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JOHN CABOT UNIVERSITY

COURSE CODE: "PL 208"
COURSE NAME: "Statistical Analysis for Political Science"
SEMESTER & YEAR: Fall 2023
SYLLABUS

INSTRUCTOR: Bogdan Gabriel Popescu
EMAIL: [email protected]
 HOURS: MW 3:00 PM 4:15 PM
TOTAL NO. OF CONTACT HOURS: 45
CREDITS: 3
PREREQUISITES:
OFFICE HOURS:
COURSE DESCRIPTION:
This is an applied course on statistical methods commonly used in social science research (including political science and sociology) and provides the necessary foundation to conduct your own analysis and to help you interpret the numbers presented in the media. Students will learn how to read statistics in a research context, what data to use for different research topics, to adopt research designs that are relevant for the research question, use statistical tests and draw conclusions based on statistical tests. Students will also learn how to carry out statistical tests using statistical packages, and to interpret results based on their own analyses.
SUMMARY OF COURSE CONTENT:

This is an applied course on statistical methods commonly used in social science research (including political science and sociology) and provides the necessary foundation to conduct your analysis and to help you interpret the numbers presented in the media. Students will learn how to read statistics in a research context, what data to use for different research topics, adopt research designs relevant to the research question, use statistical tests, and draw conclusions based on statistical tests. Students will also learn to carry out statistical tests using statistical packages and interpret results based on their analyses.

The course will convene twice a week. There will be lectures covering statistical concepts applied to political science and practical lab sessions where students will use statistical software to conduct the tests. There will be assignments that have to be completed every week. The grades will be 30% midterm, 30% final exam, and 40% weekly assignments.
LEARNING OUTCOMES:
Upon successful completion of this course the students will be able to:

- Use statistical core terminology accurately.
- Organize data using both numerical and graphical methods.
- Use measures of central tendency and variability to summarize a data set.
- Carry out tests of hypothesis about population parameters.
TEXTBOOK:
NONE
REQUIRED RESERVED READING:
NONE

RECOMMENDED RESERVED READING:
NONE
GRADING POLICY
-ASSESSMENT METHODS:
AssignmentGuidelinesWeight
5 problem setsYou will be graded on problem sets of about five during the semester (40% of your grade) and two exams (each 30% of your grade). For the problem sets, you should work within a group. You will work on the problem sets independently for optimal learning and submit that version to me. You will then check the responses with the other team members and offer the updated responses to the problem set. After you tried the answers on your own, you should go back to the team, write down the correct answer, and submit your assignment. Your final grade for that assignment will be an average of what you submitted originally and the submission after you consulted with your group. Your colleagues will also grade how much you contributed to helping your fellow students. Thus, part of the grade for the problems set will also be how much you help your colleagues.40
Midterm 30
Final Exam 30

-ASSESSMENT CRITERIA:
AWork of this quality directly addresses the question or problem raised and provides a coherent argument displaying an extensive knowledge of relevant information or content. This type of work demonstrates the ability to critically evaluate concepts and theory and has an element of novelty and originality. There is clear evidence of a significant amount of reading beyond that required for the course.
BThis is highly competent level of performance and directly addresses the question or problem raised.There is a demonstration of some ability to critically evaluatetheory and concepts and relate them to practice. Discussions reflect the student’s own arguments and are not simply a repetition of standard lecture andreference material. The work does not suffer from any major errors or omissions and provides evidence of reading beyond the required assignments.
CThis is an acceptable level of performance and provides answers that are clear but limited, reflecting the information offered in the lectures and reference readings.
DThis level of performances demonstrates that the student lacks a coherent grasp of the material.Important information is omitted and irrelevant points included.In effect, the student has barely done enough to persuade the instructor that s/he should not fail.
FThis work fails to show any knowledge or understanding of the issues raised in the question. Most of the material in the answer is irrelevant.
-ATTENDANCE REQUIREMENTS:
ATTENDANCE REQUIREMENTS AND EXAMINATION POLICY
You cannot make-up a major exam (midterm or final) without the permission of the Dean’s Office. The Dean’s Office will grant such permission only when the absence was caused by a serious impediment, such as a documented illness, hospitalization or death in the immediate family (in which you must attend the funeral) or other situations of similar gravity. Absences due to other meaningful conflicts, such as job interviews, family celebrations, travel difficulties, student misunderstandings or personal convenience, will not be excused. Students who will be absent from a major exam must notify the Dean’s Office prior to that exam. Absences from class due to the observance of a religious holiday will normally be excused. Individual students who will have to miss class to observe a religious holiday should notify the instructor by the end of the Add/Drop period to make prior arrangements for making up any work that will be missed. 
ACADEMIC HONESTY
As stated in the university catalog, any student who commits an act of academic dishonesty will receive a failing grade on the work in which the dishonesty occurred. In addition, acts of academic dishonesty, irrespective of the weight of the assignment, may result in the student receiving a failing grade in the course. Instances of academic dishonesty will be reported to the Dean of Academic Affairs. A student who is reported twice for academic dishonesty is subject to summary dismissal from the University. In such a case, the Academic Council will then make a recommendation to the President, who will make the final decision.
STUDENTS WITH LEARNING OR OTHER DISABILITIES
John Cabot University does not discriminate on the basis of disability or handicap. Students with approved accommodations must inform their professors at the beginning of the term. Please see the website for the complete policy.
SCHEDULE
Week 1: Overview of Statistics
Week 2: Levels of Data
Week 3: Descriptive statistics
Week 4: Probability - I
Week 5: Probability - II
Week 6: Statistical significance testing and z-tests
Week 7: Correlation
Week 8: Univariate regression 1
Week 9: Univariate regression 2
Week 10: Univariate and Multivariate regressions
Week 11: Multivariate regressions
Week 12: Theories of Change
Week 13: Threats to Validity 
Week 14: Differences in Differences