/  Data Analysis Techniques Training

Data Analysis Techniques Training

BMC Training provides a training course in Data Analysis Techniques in Maintenance Engineering Training

Course Title
Venue
Start Date
End Date
  • Istanbul
    16 - 8 - 2020
    20 - 8 - 2020
  • Bali
    16 - 8 - 2020
    20 - 8 - 2020
  • Singapore
    16 - 8 - 2020
    20 - 8 - 2020
  • Washington
    16 - 8 - 2020
    20 - 8 - 2020
  • London
    23 - 8 - 2020
    27 - 8 - 2020
  • Madrid
    23 - 8 - 2020
    27 - 8 - 2020
  • Munich
    23 - 8 - 2020
    27 - 8 - 2020
  • Berlin
    23 - 8 - 2020
    27 - 8 - 2020
  • New York
    23 - 8 - 2020
    27 - 8 - 2020
  • Dubai
    16 - 8 - 2020
    20 - 8 - 2020
  • Paris
    16 - 8 - 2020
    20 - 8 - 2020
  • Hong Kong
    16 - 8 - 2020
    20 - 8 - 2020
  • Dubai
    23 - 8 - 2020
    27 - 8 - 2020
  • Paris
    23 - 8 - 2020
    27 - 8 - 2020
  • Hong Kong
    23 - 8 - 2020
    27 - 8 - 2020
  • Istanbul
    27 - 9 - 2020
    1 - 10 - 2020
  • Bali
    27 - 9 - 2020
    1 - 10 - 2020
  • Singapore
    27 - 9 - 2020
    1 - 10 - 2020
  • Washington
    27 - 9 - 2020
    1 - 10 - 2020
  • Kuala Lumpur
    6 - 9 - 2020
    10 - 9 - 2020
  • Rome
    6 - 9 - 2020
    10 - 9 - 2020
  • Barcelona
    6 - 9 - 2020
    10 - 9 - 2020
  • Zurich
    6 - 9 - 2020
    10 - 9 - 2020
  • Dubai
    13 - 9 - 2020
    17 - 9 - 2020
  • Paris
    13 - 9 - 2020
    17 - 9 - 2020
  • Hong Kong
    13 - 9 - 2020
    17 - 9 - 2020
  • London
    20 - 9 - 2020
    24 - 9 - 2020
  • Madrid
    20 - 9 - 2020
    24 - 9 - 2020
  • Munich
    20 - 9 - 2020
    24 - 9 - 2020
  • Berlin
    20 - 9 - 2020
    24 - 9 - 2020
  • New York
    20 - 9 - 2020
    24 - 9 - 2020
  • Dubai
    27 - 9 - 2020
    1 - 10 - 2020
  • Paris
    27 - 9 - 2020
    1 - 10 - 2020
  • Hong Kong
    27 - 9 - 2020
    1 - 10 - 2020
  • Dubai
    18 - 10 - 2020
    22 - 10 - 2020
  • Paris
    18 - 10 - 2020
    22 - 10 - 2020
  • Hong Kong
    18 - 10 - 2020
    22 - 10 - 2020
  • Kuala Lumpur
    25 - 10 - 2020
    29 - 10 - 2020
  • Rome
    25 - 10 - 2020
    29 - 10 - 2020
  • Barcelona
    25 - 10 - 2020
    29 - 10 - 2020
  • Zurich
    25 - 10 - 2020
    29 - 10 - 2020
  • Istanbul
    4 - 10 - 2020
    8 - 10 - 2020
  • Bali
    4 - 10 - 2020
    8 - 10 - 2020
  • Singapore
    4 - 10 - 2020
    8 - 10 - 2020
  • Washington
    4 - 10 - 2020
    8 - 10 - 2020
  • London
    11 - 10 - 2020
    15 - 10 - 2020
  • Madrid
    11 - 10 - 2020
    15 - 10 - 2020
  • Munich
    11 - 10 - 2020
    15 - 10 - 2020
  • Berlin
    11 - 10 - 2020
    15 - 10 - 2020
  • New York
    11 - 10 - 2020
    15 - 10 - 2020
  • Dubai
    4 - 10 - 2020
    8 - 10 - 2020
  • Paris
    4 - 10 - 2020
    8 - 10 - 2020
  • Hong Kong
    4 - 10 - 2020
    8 - 10 - 2020
  • Dubai
    11 - 10 - 2020
    15 - 10 - 2020
  • Paris
    11 - 10 - 2020
    15 - 10 - 2020
  • Hong Kong
    11 - 10 - 2020
    15 - 10 - 2020
  • Istanbul
    15 - 11 - 2020
    19 - 11 - 2020
  • Bali
    15 - 11 - 2020
    19 - 11 - 2020
  • Singapore
    15 - 11 - 2020
    19 - 11 - 2020
  • Washington
    15 - 11 - 2020
    19 - 11 - 2020
  • Kuala Lumpur
    22 - 11 - 2020
    26 - 11 - 2020
  • Rome
    22 - 11 - 2020
    26 - 11 - 2020
  • Barcelona
    22 - 11 - 2020
    26 - 11 - 2020
  • Zurich
    22 - 11 - 2020
    26 - 11 - 2020
  • Dubai
    1 - 11 - 2020
    5 - 11 - 2020
  • Paris
    1 - 11 - 2020
    5 - 11 - 2020
  • Hong Kong
    1 - 11 - 2020
    5 - 11 - 2020
  • London
    8 - 11 - 2020
    12 - 11 - 2020
  • Madrid
    8 - 11 - 2020
    12 - 11 - 2020
  • Munich
    8 - 11 - 2020
    12 - 11 - 2020
  • Berlin
    8 - 11 - 2020
    12 - 11 - 2020
  • New York
    8 - 11 - 2020
    12 - 11 - 2020
  • Dubai
    15 - 11 - 2020
    19 - 11 - 2020
  • Paris
    15 - 11 - 2020
    19 - 11 - 2020
  • Hong Kong
    15 - 11 - 2020
    19 - 11 - 2020
  • Dubai
    20 - 12 - 2020
    24 - 12 - 2020
  • Paris
    20 - 12 - 2020
    24 - 12 - 2020
  • Hong Kong
    20 - 12 - 2020
    24 - 12 - 2020
  • Kuala Lumpur
    27 - 12 - 2020
    31 - 12 - 2020
  • Rome
    27 - 12 - 2020
    31 - 12 - 2020
  • Barcelona
    27 - 12 - 2020
    31 - 12 - 2020
  • Zurich
    27 - 12 - 2020
    31 - 12 - 2020
  • Istanbul
    13 - 12 - 2020
    17 - 12 - 2020
  • Bali
    13 - 12 - 2020
    17 - 12 - 2020
  • Singapore
    13 - 12 - 2020
    17 - 12 - 2020
  • Washington
    13 - 12 - 2020
    17 - 12 - 2020
  • London
    6 - 12 - 2020
    10 - 12 - 2020
  • Madrid
    6 - 12 - 2020
    10 - 12 - 2020
  • Munich
    6 - 12 - 2020
    10 - 12 - 2020
  • Berlin
    6 - 12 - 2020
    10 - 12 - 2020
  • New York
    6 - 12 - 2020
    10 - 12 - 2020
  • Dubai
    13 - 12 - 2020
    17 - 12 - 2020
  • Paris
    13 - 12 - 2020
    17 - 12 - 2020
  • Hong Kong
    13 - 12 - 2020
    17 - 12 - 2020
  • Dubai
    6 - 12 - 2020
    10 - 12 - 2020
  • Paris
    6 - 12 - 2020
    10 - 12 - 2020
  • Hong Kong
    6 - 12 - 2020
    10 - 12 - 2020

Introduction

Corporate ethos which demands continual improvement in work place efficiencies and reduced operating, maintenance, support service and administration costs means that managers, analysts and their advisors are faced with ever-challenging analytical problems and performance targets. To make decisions which result in improved business performance it is vital to base decision making on appropriate analysis and interpretation of numerical data.

Objectives                                                   

This course aims to provide those involved in analysing numerical data with the understanding and practical capabilities needed to convert data into information via appropriate analysis, and then to represent these results in ways that can be readily communicated to others in the organisation.

Objectives include:

  • To provide delegates with both an understanding and practical experience of a range of the more common analytical techniques and representation methods for numerical data.
  • To give delegates the ability to recognize which types of analysis are best suited to particular types of problems.
  • To give delegates sufficient background and theoretical knowledge to be able to judge when an applied technique will likely lead to incorrect conclusions.
  • To provide delegates with a working vocabulary of analytical terms to enable them to converse with people who are experts in the areas of data analysis, statistics and probability, and to be able to read and comprehend common textbooks and journal articles in this field.
  • To introduce some basic statistical methods and concepts.
  • To explore the use of Excel 2010 or 2013 for data analysis and the capabilities of the Data Analysis Tool Pack.

Content

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.

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