Checking date: 27/04/2017


Course: 2019/2020

Applied Statistics
(16535)
Study: Bachelor in Philosophy, Politics and Economics (283)


Coordinating teacher:

Department assigned to the subject: Department of Statistics

Type: Compulsory
ECTS Credits: 6.0 ECTS

Course:
Semester:




Competences and skills that will be acquired and learning results. Further information on this link
- To analyze univariate and bivariate data - To solve probability problems - To use random variables - To demonstrate an understanding of basic concepts and techniques in estimation - To be able to solve problems in estimation - To be able to solve problems using a statistical software.
Description of contents: programme
PROGRAMME 1. Introduction. 1.1. Concepts and use of Statistics. 1.2. Statistical terms: populations, subpopulations, individuals and samples. 1.3. Types of variables. 2. Analysis of univariate data. 2.1. Representations and graphics of qualitative variables. 2.2. Representations and graphics of quantitative variables. 2.3. Numerical summaries. 3. Analysis of bivariate data. 3.1. Representations and graphics of qualitative and discrete data. 3.2. Representations and numerical summaries of quantitative data: covariance and correlation. 4. Probability and probabilistic models. 4.1. Random experiments, sample space, elemental and composite events. 4.2. Properties of Probability. Conditional Probability and its properties. 4.3. Random variables and their characteristics. 4.4. Discrete probability models: Bernoulli variables and related distributions. 4.5. Continuous probability models: The normal distribution and related distributions. 4.6. Introduction to the bivariate normal distribution. 5. Introduction to Statistical Inference. 5.1. Parameter point estimation. 5.2. Goodness-of-fit to a probability distribution. Graphical methods. 5.3. The sample mean distribution. 5.4. Confidence interval for the mean.
Learning activities and methodology
14 Theoretical support materials available on the Web, and 14 sessions based on problem-solving sessions and practical computing. No group tutorials except during the last week.
Assessment System
  • % end-of-term-examination 60
  • % of continuous assessment (assigments, laboratory, practicals...) 40

The course syllabus and the academic weekly planning may change due academic events or other reasons.