Enroll now and acquire new skills on Data Description and Exploration quickly and in a 100% online modality”

The ability to create clear and effective visualizations can help professionals in this area convey their findings in a clear and concise manner, which can be crucial for decision making. Data Description and Data Exploration are essential skills for an engineer, as they enable them to identify patterns and trends, ensure data quality, and communicate the results of analysis effectively effectively. 

Due to this, TECH has designed a Postgraduate certificate in Data Description and Exploration with which it seeks to provide students with the skills and competencies necessary to perform their work as specialists with the highest quality in their work. Thus, throughout this program, aspects such as the Summary of Statistical Data, Unidimensional Descriptive Statistics, the Transformation of Variables or the Types of Variables and Scales of Measurement will be addressed. 

And all this, thanks to a convenient 100% online mode that allows students to organize their studies as best suits them, combining them with their other occupations. 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 efficiently. 

Reach your maximum potential as an expert in Statistics, thanks to a complete program with the most challenging practical activities”

This Postgraduate certificate in Data Description and Exploration 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 Data Description and Exploration
• 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 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

Achieve professional success in one of the most promising areas of Computational Statistics, 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 One-Dimensional Descriptive Statistics from any device with internet connection, whether Tablet, mobile or computer”

Delve into the essentials of Data Description and Exploration, from the comfort of your home, 24 hours a day”

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

Deepen your knowledge, thanks to the most innovative teaching materials and a wide variety of additional content available on the Online Campus”

Module 1. Data Description and Exploration

1.1. Introduction to Statistics

1.1.1. Basic Concepts in Statistics
1.1.2. The Purpose of Exploratory Data Analysis or Descriptive Statistics
1.1.3. Types of Variables and Measurement Scales
1.1.4. Rounding and Scientific Notation

1.2. Summary of Statistical Data

1.2.1. Frequency Distributions: Tables
1.2.2. Grouping in Intervals
1.2.3. Graphical Representations
1.2.4. Differential Diagram
1.2.5. Integral Diagram

1.3. One-Dimensional Descriptive Statistics

1.3.1. Central Position Characteristics: Mean, Median, Mode
1.3.2. Other Position Characteristics: Quartiles, Deciles and Percentiles
1.3.3. Dispersion Characteristics: Variance and Standard Deviation (Sample and Population), Range, Inter-Quartile Range
1.3.4. Relative Dispersion Characteristics
1.3.5. Typical Scores
1.3.6. Shape Characteristics: Symmetry and Kurtosis

1.4. Complements in the Study of a Variable

1.4.1. Exploratory Analysis: Box Plots and Other Graphs
1.4.2. Transforming Variables
1.4.3. Other Averages: Geometric, Harmonic, Quadratic
1.4.4. Chebyshev's Inequality

1.5. Two-Dimensional Descriptive Statistics

1.5.1. Two-Dimensional Frequency Distributions
1.5.2. Double-Entry Statistical Tables. Marginal and Conditional Distributions
1.5.3. Concepts of Independence and Functional Dependence
1.5.4. Graphical Representations

1.6. Complements in the Study of Two Variables

1.6.1. Numerical Characteristics of a Two-Dimensional Distribution
1.6.2. Joint, Marginal and Conditional Moments
1.6.3. Relationship between Marginal and Conditional Measures

1.7. Regression

1.7.1. General Regression Line
1.7.2. Regression Curves
1.7.3. Linear Adjustment
1.7.4. Prediction and Error

1.8. Correlation

1.8.1. Concept of Correlation
1.8.2. Correlation Ratios
1.8.3. Pearson's Correlation Coefficient
1.8.4. Correlation Analysis

1.9. Correlation between Attributes

1.9.1. Sperman's Coefficient
1.9.2. Kendall Coefficient
1.9.3. Chi-Squared Coefficient

1.10. Introduction to Time Series

1.10.1. Time Series
1.10.2. Stochastic Processes

1.10.2.1. Stationary Processes
1.10.2.2. Non-Stationary Processes

1.10.3. Models
1.10.4. Applications

Thanks to the most efficient teaching methodology, TECH Relearning, you will be able to acquire new knowledge in a precise and natural way, without spending too much time studying”