Improve your skills on Segmentation and Survey Processing Techniques, thanks to the best online university in the world according to Forbes, thanks to TECH”

Segmentation and Survey Processing Techniques are important to engineers because they enable them to perform accurate and reliable quantitative and qualitative analyses. With these techniques, it is possible to assess the responses of survey participants and perform a detailed analysis of the data collected, which facilitates the identification of patterns, trends and significant relationships between different variables, to provide valuable information for decision making and strategic planning.

For this reason, TECH has designed a Postgraduate certificate in Segmentation and Survey Processing Techniques with which it seeks to provide students with the skills and competencies necessary to perform their work as specialists, with the highest possible efficiency and quality. Therefore, throughout this program, aspects such as Multidimensional Scaling, Shopping Cart Analysis, Automatic Interaction Detection Methods and the Chaid Algorithm will be addressed.

All this, thanks to a convenient 100% online format that allows students to organize their schedules and studies, combining them with their other day-to-day work and interests. In addition, this qualification 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 an expert in Multidimensional Scaling and Questionnaire Reliability in just a few weeks and with total freedom to organize your schedule and studies”

This Postgraduate certificate in Segmentation and Survey Processing Techniques 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 Segmentation and Survey Processing Techniques
• The graphic, schematic and eminently practical contents with which it is conceived provide sporting and practical information on those disciplines that are essential for professional practice
• Practical exercises where the self-assessment process can be carried out 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

Access all the content on Segmentation from your Tablet, cell phone or computer 24 hours a day”

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.

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.

Address Discrete Choice Models and Multidimensional Preference, from the comfort of your home and at any time of the day"

Boost your profile in one of the areas with the greatest future in the field of Engineering, thanks to TECH, the largest digital university in the world"

All the contents and structure of this syllabus have been designed by the renowned professionals that conform TECH's team of experts in this area of Engineering. These specialists have used their extensive experience and their most advanced knowledge to create practical and completely up-to-date contents. All this based on the most efficient teaching methodology, Relearning of TECH Global University.

Expand your knowledge of Segmentation and Survey Processing Techniques, thanks to the most innovative teaching materials and a wide variety of additional content available on the Virtual Campus”

Module 1. Segmentation and Survey Processing Techniques

1.1. Sample Survey

1.1.1. Objective of a Sample Survey. Most Common Data Collection Methods. Sources of Error in Surveys
1.1.2. Sample Selection: Sampling and Size. Secondary Sources
1.1.3. Official Surveys: National Institute of Statistics
1.1.4. Some Official Surveys: National Health Survey, European Health Survey

1.2. Validity and Reliability of Questionnaires

1.2.1. Factorial Validity
1.2.2. Internal Consistency: Cronbach's Alpha

1.3. Statistical Analysis of Data from Two-Dimensional Contingency Tables

1.3.1. Possible Analyses on a Two-Dimensional Contingency Table
1.3.2. The Logic of Log-Linear Analysis: Decomposition of a Two-Dimensional Contingency Table Basic Elements of the Logarithmic-linear analysis. Effects and Parameters
1.3.3. Calculation and Interpretation of Parameters
1.3.4. Logarithmic-Linear Models for a 2-Way Table
1.3.5. Hierarchical Models. Relationship Between Independence Hypotheses and Hierarchical Log-linear Models. Contrasts for the Significance of Parameters
1.3.6. Contrasts for Significance of Effects. Contrasts for the Goodness-of-Fit of a Model

1.4. Study of a Contingency Table by Means of Correspondence Analysis

1.4.1. Profiles and Chi-Square Distance
1.4.2. Inertia Absorption
1.4.3. Representation Quality
1.4.4. Element Contribution to the Factor
1.4.5. Contribution of the Factor to the Element. Principle of Distributional Equivalence

1.5. Segmentation Analysis: CHAID Algorithm

1.5.1. Automatic Interaction Detection Methods
1.5.2. CHAID Algorithm: Stages of the Process, Types of Predictors, Methods of Stopping the Algorithm
1.5.3. Behavior of CHAID in the Presence of Simpson's Paradox

1.6. Statistical Analysis of Data from Three-Dimensional Contingency Tables

1.6.1. Concepts of Association and Interaction. Simpson's Paradox
1.6.2. Components that Influence the Magnitude of Frequencies in a Three-Dimensional Contingency Table

1.6.2.1. Complete Independence
1.6.2.2. Multiple Independence and Conditional Independence
1.6.2.3. Saturated Model for a Three-Way Table

1.6.3. Log-Linear Hierarchical Linear Models for a Three-Way Table

1.6.3.1. Degrees of Freedom of the Models
1.6.3.2. Relationship Between Independence Hypotheses and Hierarchical Log-linear Models

1.6.4. Evaluation of the Models. Significance Test for the Goodness-of-Fit of a Model. Significance Test of the Effects

1.7. Discrete Choice and Multidimensional Preference Models

1.7.1. Discrete Choice Models
1.7.2. Multidimensional Preference

1.8. Classification and Regression Trees and Random Forests

1.8.1. Classification and Regression Trees
1.8.2. Random Forests

1.9. Multidimensional scaling

1.9.1. Introduction
1.9.2. Distance and Similarity
1.9.3. Classical Solution
1.9.4. Similarities

1.10. Shopping Cart Analysis

1.10.1. Shopping Cart Analysis
1.10.2. Example of Applications

Thanks to the most efficient pedagogical methodology, TECH Relearning, you will be able to assimilate the essential concepts of the content, in a precise and natural way”