Syllabus Information

5.1. Methodological overview

The methodology followed in this course is oriented towards achievement of the learning objectives. A wide range of teaching and learning tasks are implemented, such as such as lectures, practice sessions, computer practice sessions, and tutorials.

Lectures: The professors will present the main contents of the course and try to motivate participation and discussion in the classroom. Slides will be employed in these sessions to help the students to understand the topics. It is recommended to attend the lectures and make notes to complement and clarify the slides.

Practice sessions: In these sessions, the students will learn how to manage and solve practical problems. Before each practical session, the students will have at their disposal the set of problems that will be solved.

Computer practice sessions: During the semester, the students will do several computer practice sessions. In these sessions, they will solve some problems applying the methods and techniques studied in class by using a spreadsheet. Each practice session will consist of two parts. In the first one, the students will be guided to learn the main theoretical concepts; in the second, these concepts will be employed to solve real problems.

Classroom materials will be available via Moodle. These include a repository of the slides and lecture notes used in class, the course syllabus, as well as other learning resources such as leaning exercises, data files and outlines of the computer practices sessions. Further information regarding the course will be provided on the first day of class

5.2. Learning tasks

The course is worth 6 ECTS implying a workload for the student of 150 hours divided between the classroom and private study hours. This workload is distributed in the following way:

5.3. Syllabus

Lesson 1:   Statistical Methods in Business and Economics

Lesson 2:   Scales of Measurement and Information Sources

Lesson 3:   Describing Univariate Data: Frequency Tables and Distributions, and Graphic Presentation

Lesson 4:   Describing Univariate Data: Numerical Measures

Lesson 5:   Frequency Tables and Distributions and Graphic Presentation of Bivariate Data

Lesson 6:   Correlation and Simple Linear Regression

Lesson 7:   Index Numbers

Lesson 8:   Probability Concepts

Lesson 9:   Statistical Decision Theory

5.4. Course planning and calendar

For further details concerning the timetable, classroom and further information regarding this course please refer to the "Facultad de Economía y Empresa " website (http://econz.unizar.es/)