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Course 2020-2021 a.y.

30320 - QUANTITATIVE METHODS FOR SOCIAL SCIENCES (MODULE II - STATISTICS)

BIG
Department of Decision Sciences

Course taught in English


Go to class group/s: 23

BIG (6 credits - II sem. - OB  |  SECS-S/01)
Course Director:
REBECCA GRAZIANI

Classes: 23 (II sem.)
Instructors:
Class 23: REBECCA GRAZIANI


Suggested background knowledge
PREREQUISITES

The exam code 30320 ‘Quantitative methods for social sciences - module 2 (Statistics)’ is a prerequisite of the exam code 30337 Policy evaluation


Mission & Content Summary
MISSION

This course provides an introduction to both the logic and mathematics of statistics, with an emphasis on political science applications. The course introduces students to the practice of data analysis, covering univariate and bivariate descriptive statistics and inference. Emphasis is put on the investigation and statistical assessment of relationships between two or more variables. The lectures switch between frontal lecturing, small group discussions and simulations. Students should bring their laptop to each session. Each session is indeed designed with the aim of fostering independent work by students, who are strongly encouraged to autonomously explore and apply the techniques shown and discussed by the instructor. The analyses are run using STATA with an emphasis on an effective use of the software and interpretation of the results. In sum, this course aims to cultivate students’ nascent analytical abilities and develop their statistical reasoning and literacy; equip students with a computational competence in STATA software in a supportive learning environment for all students.

CONTENT SUMMARY
  • Describing data through tables, charts and synthetic measures.
  • Describing association between two variables.
  • Inference on the mean and the proportion: point estimation, confidence interval estimation and significance tests.
  • Inference on bivariate associations: two-samples t test and chi-square test of independence.
  • Correlation analysis.
  • Regression analysis: simple linear regression and multiple linear regression.

Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
  • Read reports and scientific articles that make use of basic statistical techniques.
  • Learn basic and advanced statistical techniques.
  • Set up and run empirical analyses, that require the use of basic and advanced statistical techniques to study relevant problems in Economics, Sociology and Political and other Social Sciences.
APPLYING KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
  • Use a statistical software (STATA) for data management and to implement basic statistical techniques for the empirical part of social sciences study.

Teaching methods
  • Face-to-face lectures
  • Online lectures
  • Exercises (exercises, database, software etc.)
DETAILS
  • Exercises are delivered through Bboard platform for E-Learning. They are multiple choice questions, with solutions provided as feedbacks

Assessment methods
  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
  •   x x
  • Individual assignment (report, exercise, presentation, project work etc.)
  • x    
  • Group assignment (report, exercise, presentation, project work etc.)
  •   x x
    ATTENDING AND NOT ATTENDING STUDENTS

    Two partial exams or a general exam, four tests and a final assignment.

     

    Two partial exams 

    Delivered as Blackboard test, through Lockdown Browser with Respondus Monitor. The questions are both closed-ended questions and open-ended (essay questions). Each partial exam is graded out of 22. The arithmetic average of the partial exams' marks contributes to the final grade.

    The tests aim at assessing the students acquired knowledge on the content of the course, in particular with reference to the first and second Intended Learning Outcomes, as the ability of reading and providing the correct interpretation to the report of analyses run by others. Students answer the questions based on the theory and/or the inspection of STATA outputs. 

     

    General Exam 

    Delivered as Blackboard platform for E-Learning test, through Lockdown browser with Respondus Monitor. The questions are both closed-ended questions and open-ended (essay questions). The General Exam is graded out of 22.

    The test aim at assessing the students acquired knowledge on the content of the course, in particular with reference to the first and second Intended Learning Outcomes, as the ability of reading and providing the correct interpretation to the report of second-hand analyses. Students answer the questions based on the theory and/or the inspection of STATA outputs. 

     

    Two Tests

    Delivered through the Blackboard platform for E-Learning of the course, with both closed-ended questions and open-ended (essay questions). Each test gives at most 3 points, the arithmetic average of the tests' marks contributes to the final grade.

    Students answers at the questions based on the result of the analyses run with STATA, so to achieve the fourth Intended Learning Outcomes, as to use a statistical software (STATA) for data management and to implement basic and advanced statistical techniques for the empirical part of social sciences study.

     

    Final Assignment

    The final assignment consists in an analysis of a provided dataset based on a research question, set by the instructor. The report with a description of the results and comments should be posted in Blackboard platform for E-Learning. The assignment provides up to 6 points.

    The project lets achieve the third and the fourth Intended Learning Outcomes, as to set up and run empirical analyses, that require the use of basic statistical techniques to study relevant problems in Economics, Sociology and Political and other Social Sciences and to use a statistical software (STATA) for data management and to implement basic statistical techniques for the empirical part of social sciences studies.


    Teaching materials
    ATTENDING AND NOT ATTENDING STUDENTS
    • P. POLLOCK, The Essentials of Political Analysis, Sage, 2016, 5th edition (selected chapters).
    • A. AGRESTI, C.FRANKLIN, B. KLINGENBERG, Statistics: The Art and Science of Learning from Data, Pearson 2017, Global Edition (selected chapters).
    • Online exercises delivered through Bboard platform.
    • Lectures Notes.
    Last change 14/12/2020 19:51