With the study of this Postgraduate certificate you will deepen in just 150 hours in statistics applied to biomedical research with R to perfect your professional skills”

Statistics can provide a glimpse of the obstacles that arise during the development of research. It does this through data and the prevention of avoidable problems. This tool allows, in the first instance, to establish the type of sampling, the sample size and the type of data collection, among other advantages. In this way, the information would be preserved and would provide full details to specialists who wanted to further investigate on a study basis.

This Postgraduate certificate in Biostatistics with R is designed for graduates in Pharmacy and other Health Sciences who wish to deepen their knowledge in the study of statistical data. To achieve this, this degree explores the statistical techniques of Data Mining with R and its application in the pharmaceutical industry, among other issues. In addition, TECH has an experienced teaching team in the area that has reliable knowledge to transmit all the contents of the subject. All this, in order to expand and update the research knowledge of healthcare professionals, through strategic tools.

This is a university degree taught in a 100% online format, which allows students to comprehensively delve into trends and new theories of regression methods with R. All this, thanks to theoretical-practical and additional materials that can be downloaded so that students can have the reference guide, even offline, once it has been stored on their electronic device. In addition, the innovative pedagogical system, based on the Relearning methodology, relieves specialists of long hours of memorization and allows them to adapt the pace of study according to their personal and professional needs.

Do you wish to improve your professional skills in order to apply them to your pharmacological research project? Now you can get it thanks to TECH and its 100% online degree”

This Postgraduate certificate in Biostatistics with R contains the most complete and up-to-date scientific program on the market. The most important features include:

• Development of case studies presented by experts in Medical Research
• The graphic, schematic, and practical contents with which they are created, provide scientific and practical information on the disciplines that are essential for professional practice
• Practical exercises where self-assessment can be used to improve learning
• Its special emphasis on innovative methodologies
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments
• The availability of access to content from any fixed or portable device with an Internet connection

By taking this program you will not have to do without other areas of your life TECH adapts to you and your needs with a 100% online degree suitable for an active working life”

The program’s teaching staff includes professionals from the sector who contribute their work experience to this educational program, as well as renowned specialists from leading societies and prestigious universities.

Its multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide an immersive education programmed to learn in real situations.

The design of this program focuses on Problem-Based Learning, by means of which the professional must try to solve the different professional practice situations that are presented throughout the academic course. For this purpose, the student will be assisted by an innovative interactive video system created by renowned experts.

Apply multivariate analysis and new scientific methods associated with Statistics to drive the development of your own and your collaborating trials"

Delve into the R program and regression methods and become part of the group of experts at the forefront of pharmacological research"

The materials contained in this Postgraduate certificate have been enriched with the guidelines of the specialists to offer the best professional guarantee for the instruction of the students. In addition, the Relearning methodology has been applied, so that Pharmacy graduates do not invest long hours of memorization and can easily assimilate the contents. In this way, the program will teach students about the intricacies of Statistics and R in Health Research. In this sense, TECH aims to enlighten the professionals of the sector, with a practical character, towards the scenarios in which they will develop or are already developing as specialists.

Learn about the most common statistical techniques in Pharmacological Research and enjoy all the contents that make this degree program dynamic so that you can get the most out of it”

Module 1. Statistics and R in Health Research

1.1. Biostatistics

1.1.1. Introduction to The Scientific Method
1.1.2. Population and Sample. Sampling Measures of Centralization
1.1.3. Discrete Distributions and Continuous Distributions
1.1.4. General Outline of Statistical Inference. Inference about a Normal Population Mean. Inference about a General Population Mean
1.1.5. Introduction to Nonparametric Inference

1.2. Introduction to R

1.2.1. Basic Features of the Program
1.2.2. Main Object Types
1.2.3. Simple Examples of Simulation and Statistical Inference
1.2.4. Graphs
1.2.5. Introduction to R Programming

1.3. Regression Methods with R

1.3.1. Regression Models
1.3.2. Variable Selection
1.3.3. Model Diagnosis
1.3.4. Treatment of Outliers
1.3.5. Regression Analysis

1.4. Multivariate Analysis with R

1.4.1. Description of Multivariate Data
1.4.2. Multivariate Distributions
1.4.3. Dimension Reduction
1.4.4. Unsupervised Classification: Cluster Analysis
1.4.5. Supervised Classification: Discriminant Analysis

1.5. Regression Methods for Research with R

1.5.1. Generalized Linear Models (GLM): Poisson Regression and Negative Binomial Regression
1.5.2. Generalized Linear Models (GLM): Logistic and Binomial Regressions
1.5.3. Poisson and Negative Binomial Regression Inflated by Zeros
1.5.4. Local Fits and Generalized Additive Models (GAMs)
1.5.5. Generalized Mixed Models (GLMM) and Generalized Additive Mixed Models (GAMM)

1.6. Statistics Applied to Biomedical Research with R I

1.6.1. Basic Notions of R. Variables and Objects in R. Data handling. Files Graphs
1.6.2. Descriptive Statistics and Probability Functions
1.6.3. Programming and Functions in R
1.6.4. Contingency Table Analysis
1.6.5. Basic Inference with Continuous Variables

1.7. Statistics Applied to Biomedical Research with R II

1.7.1. Analysis of Variance
1.7.2. Correlation Analysis
1.7.3. Simple Linear Regression
1.7.4. Multiple Linear Regression
1.7.5. Logistic Regression

1.8. Statistics Applied to Biomedical Research with R III

1.8.1. Confounding Variables and Interactions
1.8.2. Construction of a Logistic Regression Model
1.8.3. Survival Analysis
1.8.4. Cox Regression
1.8.5. Predictive Models. ROC Curve Analysis

1.9. Statistical Data Mining Techniques with R I

1.9.1. Introduction. Data Mining. Supervised and Unsupervised Learning. Predictive Models Classification and Regression
1.9.2. Descriptive Analysis Data Pre-Processing
1.9.3. Principal Component Analysis (PCA)
1.9.4. Cluster Analysis. Hierarchical Methods. K-Means

1.10. Statistical Data Mining Techniques with R II

1.10.1. Model Evaluation Measures. Predictive Ability Measures. ROC Curves
1.10.2. Models Assessment Techniques. Cross-Validation. Bootstrap Samples
1.10.3. Tree-Based Methods (CART)
1.10.4. Support Vector Machines (SVM)
1.10.5. Random Forest (RF) and Neural Networks (NN)

A degree designed for professionals like you, who want to improve the quality of their work and, therefore, the quality of their scientific results”