Statistics and Big Data. Inference and statistical methods are applied in the control of production or stock processes, quality control and reliability, customer analysis and market or product studies, risk or financial product analysis, data mining and business intelligence, Very fashionable today under the name of Big Data, design of experiments, clinical analysis, epidemiological studies, etc. The results of the research in this area are in the field of statistical inference, biostatistics, geostatistics, sampling and re-sampling techniques, time series, non-parametric inference, categorical data, censored and / or truncated data, prediction, analysis Multivariate, etc. ITMATI deals with this technology with the solution to demands related to statistical advice and data analysis, prediction in time series, mapping from spatial data, modeling in finance, with environmental and energy statistics, With statistics of tourism, health, and in general, with all kinds of problems related to statistical applications in the industry or the company.

Outline:

• Statistical modelling.
• Regression models.
• Predictive models.
• Multivariate analysis:
  - Multivariate analysis.
  - Classification and discrimination.
  - Cluster analysis.
  - Analysis of compositional data.
• Non-parametric and parametric inference:
  - Statistical inference.
  - Parameter estimation.
  - Stimation in small areas.
  - Procedures for sturdiness.
  - Resampling methods.
•  Inference for stochastic processes:
  - Stochastic processes.
  - Time series.
  - Spatial statistics.
  - Space-time statistics.
  - Neural networks.
  - Analysis of functional data (dependent data, categorical data, censored data).
• Other statistical methods:
  - Experimental design.
  - Sampling techniques.
  - Imputation techniques.
  - Survival analysis.

Specific cases:

• Quality control.
  - Quality control. Reliability.
• Control and optimization of production processes and stocks:
  - Control of products.
  - Process control.
• Risk and financial analysis:
  - Quantitative finance.
  - Econometrics.
  - Risk modellling.
  - Valuation of financial derivatives.
  - General equilibrium.
  - Social accounting planning.
• Surveys of customers, markets and products:
  - Designs, development and analysis of surveys.
  - Statistical confidentiality.
  - Data protection.
• Exploiting internal information.
  - Analysis of data. Data mining.
• Experimental designs, clinical trials.
  - Other statistical techniques (sampling, de imputation, survival analysis...)
• Biostatistics.
  - Epidemiology.
  - Clinical trials and effectiveness of treatments.
  - Genomics.
• Statistical models for energy and the environment.
  - Pollution control.
  - Impact and emission reduction.
  - Wind and solar forecast maps.
• Geostatistics.
  - Hidrogeology, oceanography, etc.