Statistics for Social Sciences I: Introduction to Statistics

Universidad Carlos III de Madrid

Course Description

  • Course Name

    Statistics for Social Sciences I: Introduction to Statistics

  • Host University

    Universidad Carlos III de Madrid

  • Location

    Madrid, Spain

  • Area of Study

    International Studies, Statistics

  • Language Level

    Taught In English

  • Course Level Recommendations

    Lower

    ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

    Hours & Credits

  • ECTS Credits

    6
  • Recommended U.S. Semester Credits
    3
  • Recommended U.S. Quarter Units
    4
  • Overview

    Statistics for Social Sciences I: Introduction to Statistics
    Bachelor in International Studies
    ECTS Credits: 6.0
    Semester: 2

    COMPETENCES AND SKILLS THAT WILL BE ACQUIRED AND LEARNING RESULTS

    Specific competences:
    1. Understand the basic concepts of population, sample, variable and statistic.
    2. Know how to summarize a sample using measures of centre and variability.
    3. Learn how to use statistical graphs to illustrate the main features of a sample.
    4. Understand and implement the basic ideas of a regression analysis.
    5. Learn how to estimate a population parameter based on sample data and how to formalize a hypothesis test.
    6. Use of statistical software.

    Transversal competences:
    1. Capacity of analysis and synthesis.
    2. Understanding of how to use computer packages.
    3. Problem solving.
    4. Teamwork.
    5. Critical reasoning.
    6. Verbal and written communication.

    DESCRIPTION OF CONTENTS: PROGRAMME

    1. Introduction.
    1.1. Concept and uses of statistics.
    1.2. Statistical terminology.
    1.3. Typos of variables.

    2. Analysis of univariate data.
    2.1. Representations and plots of qualitative data.
    2.2. Representations and plots of quantitative data.
    2.3. Numerical summary of a sample of data.

    3. Analysis of bivariate data.
    3.1. Representations and plots of qualitative and discrete data.
    3.2. Representations and numerical summaries of quantitative data: correlation and regression.
    3.3 Introduction to time series analysis.

    4. Probability and probabilistic models.
    4.1. Random experiments, sample space, elementary and composite events.
    4.2. Properties of probability.
    4.3. Conditional probability and its properties.
    4.4. Random variables and their characteristics.
    4.5. Bernoulli trials and related distributions.
    4.6. The normal distribution.
    4.7 Other distributions

    5. Introduction to statistical inference.
    5.1. Outline and objectives.
    5.2. Point estimators.
    5.3. Interval estimators.
    5.4. Fundamentals of hypothesis testing.
    5.5. Tests for normal means.
    5.6. Tests for proportions.
    5.7. Testing for independence.

    LEARNING ACTIVITIES AND METHODOLOGY

    Theory: Theory classes with materials available on the web.
    Prácticas: Problem classes. Computing classes using statistical software.
    Group tutorials for resolution of problems, doubts etc.

    ASSESSMENT SYSTEM

    Continuous evaluation:
    Two written tests counting 40% of the final grade.
    Group project counting 10% of the final grade.
    Continuous evaluation, exercises and practical classes, counting 10% of the final grade.

    Final exam. End of course exam counting 40% of the final grade.

    BASIC BIBLIOGRAPHY

    D. Huff. How to Lie with Statistics. W.W. Norton & Company.
    G. Davis, B. Pecar. Business Statistics using Excel. OUP. 2010

    ADDITIONAL BIBLIOGRAPHY

    D. Rowntree. Statistics without Tears. Penguin Books.
    G. Klass. Just plain data analysis (2nd ed.). Rowman & Littlefield. 2012

Course Disclaimer

Please note that there are no beginning level Spanish courses offered in this program.

Courses and course hours of instruction are subject to change.

Eligibility for courses may be subject to a placement exam and/or pre-requisites.

Credits earned vary according to the policies of the students' home institutions. According to ISA policy and possible visa requirements, students must maintain full-time enrollment status, as determined by their home institutions, for the duration of the program.

ECTS (European Credit Transfer and Accumulation System) credits are converted to semester credits/quarter units differently among U.S. universities. Students should confirm the conversion scale used at their home university when determining credit transfer.

Please reference fall and spring course lists as not all courses are taught during both semesters.

Availability of courses is based on enrollment numbers. All students should seek pre-approval for alternate courses in the event of last minute class cancellations

Please note that some courses with locals have recommended prerequisite courses. It is the student's responsibility to consult any recommended prerequisites prior to enrolling in their course.