Subject: Informatics and data analysis
Scientific Area:
Computer User Skills
Workload:
64 Hours
Number of ECTS:
5 ECTS
Language:
Portuguese
Overall objectives:
1 - Know the most used computer tools in the processing of data and information with emphasis on their functionalities and areas of application;
2 - Specifically to be aware of the main features and potential of Microsoft Word and Microsoft Excel in their multiple functions;
3 - Learn about Web collaboration services that provide environments for remote meetings;
4 - Familiarize students with the concepts inherent to Data Analysis;
5 - Acquire skills in the processing of analytical data;
6 - Choice of work methods and techniques;
7 - Highlight the appropriate statistical techniques to support the decision-making process.
Syllabus:
1 - Web collaboration services: Colibri platforms; Microsoft Teams;
1.1 - Basic concepts of platforms;
1.2 - Create/hold remote meetings; videoconferencing sessions with participants from multiple institutions;
2 - Introduction to Word Processing; Basic Word Processing Tools -Microsoft Word;
2.1 - Insertion of fields, headers, footers, subtitles, markers and indexes;
2.2 - Letters and mailings, macros: automation of tasks and creation of databases for creating mailing lists;
2.3 - Document protection;
2.4 - Information sharing between applications.
3 - Introduction to Spreadsheet;
3.1 - Potentialities, structure and working environment of the Microsoft Excel spreadsheet program;
3.2 - Basic worksheet tasks;
3.3 - Operations with worksheets;
3.4 - Introduction of simple formulas in the spreadsheet;
3.5 - Functions available in Excel;
3.6 - Creating and editing command macros;
3.7 - Elaboration and manipulation of graphics;
3.8 - Creation and manipulation of data lists or tables;
3.9 - Elaboration and manipulation of tables and dynamic graphics;
3.10 - Integration of tables and graphics prepared in the spreadsheet in the word processor.
4 - Sampling and respective characterization: statistics and measures of central tendency and dispersion; Graphic representations;
5 - Decision-making based on observed data: The various hypothesis tests; Definition of hypotheses (example: comparing two methods (or two operators)); Identification of test statistics and their distribution; Definition of the decision rule with specification of the significance level of the test; Calculation of test statistics and decision making; Error types;
6 - Comparison between parameters of more than two populations: Analysis of variance, Underlying assumptions; interpretation of results;
7 - Simple linear regression: Scatter plot and its interpretation. Simple linear regression model. Definition and interpretation of the linear correlation coefficient. Estimation of the value of the dependent variable from a value assumed by the independent variable. Coefficient of determination as a measure of the quality of the regression. Forecast ranges. Calculation of analytical thresholds in methods using linear calibration
Literature/Sources:
Marques, C.P., Costa, N. , 2013 , Fundamental do Word 2013 , FCA
Marques, C.P., Costa, N. , 2013 , Fundamental do Excel 2013 , FCA
Guimarães, R.; Sarsfield Cabral, J.; , 2007 , Estatística , Mc Graw Hill
Reis, E; Andrade, R.;Calapez, T.; Melo, P , 2015 , Estatística Aplicada - Vol. 1, , Edições Sílabo
Brereton, R , 2003 , Chemometrics: Data Analysis for the Laboratory andChemical Plant , John Wiley & Sons,
Assesssment methods and criteria:
Classification Type: Quantitativa (0-20)
Evaluation Methodology:
The aim is to acquire and apply the knowledge provided for the objectives and programmatic contents, through an active and interdisciplinary methodology. The student must understand the basic concepts and know how to relate them to each other, also reinforcing them, through applied learning using the tools available and provided in class. To achieve the objectives and implement the syllabus, the UC's contact hours are scheduled as follows: Theoretical-practical teaching: 64 hours. The assessment will include several moments of assessment applied to the theoretical-practical components, (e.g. frequencies), any of the elements cannot exceed a weight of 50%, the theoretical-practical elements can be recovered in appeal.