Statistics

Index

General Information

Estimated learning time

Recommendations

Competences / Learning outcomes

Learning objectives

Teaching blocks

Teaching methods and general organization

Official assessment of learning outcomes

Reading and study resources

General Information

Course unit nameStatistics
Course unit code364565
Academic year2024/2025
CoordinatorMaria Carme Riera I Prunera
DepartmentDepartment of Econometrics, Statistics and Applied Economics
Credits6
Single programS

Estimated learning time

Total number of hours : 150 Hours
ActivitiesType of trainingHoursObservations
Face-to-face and/or online activities60
- Lecture with practical component Face-to-face 45
- Problem-solving class Face-to-face 15
Supervised project40
Independent learning50

Recommendations

Given the content of the subject, it is highly recommended that students have previously passed the subjects Data Analysis and Mathematics.

Competences / Learning outcomes to be gained during study

  • CB3 - Ability to gather and interpret relevant data (usually within the field of study) to inform judgements that include reflection on relevant social, scientific or ethical issues.
  • CG5 - Ability to work in a team (capacity to collaborate with others and contribute to a common project, capacity to work in cross-disciplinary and multicultural teams).
  • CG8 - Capacity to communicate in English and/or other foreign languages orally and in writing, comprehension skills, and mastery of specialized language.
  • CG1 - Commitment to ethical practice (critical and self-critical skills and attitudes that comply with ethical and deontological principles).
  • CG3 - Capacity for learning and responsibility (capacity for analysis, synthesis, to adopt global perspectove and to apply knowledge in practice).
  • CG10 - Capacity to apply ICTs to professional activities.
  • CE9 - Ability to use quantitative methods to solve real problems in different business areas.

Learning objectives

Referring to knowledge

The course provides an introduction to statistical inference techniques, which aid the decision-making processes in professional business environments. After completing the course, students should be able to:

— Describe why sampling is important and explain the difference between descriptive and inferential statistics.

— Distinguish between a point estimate and a confidence interval estimate and create confidence interval estimates for different parameters.

— Identify the estimators’ properties.

— Understand hypothesis-testing methodologies with the aim of verifying the coherence of a previous statement regarding the behaviour of a population based on available sample information.

Referring to abilities, skills

— Acquire the capacity to use statistical inference tools for decision-making in theoretical and real situations.

— Apply the knowledge obtained in class to solve real-life problems.

— Acquire the knowledge and understanding of basic statistical calculations and the appropriate tools.

Learning objectives

Referring to knowledge

The course provides an introduction to statistical inference techniques, which aid the decision-making processes in professional business environments. After completing the course, students should be able to:

— Describe why sampling is important and explain the difference between descriptive and inferential statistics.

— Distinguish between a point estimate and a confidence interval estimate and create confidence interval estimates for different parameters.

— Identify the estimators’ properties.

— Understand hypothesis-testing methodologies with the aim of verifying the coherence of a previous statement regarding the behaviour of a population based on available sample information.

Referring to abilities, skills

— Acquire the capacity to use statistical inference tools for decision-making in theoretical and real situations.

— Apply the knowledge obtained in class to solve real-life problems.

— Acquire the knowledge and understanding of basic statistical calculations and the appropriate tools.

Teaching blocks

  • 1 Probability

  • 2 Distribution models for random variables

  • 3 Sampling

  • 4 Point estimation

  • 5 Interval estimation

  • 6 Hypothesis testing

  • 7 Chi-square tests and some non-parametric tests

Teaching methods and general organization

Taking into account the fact that the subject is devoted to very practical aspects, the learning objectives require a considerable amount of practical work; thus, the teaching methodology combines theoretical and practical concepts focusing on their applicability. 

This subject combines lectures and problem-solving sessions, which are organised as follows:

— Two 2-hour lectures per week. The lecturer presents the theoretical and practical content students need in order to achieve the general and specific objectives.

— Part of those lectures will be devoted to problem solving after the theoretical explanation. Students will be able to work through exercises in small groups. The sessions are designed to develop students’ problem-solving skills and speed.

The Virtual Campus is intended to facilitate communication between students and the teaching staff. All administrative and academic information for this subject is published on the Virtual Campus: the course plan, a schedule of activities, the list of exercises for problem-solving sessions, and a list of additional exercises with model solutions.

The main activities completed during the course consist of the following:

— Face-to-face learning activities: carried out in the classroom with the lecturer. They comprise theoretical activities and theoretical activities with a practical component.

The total number of hours for these activities is 60. To facilitate the completion of these activities, students will have access to the theoretical and practical material used by the lecturers to explain each topic via the Virtual Campus starting from the week before the course starts.


— Independent learning activities: they include problem-solving exercises. Students are expected to hand in a series of 10 exercises applying the theoretical knowledge acquired at the end of each unit. The total number of hours devoted to these activities is 50.


— Tutored/directed activities: activities devoted to the discussion of problems, solving doubts and monitoring independent work from students. The total number of hours devoted to these activities is 40.

These activities are designed to contribute to achieving the competences that are necessary to interpret economic, business and sociological information, among other, critically analyse statistical information, and get to know the different tools available to do so.
Besides, independent learning develops the students’ ability to use ICTs, which is essential for their career development.

Official assessment of learning outcomes

To pass the continuous assessment, students must demonstrate that they have acquired general knowledge by achieving the minimum requirements for the compulsory activities and the final examination, which can be taken in any of the official examination sessions, according to the criteria described below.

Students are entitled to choose single assessment up to the last day of class. There is no need for them to inform the teacher about it.


Continuous assessment consists of two parts:

— A series of assessed activities throughout the course, including 4 scheduled classroom tests (30%) and 10 regular exercises (10%).

Students who obtain a mark below 3.5 out of 10 in continuous assessment are automatically entered for single assessment.

— A final examination covering all course content on the date established by the Academic Council (60%).

All activities must be properly completed on the scheduled date and place. All of the assessed activities completed during the course (continuous assessment activities and final examination) are marked out of 10. Students pass this subject if they achieve a final grade of at least 5 out of 10. Nevertheless, students who do not achieve a mark of 3.5 out of 10 in the final examination are not eligible for continuous assessment and are awarded the mark of the final examination as the final grade for the subject.

Students must obtain a final grade of 5 out of 10 or higher to pass the subject.

 

Examination-based assessment

Students who are unable to meet the requirements for continuous assessment and students who request single assessment must sit an examination covering all the course contents (also considering practical issues), on the date established by the Academic Council. The mark obtained in the examination is the final grade for the subject.

The written examination assesses both the theoretical and practical aspects of the course. Students must demonstrate the knowledge, skills and competences acquired during the course.

To pass the subject, students must:
a) Submit a written request indicating that they wish to waive their right to continuous assessment. The deadline for requests is the day of the final examination.
b) Obtain a minimum pass mark of 5 out of 10 in the final examination in one of the official examination periods.

 

Repeat assessment

Students who do not pass the continuous or single assessment are entitled to repeat assessment, which consists of a final examination on the subject contents, skills and competences set out in this course plan.

To pass the repeat assessment, students must obtain a minimum pass mark of 5 out of 10.

In order to complete the assessment of the subject, students must demonstrate that they have achieved the objectives of the course through a single examination worth 100% of the final grade. This examination will take place during the official examination period set by the Academic Council.

Reading and study resources

Book

GONICK, Larry;  SMITH, Wollcott. The cartoon guide to statistics. New York : HarperCollins, 1993

Book

LIND, Douglas A.,  MARCHAL, William G., WATHEN, Samuel A. Statistical techniques in business & economics. 16th ed. New York, NY : McGraw-Hill/Irwin, 2018

Comment:

Book

MOORE, David S., McCABE, George P., CRAIG, Bruce A. Introduction to the practice of statistics. 8th ed. New York, NY : W.H. Freeman, 2014

Comment:

Book

MOORE, David S., NOTZ, William I., FLIGNER, Michael A. The basic practice of statistics. 6th ed. New York : W.H. Freeman and Co., 2013

Comment:

Book

NEWBOLD, P., CARLSON, W., THORNE, B.M. Statistics for business and economics. 8th ed. Harlow, Essex : Pearson Education, 2013

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