Data Analysis Methods and Techniques

Course Info

Length: 1 Week

City: Istanbul

Type: In Classroom

Available Dates

  • Apr-29-2024

    Istanbul

  • May-27-2024

    Istanbul

  • June-24-2024

    Istanbul

  • July-29-2024

    Istanbul

  • Aug-26-2024

    Istanbul

  • Sep-30-2024

    Istanbul

  • Oct-28-2024

    Istanbul

  • Nov-25-2024

    Istanbul

  • Dec-30-2024

    Istanbul

Dates in Other Venues

  • Apr-01-2024

    Paris

  • Apr-01-2024

    Singapore

  • Apr-08-2024

    Dubai

  • Apr-08-2024

    Barcelona

  • Apr-15-2024

    London

  • Apr-15-2024

    Amsterdam

  • Apr-22-2024

    Singapore

  • Apr-22-2024

    Kuala Lumpur

  • Apr-29-2024

    Paris

  • May-06-2024

    Singapore

  • May-06-2024

    Paris

  • May-13-2024

    Dubai

  • May-13-2024

    Barcelona

  • May-20-2024

    London

  • May-20-2024

    Amsterdam

  • May-27-2024

    Kuala Lumpur

  • June-03-2024

    Singapore

  • June-03-2024

    Paris

  • June-10-2024

    Dubai

  • June-10-2024

    Barcelona

  • June-17-2024

    London

  • June-17-2024

    Amsterdam

  • June-24-2024

    Kuala Lumpur

  • July-01-2024

    Paris

  • July-01-2024

    Singapore

  • July-08-2024

    Dubai

  • July-08-2024

    Barcelona

  • July-15-2024

    Amsterdam

  • July-15-2024

    London

  • July-22-2024

    Singapore

  • July-22-2024

    Kuala Lumpur

  • July-29-2024

    Paris

  • Aug-05-2024

    Paris

  • Aug-05-2024

    Singapore

  • Aug-12-2024

    Barcelona

  • Aug-12-2024

    Dubai

  • Aug-19-2024

    Amsterdam

  • Aug-19-2024

    London

  • Aug-26-2024

    Kuala Lumpur

  • Sep-02-2024

    Paris

  • Sep-02-2024

    Singapore

  • Sep-09-2024

    Barcelona

  • Sep-09-2024

    Dubai

  • Sep-16-2024

    Amsterdam

  • Sep-16-2024

    London

  • Sep-23-2024

    Kuala Lumpur

  • Sep-23-2024

    Singapore

  • Sep-30-2024

    Paris

  • Oct-07-2024

    Paris

  • Oct-07-2024

    Singapore

  • Oct-14-2024

    Dubai

  • Oct-14-2024

    Barcelona

  • Oct-21-2024

    Amsterdam

  • Oct-21-2024

    London

  • Oct-28-2024

    Kuala Lumpur

  • Nov-04-2024

    Paris

  • Nov-04-2024

    Singapore

  • Nov-11-2024

    Dubai

  • Nov-11-2024

    Barcelona

  • Nov-18-2024

    London

  • Nov-18-2024

    Amsterdam

  • Nov-25-2024

    Kuala Lumpur

  • Dec-02-2024

    Paris

  • Dec-02-2024

    Singapore

  • Dec-09-2024

    Barcelona

  • Dec-09-2024

    Dubai

  • Dec-16-2024

    London

  • Dec-16-2024

    Amsterdam

  • Dec-23-2024

    Singapore

  • Dec-23-2024

    Kuala Lumpur

  • Dec-30-2024

    Paris

Course Details

Course Outline

5 days course

The Basics
 
  • Sources of data, data sampling, data accuracy, data completeness, simple representations, dealing with practical issues.

 

Fundamental Statistics

 

  • Mean, average, median, mode, rank, variance, covariance, standard deviation, “lies, more lies and statistics”, compensations for small sample sizes, descriptive statistics, insensitive measures.
Basics of Data Mining and Representation
 
  • Single, two and multi-dimensional data visualisation, trend analysis, how to decide what it is that you want to see, box and whisker charts, common pitfalls and problems.

 

Data Comparison

 

  • Correlation analysis, the autocorrelation function, practical considerations of data set dimensionality, multivariate and non-linear correlation.
 
Histograms and Frequency of Occurrence

 

  • Histograms, Pareto analysis (sorted histogram), cumulative percentage analysis, the law of diminishing return, percentile analysis.
Frequency Analysis
 
  • The Fourier transform, periodic and a-periodic data, inverse transformation, practical implications of sample rate, dynamic range and amplitude resolution.

 

Regression Analysis and Curve Fitting

 

  • Linear and non-linear regression, order; best fit; minimum variance, maximum likelihood, least squares fits, curve fitting theory, linear, exponential and polynomial curve fits, predictive methods.
Probability and Confidence

 

  • Probability theory, properties of distributions, expected values, setting confidence limits, risk and uncertainty, ANOVA (analysis of variance).

 

Some more advanced ideas
 
  • Pivot tables, the Data Analysis Tool Pack, internet-based analysis tools, macros, dynamic spread sheets, sensitivity analysis.

Course Video