5 Sections
51 Lessons
20 Hours
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1. Univariate Data Analysis and Visualization
10
1.1
Sample design
1.2
The scale: types and selection criteria
1.3
Database development
1.4
Measures of centrality and variability
1.5
Calculating measurements using computer tools
1.6
Univariate data visualization
1.7
Variable distribution pattern
1.8
Classification of variables with tools
1.9
Exam
1.10
Additional content
2. Multivariate Data Analysis and Visualization
11
2.1
Relationship between quantitative variables: types and selection criteria
2.2
Calculation of relational measures using computer tools
2.3
Visualization of multivariate relationships using computer tools
2.4
Relationship between qualitative variables: types and selection criteria
2.5
Creating contingency tables using computer tools
2.6
Calculation of relational measures using computer tools
2.7
Data classification and reduction methods
2.8
Selection criteria for exploratory tools for multivariate relationships
2.9
Verification of assumptions for data classification and reduction methods using computer tools
2.10
Exam
2.11
Additional content
3. Econometric Techniques (Modeling and Prediction)
9
3.1
Concept, data and its handling, introduction to Gretl
3.2
Simple Linear Regression Model: Elements, hypotheses, estimation
3.3
Multiple Linear Regression Model
3.4
Contrasts, diagnosis, prediction
3.5
Economic Forecasting Techniques
3.6
Analysis of a series with a trend
3.7
Guidelines for evaluation
3.8
Exam
3.9
Additional content
4. Big Data: Concepts, Methods and Technologies
11
4.1
Introduction to Big Data Processing and Analysis
4.2
Data Type Classification
4.3
Big Data Project Development Cycle
4.4
Data Processing Strategies
4.5
Hybrid Architectures for Big Data
4.6
Laboratory Analysis vs. Production Analysis
4.7
Laboratory Analysis vs. Production Analysis
4.8
The Apache Ecosystem of Hadoop
4.9
Introduction to NoSQL Databases
4.10
Exam
4.11
Additional content
5 Trends in Data Analysis and Big Data
10
5.1
Data Mining / Machine Learning
5.2
Risk Analysis and Quality Management
5.3
Data Analysis and Visualization for Decision Making
5.4
Methodologies for advanced modeling and prediction
5.5
Univariate and Multivariate Modeling
5.6
Debate on Trends in Big Data Analytics
5.7
Cloud Computing and Big Data
5.8
Applications of Big Data Analytics
5.9
Exam
5.10
Additional content
Data Analysis and Big Data Techniques
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