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General information |
Course unit name: Statistics
Course unit code: 364565
Academic year: 2025-2026
Coordinator: Maria Carme Riera I Prunera
Department: Department of Econometrics, Statistics and Applied Economics
Credits: 6
Single program: S
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Estimated learning time |
Total number of hours 150 |
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Face-to-face and/or online activities |
60 |
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- Lecture with practical component |
Face-to-face |
45 |
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- Problem-solving class |
Face-to-face |
15 |
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Supervised project |
40 |
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Independent learning |
50 |
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Recommendations |
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Given the content of the subject, it is highly recommended that students have previously passed the subjects Data Analysis and Mathematics. |
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Competences / Learning outcomes to be gained during study |
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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. |
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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). |
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CG8 - Capacity to communicate in English and/or other foreign languages orally and in writing, comprehension skills, and mastery of specialized language. |
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CG1 - Commitment to ethical practice (critical and self-critical skills and attitudes that comply with ethical and deontological principles). |
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CG3 - Capacity for learning and responsibility (capacity for analysis, synthesis, to adopt global perspectove and to apply knowledge in practice). |
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CG10 - Capacity to apply ICTs to professional activities. |
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CE9 - Ability to use quantitative methods to solve real problems in different business areas. |
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Learning objectives |
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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:
Referring to abilities, skills — Acquire the capacity to use statistical inference tools for decision-making in theoretical and real situations.
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Teaching blocks |
1. Probability
1.1. Random experiment and basic grounds of probability
1.2. Conditioned probability and statistical independence
1.3. Bayes’ theorem
2. Distribution models for random variables
2.1. Distribution models for discrete and continuous random variables
2.2. Distributions derived from normal distribution
2.3. Central limit theorem
3. Sampling
3.1. Random sample and sample statistics
3.2. Sampling distributions
4. Point estimation
4.1. Introduction to the estimation process
4.2. Properties of point estimates
4.3. Methods of point estimation
5. Interval estimation
5.1. Definition of confidence intervals
5.2. Confidence intervals for the mean and for the difference between means
5.3. Confidence intervals for the proportion and for the difference between proportions
5.4. Confidence intervals for the variance
5.5. Choosing sample size
6. Hypothesis testing
6.1. Decision rule
6.2. Types of errors; power of a test
6.3. Test hypothesis for the mean and for the difference between means
6.4. Test hypothesis for the variance and for the equality of variances
6.5. Test hypothesis for the proportion and for the difference between proportions
7. Chi-square tests and some non-parametric tests
7.1. Goodness of fit tests
7.2. Association tests
7.3. Runs, ranks and signs tests
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Teaching methods and general organization |
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Given the nature of this subject, meeting the learning objectives requires a significant amount of practical work. The teaching methodology therefore combines theoretical and practical content, with a focus on real-world applications.
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Official assessment of learning outcomes |
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To pass the continuous mode of assessment, students must demonstrate that they have acquired the requisite knowledge and competences by meeting the minimum requirements established for both for the compulsory activities and the final examination (see criteria below). The latter can be sat at any of the official examination sessions.
Examination-based assessment Students who are unable to meet the requirements for continuous assessment and those who opt for this mode of evaluation are required to sit an examination covering the whole of the syllabus (including practical components issues), on the date established for that purpose by the Academic Board. The mark obtained on this examination constitutes the final grade for the subject.
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Reading and study resources |
Check availability in Cercabib
Book
GONICK, Larry; SMITH, Wollcott. The cartoon guide to statistics. New York : HarperCollins, 1993
LIND, Douglas A., MARCHAL, William G., WATHEN, Samuel A. Statistical techniques in business & economics. 16th ed. New York, NY : McGraw-Hill/Irwin, 2018
MOORE, David S., McCABE, George P., CRAIG, Bruce A. Introduction to the practice of statistics. 8th ed. New York, NY : W.H. Freeman, 2014
MOORE, David S., NOTZ, William I., FLIGNER, Michael A. The basic practice of statistics. 6th ed. New York : W.H. Freeman and Co., 2013
NEWBOLD, P., CARLSON, W., THORNE, B.M. Statistics for business and economics. 8th ed. Harlow, Essex : Pearson Education, 2013