Introduction to the Program

Get up-to-date on statistics applied to nutrition research with R and streamline your processes within the ongoing scientific project” 

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Within the framework of nutritional research, statistics play an important role, since the professionals tabulate the information and, in a detailed way, obtain the results of the tests performed. This process is essential for data collection and subsequent dissemination of the same within the work team, so that thanks to this technique, results can be achieved more quickly and efficiently.

To this extent, it is necessary that the nutrition professional delves into the latest knowledge of statistical processes, since they will be of vital importance in their research. This will make it easier to handle the enormous amount of information obtained from samples and experiments. And it is in this context that this program arises, which aims to provide an up-to-date view of the technique of R and to show recent advances in the field of Statistics.

Throughout the course, students will learn the main concepts of Biostatistics and the characteristics of the R program. Likewise, they will make an exhaustive approach to the regression method and multivariate analysis with R, describing also the statistical techniques of Data Mining.

This is a 100% online program, with no on-site classes or transfers to physical centers, so nutritionists only need to have a device with an Internet connection. This will allow them to accommodate their work routine with their personal commitments and the development of the Postgraduate certificate.

Do you want to learn more about Biostatistics with R? Enroll in this Postgraduate certificate and identify the latest updates that will help you in your nutritional research”

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: 

  • The development of case studies presented by experts in Biostatistics. with R
  • 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
  • Content that is accessible from any fixed or portable device with an Internet connection

A program designed to your needs with which you can update your research strategies to advance faster in your project”

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

The 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 immersive education programmed to learn in real situations.

This program is designed around Problem-Based Learning, whereby the professional must try to solve the different professional practice situations that arise during the academic year For this purpose, the student will be assisted by an innovative interactive video system created by renowned and experienced experts.

You will master Multivariate Analysis with R and its multivariate data descriptions"

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This qualification will meet your immediate needs, allowing you to handle advanced statistical techniques of 'Data Mining' with R"

Syllabus

In its commitment to academic excellence, TECH, in close collaboration with the teaching team, has designed for this program an academic syllabus enriched with audiovisual and graphic material, practical exercises and complementary readings. In this way, nutrition professionals will obtain the best resources in order to advance more quickly in their research. In short, everything the nutritionist needs to get up to date in Statistics and R in scientific research with the best guarantees and under a comfortable online modality. 

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Access the Virtual Campus and learn more about the best techniques for your nutritional research through interactive diagrams, videos or case studies”

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) 

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Tree-based methods, descriptive analysis, clustering... everything you need to know about the statistical techniques of Data Mining with R can be found in this course"

Postgraduate Certificate in Biostatistics with R

Biostatistics is an essential discipline in the health sciences that enables professionals to analyze and understand data related to medical research and clinical studies. In today's information age, the management of advanced tools has become crucial to obtain accurate and meaningful results. The Postgraduate Certificate in Biostatistics with R created by TECH Global University is the answer to this need, providing students with the skills and knowledge to analyze data accurately using the R programming language. The contents of the program, which is 100% online, range from the basics of descriptive statistics to regression analysis and experimental design in the field of health sciences. Students will develop skills in data visualization, interpretation of results and evidence-based informed decision making. Through case studies, students will address common problems and challenges in biostatistics and learn how to solve them efficiently using R.

Learn about biostatistics with R

R is an open source software tool widely used in statistics and scientific research, due to its versatility and advanced analysis capabilities. In this program, taught in online mode, participants will learn how to apply fundamental statistical concepts in the context of biostatistics, and use R to perform complex data analysis efficiently. Professionals who master biostatistics with R excel in the scientific community and in the healthcare industry. They can analyze large data sets, identify patterns or trends, and effectively communicate results to other professionals and stakeholders. In summary, this Postgraduate Certificate provides participants with solid training in statistics applied to the health sciences, while training them to use R as a powerful tool for data analysis.