Data Analysis Methods and Techniques

Course Info

Length: 1 Week

Type: In Classroom

Available Dates

Venue

  • Nov-18-2024

    London

  • Nov-18-2024

    Amsterdam

  • Nov-25-2024

    Kuala Lumpur

  • Nov-25-2024

    Istanbul

  • Dec-02-2024

    Paris

  • Dec-02-2024

    Singapore

  • Dec-09-2024

    Dubai

  • Dec-09-2024

    Barcelona

  • Dec-16-2024

    Amsterdam

  • Dec-16-2024

    London

  • Dec-23-2024

    Kuala Lumpur

  • Dec-23-2024

    Singapore

  • Dec-30-2024

    Istanbul

  • Dec-30-2024

    Paris

  • Jan-06-2025

    Istanbul

  • Jan-06-2025

    Kuala Lumpur

  • Jan-13-2025

    Singapore

  • Jan-13-2025

    Paris

  • Jan-20-2025

    Amsterdam

  • Jan-20-2025

    London

  • Jan-27-2025

    Dubai

  • Jan-27-2025

    Barcelona

  • Feb-03-2025

    Istanbul

  • Feb-03-2025

    Kuala Lumpur

  • Feb-10-2025

    Singapore

  • Feb-10-2025

    Paris

  • Feb-17-2025

    Amsterdam

  • Feb-17-2025

    London

  • Feb-24-2025

    Barcelona

  • Feb-24-2025

    Dubai

  • Mar-03-2025

    Kuala Lumpur

  • Mar-03-2025

    Istanbul

  • Mar-10-2025

    Paris

  • Mar-10-2025

    Singapore

  • Mar-17-2025

    Amsterdam

  • Mar-17-2025

    London

  • Mar-24-2025

    Dubai

  • Mar-24-2025

    Barcelona

  • Mar-31-2025

    Kuala Lumpur

  • Mar-31-2025

    Istanbul

  • Apr-07-2025

    Istanbul

  • Apr-07-2025

    Kuala Lumpur

  • Apr-14-2025

    Paris

  • Apr-14-2025

    Singapore

  • Apr-21-2025

    London

  • Apr-21-2025

    Amsterdam

  • Apr-28-2025

    Barcelona

  • Apr-28-2025

    Dubai

  • May-05-2025

    Kuala Lumpur

  • May-05-2025

    Istanbul

  • May-12-2025

    Paris

  • May-12-2025

    Singapore

  • May-19-2025

    London

  • May-19-2025

    Amsterdam

  • May-26-2025

    Barcelona

  • May-26-2025

    Dubai

  • June-02-2025

    Kuala Lumpur

  • June-02-2025

    Istanbul

  • June-09-2025

    Singapore

  • June-09-2025

    Paris

  • June-16-2025

    Amsterdam

  • June-16-2025

    London

  • June-23-2025

    Barcelona

  • June-30-2025

    Kuala Lumpur

  • June-30-2025

    Istanbul

  • June-30-2025

    Dubai

  • July-07-2025

    Kuala Lumpur

  • July-07-2025

    Istanbul

  • July-14-2025

    Singapore

  • July-14-2025

    Paris

  • July-21-2025

    Amsterdam

  • July-21-2025

    London

  • July-28-2025

    Barcelona

  • July-28-2025

    Dubai

  • Aug-04-2025

    Istanbul

  • Aug-04-2025

    Kuala Lumpur

  • Aug-11-2025

    Paris

  • Aug-11-2025

    Singapore

  • Aug-18-2025

    London

  • Aug-18-2025

    Amsterdam

  • Aug-25-2025

    Dubai

  • Aug-25-2025

    Barcelona

  • Sep-01-2025

    Istanbul

  • Sep-01-2025

    Kuala Lumpur

  • Sep-08-2025

    Singapore

  • Sep-08-2025

    Paris

  • Sep-15-2025

    London

  • Sep-15-2025

    Amsterdam

  • Sep-22-2025

    Barcelona

  • Sep-29-2025

    Kuala Lumpur

  • Sep-29-2025

    Istanbul

  • Sep-29-2025

    Dubai

  • Oct-06-2025

    Kuala Lumpur

  • Oct-06-2025

    Istanbul

  • Oct-13-2025

    Paris

  • Oct-13-2025

    Singapore

  • Oct-20-2025

    Amsterdam

  • Oct-20-2025

    London

  • Oct-27-2025

    Dubai

  • Oct-27-2025

    Barcelona

  • Nov-03-2025

    Istanbul

  • Nov-03-2025

    Kuala Lumpur

  • Nov-10-2025

    Paris

  • Nov-10-2025

    Singapore

  • Nov-17-2025

    London

  • Nov-17-2025

    Amsterdam

  • Nov-24-2025

    Barcelona

  • Nov-24-2025

    Dubai

  • Dec-01-2025

    Istanbul

  • Dec-01-2025

    Kuala Lumpur

  • Dec-08-2025

    Paris

  • Dec-08-2025

    Singapore

  • Dec-15-2025

    London

  • Dec-15-2025

    Amsterdam

  • Dec-22-2025

    Barcelona

  • Dec-29-2025

    Istanbul

  • Dec-29-2025

    Kuala Lumpur

  • Dec-29-2025

    Dubai

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