2024
Data Analysis and Health I
Name: Data Analysis and Health I
Code: MAT13048M
3 ECTS
Duration: 15 weeks/78 hours
Scientific Area:
Mathematics
Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Sustainable Development Goals
Learning Goals
To understand the main concepts of Statistics
Adequate description and adequate data collection for statistical treatment
Organize the data in order to facilitate its reading, characterization and statistical treatment
Carry out statistical analyzes using appropriate statistical techniques
Distinguish the concepts of population and sample, quantitative and qualitative variables, descriptive statistics and inferential statistics
Organize information through charts, graphs and frequency distribution
Calculate descriptive measures of location, dispersion and asymmetry; outliers; the correlation coefficient of Pearson, Spearman and Phi association.
Apply descriptive statistics techniques in the analysis of a set of data and interpret the results.
Use appropriate scientific terminology
Structure information
Adequate description and adequate data collection for statistical treatment
Organize the data in order to facilitate its reading, characterization and statistical treatment
Carry out statistical analyzes using appropriate statistical techniques
Distinguish the concepts of population and sample, quantitative and qualitative variables, descriptive statistics and inferential statistics
Organize information through charts, graphs and frequency distribution
Calculate descriptive measures of location, dispersion and asymmetry; outliers; the correlation coefficient of Pearson, Spearman and Phi association.
Apply descriptive statistics techniques in the analysis of a set of data and interpret the results.
Use appropriate scientific terminology
Structure information
Contents
• Introduction to Biostatistics - fundamental concepts.
• Variable measurement scale
• Organization of information: tables and graphs
• Review of frequency distribution
• Descriptive measures of location, dispersion, asymmetry and flattening
• Outliers: concept and identification
• Pearson and Speraman correlation
• Association Measures (Phi coefficient)
• Introduction to the study of Probabilities: Some probability distributions: Binomial, Poisson, Student t, Chi-square and Normal.
• Introduction to statistical inference: statistical hypothesis, notion of paired and unpaired subjects, levels of significance, type I and type II errors, confidence intervals
• Hypothesis testing and its requirements
• Variable measurement scale
• Organization of information: tables and graphs
• Review of frequency distribution
• Descriptive measures of location, dispersion, asymmetry and flattening
• Outliers: concept and identification
• Pearson and Speraman correlation
• Association Measures (Phi coefficient)
• Introduction to the study of Probabilities: Some probability distributions: Binomial, Poisson, Student t, Chi-square and Normal.
• Introduction to statistical inference: statistical hypothesis, notion of paired and unpaired subjects, levels of significance, type I and type II errors, confidence intervals
• Hypothesis testing and its requirements
Teaching Methods
Theoretical exposition of concepts; Resolution of exercises within the classroom using SPSS, analysis of data with concrete problems in the practical component; Theoretical-practical exam at the end of the semester.
Certificações
