Take advantage of this unique opportunity and acquire new Multivariate skills quickly and in a 100% online modality"

One of the main advantages of mastering multivariate analysis is the ability to identify patterns and trends in the data. By analyzing multiple variables at the same time, engineering professionals can identify complex relationships between them, leading to a deeper understanding of the problem at hand.

For this reason, TECH has designed a Postgraduate certificate in Multivariate I to provide students with the necessary skills and competencies to be able to perform their work as specialists with the highest possible efficiency and quality. Thus, throughout this program, aspects such as Cluster Characterization, Statistical Software Modeling or Factor Analysis, among others, will be addressed.

All this, through a convenient 100% online modality that allows students to organize their schedules and studies, combining them with their other day-to-day work and interests. In addition, this degree has the most complete theoretical and practical materials on the market, which facilitates the student's study process and allows them to achieve their objectives quickly and accurately.

Become the expert in Multivariate Statistical Techniques that you have always wanted to be, in only 6 weeks and with total freedom of organization"

This Postgraduate certificate in Multivariate I contains the most complete and up-to-date program on the market. The most important features include:

• The development of case studies presented by experts in Multivariate I
• The graphic, schematic and eminently practical contents of the book provide sporting and practical information on those 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

Achieve professional success in one of the most promising areas of Engineering, thanks to TECH and the most innovative teaching materials"

The program’s teaching staff includes professionals from 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.

Access all the content on Factor Analysis and Modeling in Statistical Software from any device with an internet connection, whether it is a tablet, cell phone or computer"

Get an in-depth understanding of the essential aspects of Correspondence Analysis and Discriminant Analysis, from the comfort of your own home, 24 hours a day"

The content and structure of this program have been designed by the renowned professionals that make up TECH's team of experts in this area of engineering. These specialists have used their extensive experience and state-of-the-art knowledge to create practical and completely up-to-date content. All this, based on the most efficient pedagogical methodology, TECH Relearning.

Acquire advanced knowledge on Computational Statistics, thanks to the most innovative teaching materials and a wide variety of additional content available on the Online Campus"

Module 1. Multivariate Statistical Techniques I

1.1. Factor Analysis

1.1.1. Introduction
1.1.2. Fundamentals of Factor Analysis
1.1.3. Factor Analysis
1.1.4. Factor Rotation Methods and Factor Analysis Interpretation

1.2. Factor Analysis Modeling

1.2.1. Examples:
1.2.2. Statistical Software Modeling

1.3. Main Component Analysis

1.3.1. Introduction
1.3.2. Main Component Analysis
1.3.3. Systematic Principal Component Analysis

1.4. Principal Component Analysis Modeling

1.4.1. Examples:
1.4.2. Statistical Software Modeling

1.5.  Correspondence Analysis

1.5.1. Introduction
1.5.2. Independence Test
1.5.3. Row and Column Profiles
1.5.4. Inertia Analysis of a Point Cloud
1.5.5. Multiple Correspondence Analysis

1.6. Correspondence Analysis Modeling

1.6.1. Examples:
1.6.2. Statistical Software Modeling

1.7. Discriminant Analysis

1.7.1. Introduction
1.7.2. Decision Rules for Two Groups
1.7.3. Classification over Several Populations
1.7.4. Fisher's Canonical Discriminant Analysis
1.7.5. Selecting Variables: Forward and Backward Procedure
1.7.6. Systematic Discriminant Analysis

1.8. Discriminant Analysis Modeling

1.8.1. Examples:
1.8.2. Statistical Software Modeling

1.9. Cluster Analysis

1.9.1. Introduction
1.9.2. Distance and Similarity Measures
1.9.3. Hierarchical Classification Algorithms
1.9.4. Non-Hierarchical Classification Algorithms
1.9.5. Procedures to Determine the Appropriate Number of Clusters
1.9.6. Characterization of Clusters
1.9.7. Systematic Cluster Analysis

1.10. Cluster Analysis Modeling

1.10.1. Examples:
1.10.2. Statistical Software Modeling

Thanks to TECH Relearning you will be able to acquire new knowledge in a precise and natural way, without spending too much time studying"