Universitat Internacional de Catalunya
Biostatistics (Cross-Disciplinary. Research.)
Biostatistics (Cross-Disciplinary. Research.)
1
12706
1
Annual
OB
Main language of instruction: Spanish
Other languages of instruction: Catalan, English
If the student is enrolled for the English track then classes for that subject will be taught in the same language.
Other languages of instruction: Catalan, English
If the student is enrolled for the English track then classes for that subject will be taught in the same language.
Teaching staff
Introduction
Biostatistics is a fundamental discipline underpinning Health Sciences. This knowledge is required in order to conduct research and critically appraise scientific literature. It validates research and is crucial to both its understanding and use.
Pre-course requirements
Basic knowledge of mathematics.
Objectives
To know the basic statistical concepts and their applications in the Health Sciences.
To train students to perform basic statistical analysis using statistical software.
To train students in critical reading of scientific articles.
Competences/Learning outcomes of the degree programme
- CB6 - Students should have and understand knowledge that provides the basis for or opportunity to be original in terms of the development and application of ideas, often within a research context.
- CB7 - Students should know how to apply the knowledge they have acquired and be able to resolve problems in new or little known environments within a broader (or multidiciplinary) context, related to their area of study.
- CB8 - Students should be able to incorporate knowledge and tackle the complexity of making judgements based on information which, being incomplete or limited, includes reflections on the social and ethical responsibility linked to the application of their knowledge and judgement
- CB9 - Students should know how to express their conclusions, and the knowledge and reasoning these are based on, to specialised and non-specialised audiences in a clear and unambiguous way.
- CE1 - Students should be able to undertake a proper analysis and an extraoral diagnosis, and underline the aesthetic and functional aspects of the teeth and the soft areas of the lower part of the face as well as a analysis and clinical and lab-based diagnosis, using diagnostic and therapeutic wax models, in order to rehabilitate dental occlusion with good functional and aesthetic balance, while taking into account multidisciplinary factors related to the masticating apparatus.
- CE10 - Students should acquire the ability to apply scientific methods, and apply the knowledge acquired to resolving problems in a scientific field. They should learn how to develop research projects both in vitro and in vivo, within the fields of mechanics, biology and microbiology applied to prosthetic and restorative dentistry and dental implants.
- CE11 - Students should be autonomous in terms of developing and applying new technologies to aesthetic restorative dentistry and searching for new scientific information, as well as acquiring the ability to evaluate and undertake the research and development projects the industry offers in an ethical way, and manage the financial and human resources, as well as be aware of the strategic basis for the transfer of new knowledge to the industry.
- CE2 - Students should be able to work as a clinical professional and/or researcher in the field of aesthetic restorative dentistry, and act as a real specialist or expert in the material; as well as know how to diagnose, treat, prevent and research oral disorders and have updated knowledge of the diagnostic and treatment-related advances which continue to arise throughout their professional life.
- CE4 - To acquire the ability to make oral preparations on mucosa, teeth, and dental implants, to build dental prostheses in patients with advanced oral and multidisciplinary disorders; as well as identify and undertake the procedures and various checks for the prosthetic components during construction.
- CE5 - To be able to give public presentations on your own clinical cases based on the scientific literature, and correctly use the scientific terminology related to temporomandibular dysfunction and aesthetic restorative dentistry.
- CE6 - To acquire the ability to make scientific informed opinions so as to choose the type of material a dental prosthesis is built of in order to fit the patient with it, as well as know how to continuously update your knowledge of the dental biomaterial used in the field of aesthetic restorative dentistry, know how to manipulate it, and about its properties, indications, biocompatibilities, toxicity and environmental impact.
- CE7 - To be able to search for, organise and analyse, from a critical point of view, and using biomedical sources of information, scientific literature on issues related to temporomandibular dysfunction and aesthetic restorative dentistry, in order to pursue continuing education in a self-directed and autonomous way.
- CE8 - To know how to apply epistemological, ethical, legislational and humanitarian factors to research and the disclosure of scientific data in the field of aesthetic restorative dentistry.
- CE9 - To recognise and interpret images and specialised diagnostic techniques that are significant in research, as well as know how to apply bioinformatic tools and new technologies to the fields of prosthetic and restorative dentistry and dental implants.
- CG2 - To be autonomous in terms of obtaining a patient's anamnesis and oral explorations in patients with pathologies that might be either advanced or multidisciplinary in nature; and fill in their medical record and other clinical paperwork using scientific language and terminology that is suited to an aesthetic restorative dentistry professional.
- CG4 - To know how to apply protocols for the use of the equipment in the dental laboratory-workshop to the point of undertaking the necessary procedures that help in oral rehabilitation or the treatments common to a restorative dentist.
Learning outcomes of the subject
It is expected that students acquire the following learning outcomes:
•Understand the basic concepts of descriptive statistics. Knowing how to apply these appropriately according to the type of variable.
•Understand the concepts of probability and probability distribution
•Understand the concept of hypothesis testing, random and systematic error and statistical significance.
•Learn proper use basic hypothesis tests.
•Know how to interpret, both statistically and clinically, the results obtained in both descriptive and inferential statistics.
•Acquire skills for database management and statistical software to analyze data.
•Know how to present the numerical results in the context of an article and / or research project.
•Know how to perform a critical reading of the statistical results presented in scientific literature as original articles, review, ....
Syllabus
- Introduction to Statistics. Definition. Concepts. Biostatistics and in the Health Sciences.
- Sampling. Observational vs. Experimental data. Theory of sampling.
- Descriptive Statistics. Definition. Frequency distributions. Graphical reporting. Measures of Statistics.
- Statistical Inference and the Normal distribution. Definition. Probability distributions. Properties of the Normal distribution. The Standard Normal distribution. Area under the curve. The Central Limit Theorem.
- Using Normal Distributions. Tests for Normality. Proportions. Mean. Confidence intervals. Sample size.
- Hypothesis testing. Definition. Concepts involved. Examples. Technique. Overview of tests. The Student’s t-distribution. Importance in hypothesis testing. Use of tables. Non-parametric tests.
- Comparing two populations (I). Introduction. Types of comparison tests. Equal variance. Student’s t-test. Welch’s Unequal variance t-test. Paired Student’s t-test. Proportions test.
- Comparing two populations (II). Mechanism of comparison. Sample size when comparing. The χ2 distribution. McNemar test.
- Relationship. Definition. Relationship between two continuous variables. Relationship between two dichotomous variables.
- Advanced techniques. Logistic regression, ANOVA and non-parametric statistics.
Teaching and learning activities
In person
Each two-hour session will consist of:
- One hour of explanation of theoretical concepts.
- One hour of practical application of the theoretical concepts.
Evaluation systems and criteria
In person
100% continuous assessment: online tests and practical exercises to be delivered on a weekly basis.
Bibliography and resources
Martínez-González MA, Sánchez-Villegas A, Faulín Fajardo FJ. Bioestadística amigable (2ª ED). Díaz de Santos. Madrid; 2006.