| Center |
| Faculty of Pharmacy and Food Sciences |
| Departament |
| Statistics and Operational Research |
| Lecturers in charge |
| Sin datos cargados |
| Met. Docent |
| In theoretical sessions the teacher will introduce the concepts and methods of statistics, with examples and exercises to be solved by the students. Statistical software will then be introduced in practical sessions in order to solve similar exercises to those used in the theoretical classes. |
| Met. Avaluació |
| In a written final test the students will be asked to solve some problems and answer some practical questions. |
| Bibliografia |
| 1.- Montgomery, D.C y Runger, G.C. (1996). Probabilidad y Estadística Aplicadas a la Ingeniería. McGraw-Hill. 2.- Devore, J.L. (2001). Probabilidad y Estadística para Ingeniería y Ciencias. Thomson Editores. 3.- Lapin, L.L. (1997). Modern Engineering Statistics. Duxbury Press. 4.- Nelson, P.R., Coffin, M. and Copeland, K.A.F. (2003). Introductory Statistics for Engineering Experimentation. Elsevier. |
| Continguts |
| Theory: 1. Exploratory data analysis Random samples. Graphical techniques. Sample statistics. 2. Modelization of experimental results Mathematical models: constants and parameters. Linear models: minimum squares. Error modelization: discrete and continuous random variables. 3. Inference about a population mean The Central Limit Theorem. Confidence interval for a population mean. Test of hypothesis. Testing normality. Nonparametric test. Inferences about a proportion. 4. Comparison of two populations Paired samples. Independent samples: confidence intervals and test of hypothesis on the difference of the means. Test of homogeneity of variances. Nonparametric tests. 5. Comparison of more than two populations The ANOVA table. Multiple comparisons. Confidence intervals. Nonparametric test. 6. Linear regression and correlation Linear model: test of hypothesis and confidence intervals. Prediction intervals. Residual analysis. Correlation. 7. Statistical process control Statistical process control: control charts. Control charts for the location of the process. Control charts for the variability of the process. Practicals: 1. Statistical software: Files and data handling. 2. Exploratory data analysis. 3. Inferences about one and two populations. 4. Analysis of variance and nonparametric methods. 5. Linear regression and correlation. |
| Objetius |
| The aim of this course is to provide engineering students with the statistical tools they must understand in order to solve the more frequent and easier statistical problems that appear in the practice of engineering properly. The emphasis is put on the statistical tools and their application using statistical software, rather than statistical theory. |
| URL de Fitxa |