if you pursue graduate training in history and/or the social sciences, and be equally useful if you pursue a career in business, government, or teaching. History 595 fulfills the methods requirement in the History major and the GER Quantitative Literacy (QLB) requirement.

  • Instructor: Dr. Margo Anderson
  • Required Text: Alan Agresti and Barbara Finley, Statistical Methods for the Social Sciences, 4th ed. Pearson Prentice Hall
    (available at NEEBO Books on Downer Ave.)
  • Materials: data storage on pantherfile or flash drive; calculator (recommended).
  • Classrooms: BOL 293, MW 2-3:15 PM
  • IMT: BOL 225 for Campus Computer Lab; Also Library, Union.
  • Telephones: Office: 414-229-3969, 229-4361. Make appointment by phone or via electronic mail: margo@uwm.edu
  • Instructor Office Location: Holton 320
  • Office Hours: MW 3:30-4:30 PM and by appointment, Holton 320.
  • Grading:
    • Undergraduates: There will be 10 home works, worth 50% of the total grade. The first seven will be due on the following Monday. The last 3 are biweekly, due on April 11, April 25, and May 9. More about this in class. The midterm will be on March 9 (worth 15%). The final exam, given on May 19, will be worth 25% of the grade. Attendance and class participation are worth 10%.
    • Graduate Students: There will be 10 home works, worth 40% of the total grade. The first seven will be due on the following Monday. The last 3 are biweekly, due on April 11, April 25, and May 9. More about this in class. The midterm will be on March 9 (worth 15%). The final exam, given on May 19, will be worth 25% of the grade. Attendance and class participation are worth 10%. You will also write a short research paper based upon your analysis of the data we are using (10% of the grade).

    This is a hard class. The material is cumulative, so if you miss a week or two, you will likely be very confused. The many assignments are designed to help you develop the routine to do well.Regular attendance in class also keeps you on track. I also take attendance to monitor how everyone is doing. So, my message is: Do not fall behind. Each week, you should expect to spend 6 hours outside of class time working on the computer, reading, and writing. Take time now to set aside those hours each week so you can do the work for the course.

    If you are a student with a disability, please feel free to contact me early in the semester for any help or accommodations which you may need.

    See www.uwm.edu/Dept/SecU/SyllabusLinks.pdf for UWM Academic policies.

    The URL for this syllabus is: https://sites.uwm.edu/margo/history-595/. The Annenberg Project has a video series, "Against All Odds: Inside Statistics." The tapes are available in the Multimedia Library and on the web, http://www.learner.org/resources/series65.html. These will supplement the materials in class. We will also link data sets, examples, lecture notes, and supplemental websites to syllabus, so the syllabus will grow in links as the semester progresses.

    Discussion Topics, Assignments, and Due Dates

    Week Date Topic
    1

    Jan 25

    		 Introduction: (1) Quantitative History, Historical Methods, Research and Computers. (2) matrix, case, variable, code/value. (3) algebra review. (4) levels of measurement. (5) linear relationships, y = a + bx. (6) Examples: Variables and Codebooks. Accessing data: Example from the City Building Process. Map First Short Assignment.
    Answer Key
    2 Feb 1 Univariate Statistics. Frequency Distributions. (1) Measures of central tendency: mean, median, mode. (2) Measures of dispersion: ntiles, range, maximum, minimum, standard deviation, coefficient of variation. Read: Agresti and Finley, ch. 3, pp. 31-61. Datasets Second Short Assignment.
    Output for assignment. Graph Paper Answer Key
    3 Feb 8 Where does all this data come from anyway? History of the Federal Statistical System. Lecture. February 8: Special Class in Lubar S250, 12:30-3:10. Probability. Read Agresti and Finley, ch. 4, pp. 73-99. Milwaukee 1880. Third Short Assignment.
    Answer Key.
    4 Feb 15 Inferences and Estimation, Standard Deviations, Standard Errors, confidence intervals.† Agresti and Finley, ch. 5, pp 107-133. Fourth Short Assignment.
    Output for Fourth Short Assignment. Answer Key
    5 Feb 22 Inference and Significance Tests. Agresti and Finley, ch. 6, pp. 143-75.Fifth Short Assignment.
    Answer Key
    6 Feb 29 Comparing means and proportions, T-Test. Agresti and Finley, ch. 7, pp. 183-209. Sixth Short Assignment Cross Tabulation Paper Assignment for Graduate Students or Extra Credit/Waiving Final Exam for Undergraduates Sixth Short Assignment Answer Key
    7 Mar 7 Comparing Categorical Variables. Chi Square Test, Agresti and Finley, ch. 8, pp. 221-247.
    Midterm Examples.
    Midterm
    MidtermAnswerKey
    8 Mar 21 Review of Univariate and Bivariate Methods. March 11 MIDTERM Returned.
    Seventh Short Assignment Seventh Short Assignment Answer Key
    9 Mar 28 Bivariate regression. Agresti and Finley, ch. 9, pp. 255-89. Regression
    Eighth Short Assignment
    Logarithms Scatterplot Regression Output Eighth Short Assignment Answer Key
    10 Apr 4 Multivariate Relationships. Agresti and Finley, ch. 10, pp. 301-315.
    Regression Models 1. U.S. States Dataset.
    New World Dataset.
    Regression Exercise.
    Usstates.sav variable list. Newworld.sav variable list.
    11 Apr 11 Multiple Regression and Correlation. Agresti and Finley, ch. 11, pp. 321-355.Ninth Short Assignment,
    Ninth Short Assignment Output
    Ninth Assignment Answer Key, Analysis of Variance. Regression Models 2,
    Regression Examples
    12 Apr 18 Analysis of Variance (ANOVA), Agresti and Finley, ch. 12, pp. 369-403.
    Anova Output
    13 Apr 25 Regression with Dummy Variables. Agresti and Finley, ch. 13, pp. 413-33. Tenth Short Assignment. Regression Models 3. Residuals Analysis. Time Series
    14 May 2 Models and Regression Diagnostics.
    Regression Exercise.

    15

    		 May 9 Logistic Regression.
    Logistic Regression. Agresti and Finley, ch. 14-15 (parts), pp. 441-452; 483-493, sections which correspond to lectures.
    16 May 18 Final Examination: 12:30-2:30 PM.
    Example of Final Exam.
    Final Exam. Extra Credit Exam
    Graduate Students: Turn in Final Paper.