PD:Anàlisi de Dades

Teaching plan for the course unit

General information

Course unit name: Data Analysis

Course unit code: 364552

Academic year: 2025-2026

Coordinator: Vicente Royuela Mora

Department: Department of Econometrics, Statistics and Applied Economics

Credits: 6

Single program: S

More information

Estimated learning time

Total number of hours 150

Face-to-face and/or online activities

	- Lecture with practical component	Face-to-face		45
	- Problem-solving class	Face-to-face		15

Supervised project

Independent learning

Recommendations

Students are recommended to have successfully completed the course in Mathematics before enrolling.

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.
-	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).
-	CG2 - Ability to detect inequalities between people and to design, implement and evaluate policies that facilitate the erradication of discrimination on these grounds on companies and institutions.
-	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 equips students with the statistical knowledge and techniques necessary to address decision-making problems in professional contexts. Specifically, students learn to:

— Identify the types of information that can be analysed using statistical methods.

— Select appropriate statistical techniques for summarising empirical data and support decision-making in business contexts.

— Calculate and correctly interpret the results of descriptive analyses, recognising any possible limitations.

Referring to abilities, skills

— Manage data using frequency tables, select the most appropriate graphical representation in each case, and summarise data using the relevant descriptive statistics.

— Understand and apply basic statistical calculations using appropriate software (Excel, R).

Teaching blocks

1. What is Statistics?

1.1. Aims of statistics

1.2. Descriptive and inferential statistics

1.3. Population and sample

1.4. Data: classification and measurement scales

2. Frequency distributions

2.1. Frequency distributions

2.2. Graphical representations

3. Measures of position

3.1. Mean, median and mode

3.2. Properties of the mean

3.3. Measures of location: quantiles

4. Measures of dispersion and shape

4.1. Dispersion: boxplot

4.2. Variance and standard deviation: properties

4.3. Linear transformation: standardised variable

5. Measures of inequality

5.1. Inequality vs. dispersion

5.2. The Lorenz curve and the Gini index

6. Bivariate data analysis

6.1. Joint frequency distributions; marginal distributions

6.2. Conditional distributions

6.3. Statistical independence

6.4. Association between attributes

7. Association between variables

7.1. Scatterplot

7.2. Linear association: covariance

7.3. Pearson’s correlation coefficient

7.4. Linear regression

8. Time series analysis

8.1. Definition of a time series

8.2. Time series plots

8.3. Trend, cyclical, seasonal and irregular components of a time series

8.4. Aggregation schemes: additive vs. multiplication

8.5. Introduction to forecasting methods

9. Index numbers

9.1. Index numbers: definition, calculation and interpretation

9.2. Unweighted index numbers

9.3. Weighted index numbers: Laspeyres and Paasche

9.4. The consumer price index

Teaching methods and general organization

This subject combines lectures with problem-solving sessions in subgroups, organised as follows:

— Theoretical and practical content (approx. 30 hours): These sessions focus on achieving the general and specific learning objectives of the course.

— Problem-solving and computer sessions (15 hours in total): In these sessions, usually held in the computer room, students work through a series of exercises. They are designed to strengthen problem-solving skills and agility, particularly through the use of IT tools.

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

Official assessment of learning outcomes

Continuous assessment

Continuous assessment is based on the following components:

— Assessed activities completed throughout the course, including two classroom tests announced in advance (20%) and in-class practical sessions (20%).

— A final examination covering all the course syllabus, on a date scheduled by the Academic Board (60%). The exam consists of open-ended questions, covering both theoretical and practical aspects and includes applied exercises.

Students who obtain a mark below 4 out of 10 on this exam receive a grade of Fail. Students must obtain a final grade of 5 out of 10 or more to pass the subject.

Students must attend at least 80% of class activities to be eligible to pass the continuous mode of assessment.

The repeat assessment exam has the same structure as that of the single assessment exam.

Examination-based assessment

Students opting for the single mode of assessment sit a final examination covering the entire syllabus, including practical aspects addressed in computer lab sessions with statistical software, on the date established by the Academic Board. The mark obtained on this examination constitutes the final grade for the subject.

Students formally opt out of the continuous mode of assessment by choosing to sit the final examination under the single mode of evaluation.

Reading and study resources

Check availability in Cercabib

Book

GONICK, L., SMITH, W. The cartoon guide to statistics. New York : HarperCollins, 1993

Catàleg UB

LIND, DA., MARCHAL, G., WATHEN, S.A. Statistical techniques in business & economics. 17th ed. New York, NY : McGraw-Hill/Irwin, 2018

Catàleg UB

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

Catàleg UB

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

Versió en línia (9th ed., 2019)