1. General information
Course:
STATISTICAL INFERENCE
Code:
53315
Type:
CORE COURSE
ECTS credits:
6
Degree:
316 - UNDERGRADUATE DEGREE IN ECONOMICS
Academic year:
2019-20
Center:
5 - FACULTY OF ECONOMICS AND BUSINESS
Group(s):
10
17
Year:
2
Duration:
C2
Main language:
Spanish
Second language:
English
Use of additional languages:
English Friendly:
Y
Web site:
Bilingual:
N
Lecturer:
ESTEBAN ALFARO CORTES
- Group(s):
10
Building/Office
Department
Phone number
Email
Office hours
Facultad de Ciencias Económicas y Empresariales. Despacho 3.14
ECONOMÍA APLICADA I
926053094
esteban.alfaro@uclm.es
Ver página Web de la Facultad y moodle de la asignatura/See Web site of the Faculty and Moodle for the subject
Lecturer:
JOSE LUIS ALFARO NAVARRO
- Group(s):
17
Building/Office
Department
Phone number
Email
Office hours
Facultad de Ciencias Económicas y Empresariales. Despacho 3.14
ECONOMÍA APLICADA I
926053274
joseluis.alfaro@uclm.es
Ver página Web de la Facultad y campus virtual de la
asignatura.
2. Pre-Requisites
|
It is recommended to have coursed the subject on Statistics for Economics |
3. Justification in the curriculum, relation to other subjects and to the profession
|
In the economic field, a basic management of the fundamental techniques for the treatment of quantitative information is essential. This need is translated into a knowledge of the main sources of statistical information, the basic rules for its interpretation and Analysis, and a mastery of the most relevant analytical-quantitative instruments. Therefore, the curriculum, within module 4 "Methods Quantitative for the Economy” devotes a section to the matter of Statistics, structured in two subjects: Statistics for Economics and Statistical Inference. The fundamental mission of the subject Inference Statistics is to deduce properties (make inferences) from a population, from a small part of it (sample). The goodness of these deductions is measured in probabilistic terms, that is, all inference is accompanied by its probability of success. Inferential statistics include: sample theory, estimation of parameters, hypothesis testing, experimental design and Bayesian Inference. |
4. Degree competences achieved in this course
| Course competences | |
|---|---|
| Code | Description |
| E03 | Ability to find economic data and select relevant facts. |
| E06 | Application of profesional criteria to the analysis of problems, based on the use of technical tools. |
| E16 | Identify relevant sources of financial information and its content, as well as the ability to derive the important information from the data, otherwise completely unknown to non-professionals. |
| G01 | Possession of the skills needed for continuous, self-led, independent learning, which will allow students to develop the learning abilities needed to undertake further study with a high degree of independence. |
| G03 | Develop oral and written communication skills in order to prepare reports, research projects and business projects and defend them before any commission or group of professionals (specialised or non-specialised) in more than one language, by collecting relevant evidence and interpreting it appropriately so as to reach conclusions. |
| G04 | Ability for the use and development of information and communication technology in the development of professional activity. |
| G05 | Capacity for teamwork, to lead, direct, plan and supervise multidisciplinary and multicultural teams in both national and international environments. |
5. Objectives or Learning Outcomes
| Course learning outcomes | |
|---|---|
| Description | |
| Enable student for autonomous work and learning, as well as for personal initiative | |
| Train the student to search for information in order to analyze it, interpret is meaning, synthesize it and communicate it to others. | |
| Train the student to work out problems in creative and innovative ways. | |
| Enable students to know the sources of official statistics and their treatment for the analysis of economic reality | |
| To know the tools and methods for quantitative analysis of markets, sectors and companies, including models for decision-making and economic forecasting models. | |
| Additional outcomes | |
| Description | |
6. Units / Contents
-
Unit 1: DISTRIBUTIONS DERIVED FROM THE NORMAL AND THE CENTRAL LIMIT THEOREM
-
Unit 1.1: CONVERGENCE OF SUCCESSIONS OF RANDOM VARIABLES: THEORY OF THE CENTRAL LIMIT
-
Unit 1.2: DISTRIBUTIONS FROM NORMAL
-
-
Unit 2: DISTRIBUTIONS IN SAMPLING
-
Unit 2.1: SAMPLING: STATISTICS AND THEIR DISTRIBUTIONS
-
Unit 2.2: SAMPLING IN NORMAL POPULATIONS
-
-
Unit 3: ESTIMATORS AND THEIR PROPERTIES
-
Unit 3.1: POINT ESTIMATION: CONCEPT AND PROPERTIES OF ESTIMATORS
-
Unit 3.2: METHODS OF POINT ESTIMATION
-
Unit 3.3: CONFIDENCE INTERVALS ESTIMATION
-
-
Unit 4: HYPOTHESES TESTING
-
Unit 4.1: INTRODUCTION TO HYPOTHESES TESTING
-
Unit 4.2: PARAMETRIC HYPOTHESES TESTING
-
Unit 4.3: NON-PARAMETRIC HYPOTHESES TESTING
-
-
Unit 5: ANALYSIS OF THE VARIANCE (ANOVA)
-
Unit 5.1: INTRODUCTION TO ANOVA
-
Unit 5.2: ANALYSIS OF THE ONE-WAY ANOVA
-
Unit 5.3: ANALYSIS OF THE MULTI-FACTOR ANOVA
-
7. Activities, Units/Modules and Methodology
| Training Activity | Methodology | Related Competences (only degrees before RD 822/2021) | ECTS | Hours | As | Com | R | Description * |
| Class Attendance (theory) [ON-SITE] | Lectures | E03 E06 E16 G01 G04 | 1.33 | 33.25 | N | N | N | |
| Class Attendance (practical) [ON-SITE] | Combination of methods | E03 E06 E16 G01 G03 G04 G05 | 0.67 | 16.75 | Y | N | N | |
| Study and Exam Preparation [OFF-SITE] | Self-study | E03 E06 E16 G01 G04 | 2.08 | 52 | Y | N | N | |
| Writing of reports or projects [OFF-SITE] | Group Work | E03 E06 E16 G01 G03 G04 G05 | 0.72 | 18 | Y | N | N | |
| Other off-site activity [OFF-SITE] | Self-study | E16 G01 G03 G04 | 0.8 | 20 | Y | N | N | |
| Progress test [ON-SITE] | Assessment tests | E03 E06 E16 G01 G03 G04 | 0.04 | 1 | Y | N | N | |
| Final test [ON-SITE] | Assessment tests | E03 E06 E16 G01 G03 G04 | 0.08 | 2 | Y | Y | Y | |
| Other on-site activities [ON-SITE] | Combination of methods | E03 E06 E16 G04 | 0.28 | 7 | N | N | N | |
| Total: | 6 | 150 | ||||||
| Total credits of in-class work: 2.4 | Total class time hours: 60 | |||||||
| Total credits of out of class work: 3.6 | Total hours of out of class work: 90 | |||||||
As: Assessable training activity Com: Training activity of compulsory overcoming R: Rescheduling training activity
8. Evaluation criteria and Grading System
| Grading System | |||
| Evaluation System | Face-to-Face | Self-Study Student | Description |
| Assessment of active participation | 5.00% | 0.00% | The active attitude of the student will be assessed in the classroom. |
| Fieldwork assessment | 20.00% | 0.00% | At the beginning of the course working groups will be created and they will develop a project along the course. These projects will be supervised by the teacher and may need to be exposed at the end. |
| Progress Tests | 10.00% | 0.00% | Written choice test with 10 questions. Each question has three alternative answers, one correct and two incorrect. Each correct answer adds 1 point and each failed subtract 0.5, questions left blank unscored. |
| Final test | 65.00% | 0.00% | Written test with some practical questions to be solved |
| Total: | 100.00% | 0.00% | |
Evaluation criteria for the final exam:
In the Final Test, a minimum of four points must be obtained for the rest of the activities to be considered.
Specifications for the resit/retake exam:
You can only recover the qualifications of group work and problem solving (handing it over again according to teacher recommendations) and final test (exam). Qualifications of the other sections will be retained but without possibility of recovery.
Specifications for the second resit / retake exam:
Evaluation criteria not defined
9. Assignments, course calendar and important dates
| Not related to the syllabus/contents | |
|---|---|
| Hours | hours |
| Class Attendance (theory) [PRESENCIAL][Lectures] | 3.25 |
| Class Attendance (practical) [PRESENCIAL][Combination of methods] | 1.75 |
| Progress test [PRESENCIAL][Assessment tests] | 1 |
| Final test [PRESENCIAL][Assessment tests] | 2 |
| Other on-site activities [PRESENCIAL][Combination of methods] | 7 |
| Unit 1 (de 5): DISTRIBUTIONS DERIVED FROM THE NORMAL AND THE CENTRAL LIMIT THEOREM | |
|---|---|
| Activities | Hours |
| Class Attendance (theory) [PRESENCIAL][Lectures] | 5 |
| Class Attendance (practical) [PRESENCIAL][Combination of methods] | 2.5 |
| Study and Exam Preparation [AUTÓNOMA][Self-study] | 8 |
| Other off-site activity [AUTÓNOMA][Self-study] | 3 |
| Unit 2 (de 5): DISTRIBUTIONS IN SAMPLING | |
|---|---|
| Activities | Hours |
| Class Attendance (theory) [PRESENCIAL][Lectures] | 5 |
| Class Attendance (practical) [PRESENCIAL][Combination of methods] | 2.5 |
| Study and Exam Preparation [AUTÓNOMA][Self-study] | 8 |
| Other off-site activity [AUTÓNOMA][Self-study] | 3 |
| Unit 3 (de 5): ESTIMATORS AND THEIR PROPERTIES | |
|---|---|
| Activities | Hours |
| Class Attendance (theory) [PRESENCIAL][Lectures] | 8 |
| Class Attendance (practical) [PRESENCIAL][Combination of methods] | 4 |
| Study and Exam Preparation [AUTÓNOMA][Self-study] | 15 |
| Writing of reports or projects [AUTÓNOMA][Group Work] | 2 |
| Other off-site activity [AUTÓNOMA][Self-study] | 6 |
| Unit 4 (de 5): HYPOTHESES TESTING | |
|---|---|
| Activities | Hours |
| Class Attendance (theory) [PRESENCIAL][Lectures] | 8 |
| Class Attendance (practical) [PRESENCIAL][Combination of methods] | 4 |
| Study and Exam Preparation [AUTÓNOMA][Self-study] | 15 |
| Writing of reports or projects [AUTÓNOMA][Group Work] | 8 |
| Other off-site activity [AUTÓNOMA][Self-study] | 6 |
| Unit 5 (de 5): ANALYSIS OF THE VARIANCE (ANOVA) | |
|---|---|
| Activities | Hours |
| Class Attendance (theory) [PRESENCIAL][Lectures] | 4 |
| Class Attendance (practical) [PRESENCIAL][Combination of methods] | 2 |
| Study and Exam Preparation [AUTÓNOMA][Self-study] | 6 |
| Writing of reports or projects [AUTÓNOMA][Group Work] | 8 |
| Other off-site activity [AUTÓNOMA][Self-study] | 2 |
| Global activity | |
|---|---|
| Activities | hours |
10. Bibliography and Sources
