Checking date: 04/04/2025 10:21:13


Course: 2025/2026

Statistics for social sciences I
(14084)
Bachelor in Political Science (Study Plan 2018) (Plan: 396 - Estudio: 205)


Coordinating teacher: KAISER REMIRO, REGINA

Department assigned to the subject: Statistics Department

Type: Basic Core
ECTS Credits: 6.0 ECTS

Course:
Semester:

Branch of knowledge: Social Sciences and Law



Objectives
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.
Learning Outcomes
C3: Know how to choose and use the different methodologies of political science and its subdisciplines for the understanding of past and future political phenomena S3: Use the information by interpreting relevant data avoiding plagiarism, and in accordance with the academic and professional conventions of the area of study, being able to evaluate the reliability and quality of such information. S9: Ability to discern which quantitative or qualitative research techniques are appropriate to apply depending on the phenomenon being analysed
Description of contents: programme
1. Exploratory Data Analysis. 1.1. Introduction. 1.2. Types of Variables. 1.3. Univariate Data Analysis. 1.4. Bivariate Data Analysis. 2. Statistical Inference. 2.1. Introduction. 2.2. Point and Interval Estimation. 2.3. Hypothesis Testing of Means and Proportions. 2.4. ANOVA Test. 3. Relationships Between Variables. 3.1. Introduction. 3.2. Relationships Between Qualitative Variables. Chi-Square Statistic. 3.3. Relationships Between Quantitative Variables. Correlation. 4. The Simple Regression Model. 4.1. Purpose of Analysis. 4.2. Estimation and Interpretation. 4.3. Diagnosis and Goodness of Fit. 4.4. Prediction.
Learning activities and methodology
Theory (3 ECTS): During theoretical sessions, the contents of the course will be introduced, explained, and illustrated with examples. Teaching materials will be provided on the Internet. Practice (3 ECTS): Blackboard exercises will be solved during practical sessions. Optionally, these activities can be complemented with applications to real datasets using statistical software. It is highly recommended that group review sessions be organized in the weeks before the midterm and final exams to address questions related to those exams.
Assessment System
  • % end-of-term-examination/test 60
  • % of continuous assessment (assigments, laboratory, practicals...) 40

Calendar of Continuous assessment


Extraordinary call: regulations
Basic Bibliography
  • D. Huff. How to Lie with Statistics. W.W. Norton & Company.
  • Remenyi, D. et al.. An introduction to statistics using Microsoft Excel . Academic Publishing. 2010
Additional Bibliography
  • D. Rowntree. Statistics without Tears. Penguin Books.

The course syllabus may change due academic events or other reasons.