Métodos cuantitativos en Ciencias Políticas (2225.YR.013002.1)
Datos generales
Tipo: |
OPT |
Curso: |
2 |
Periodo: |
S semestre |
Créditos ECTS: |
6 ECTS |
Profesorado:
| Grupo |
Profesor |
Departamento |
Idioma |
| Year 2 |
Vladimir Manaev |
Economía, Finanzas y Contabilidad |
ENG |
Conocimientos previos
Knowledge of simple algebra (high school level).
Distribución de la carga de trabajo
Activities inside classroom + independent individual/group study.
Contribución de la asignatura al programa
The course will help students to:
1) Understand empirical statistical research in the field of political science
2) Be able to critically evaluate evidence-based policy and research
3) Understand underlying assumptions behind the most popular statistical methods
4) Understand the difference between descriptive and inferential claims
5) Be able to produce your own empirical research
Objetivos de aprendizaje de la asignatura
By the end, of the course, students should:
1. Be able to critically evaluate statistical evidence, and understand assumptions behind the most popular statistical procedures used in evidence-based public policy
2. Be able to understand the most popular statistical techniques used in empirical political science research
3. Be able to design statistical part of their own research
Contenidos
1. Unit 1. Intro to Descriptive statistics. Definitions. Graphical representations of data: histograms, scatter plots, boxplots, frequency tables. [AA, Ch2] |
2. Unit 2. Descriptive statistics. Measures of central tendency and dispersion. Correlations and covariances.
[AA, Ch3] |
3. Unit 3. Elementary Probability. Probability axioms. Random variables: discrete and continuous. Normal distribution. Joint and marginal distributions.
[AA, Ch 4.1-4.6]. |
4. Unit 4. Central Limit Theorem and Basics of Statistical Inference. Central Limit Theorem. Point Estimation. Confidence intervals. Hypothesis testing.
[AA, Ch 5.1-5.4; Ch 6.1-6.4] |
5. Unit 5. Intro to Linear Regression. Simple linear regression. R2, t-stats, ANOVA, p-values.
[AA, Ch 9.1-9.6] |
Metodología
Lectures: Students are expected to attend all the lectures and participate actively in class.
Problem sets and case study: Students will be expected to hand in solutions to problem sets, and in addition read provided papers for the case study.
Evaluación
Actividades de evaluación
| Descripción |
% |
| Participation |
10 |
| Case study |
10 |
| Homeworks 1 and 2 |
20 |
| Midterm |
20 |
| Final exam |
40 |
Criterios de evaluación
1. Students can only be assessed if they attend the established minimum number of classes, including lectures and practical sessions. As a percentage, the minimum is 50% for students sitting the final exam for the first time and 80% for those re-sitting the exam. If students do not meet this condition, their mark will be recorded as "Absent". These percentages, however, do not include justified absences. Students are required to inform the teacher at least one week before the absence in question, except in cases of force majeure. The only justifiable absences are those attributed to: (i) illness, (ii) the death of a family member or similar, (iii) ESADE activities for which students have received approval to attend from Programme Management.
Unjustified absences include trips, driver's license tests, etc.
2. Students' final marks have to range from 0 to 10, computing the corresponding weight of both final exam and ongoing assessment components. The latter has to be considered regardless of whether students complete the first sitting of the final exam or re-sit it later on.
3. Students have to achieve a minimum mark of 4 on the final exam in order to pass the class. If students fail to achieve the minimum mark on the final exam, they will fail the class. In this case, the mark that has to be recorded in the final registry of marks is the mark on the final exam which has kept the student in question from passing the class.
4. If students pass the ongoing assessment component but fail the final exam after the first second sitting, the teacher may save the ongoing component mark for the following academic year. Students can always choose not to have that mark used the next time they take the class. In this case, students will have to comply with the teacher's instructions regarding the ongoing assessment component for their marks the second time they take the class.
5. If students are required to repeat the class because they did not pass the ongoing assessment component previously, because they chose to not save their old mark despite passing this component or because faculty did not save it for the following year and, in addition, they cannot attend class because they are currently enrolled in the next level class and the two classes scheduled coincide, they will be required to comply with the specific ongoing assessment plan for these types of students as established in Teaching Guide.
-Plagiarism (or submitting material that in part or whole is not entirely one's own work) is strictly prohibited. Action will be taken in instances of plagiarism. Students have to turn in their written assignments via the Moodle platform. I will analyze their work using anti-plagiarism software (such as Turnitin).
This guide is subject to the necessary modifications that may arise due to restrictions derived from the Covid-19 pandemic.
Bibliografía
Main textbook:
Alan Agresti, "Statistical Methods for the Social Sciences", 5th Global edition, Pearson 2018.
Additional/alternative textbook:
David Spiegelhalter, "The Art of Statistics", Pelican, 2019.
Horarios y secciones
| Grupo |
Profesor |
Departamento |
| Year 2 |
Vladimir Manaev |
Economía, Finanzas y Contabilidad |
Horario Year 2
Del 7/9/2022 al 26/10/2022:
Cada miércoles de 16:15 a 18:15. (Excepto: 12/10/2022)
Cada jueves de 14:30 a 16:45. (Excepto: 20/10/2022)
Jueves 13/10/2022 de 16:45 a 17:15.
Del 20/10/2022 al 24/11/2022:
Cada jueves de 14:30 a 16:45.
Del 9/11/2022 al 23/11/2022:
Cada miércoles de 16:15 a 18:15.
Lunes12/12/2022:
De 17:00 a 17:30.
De 14:15 a 17:00.
Viernes 10/2/2023 de 9:15 a 12:30.
