Info-Graphics: Data Analysis and Reporting Techniques

Course Date

2 - 6 October 2023
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30 October - 3 November 2023
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20 - 24 November 2023
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11 - 15 December 2023
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25 - 29 December 2023
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Course content

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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.
This training seminar 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 understanding and practical experience of a range more common to 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 that will 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
To explore the use of Excel 2010 or 2013 for Data Analysis and the capabilities of the Data Analysis Tool
Training Methodology
The training course adopts a problem-based learning approach, in which delegates are presented with a series of real numerical data analysis problems drawn from the widest possible range of applications – from engineering to finance and from logistics to quality control.
Each problem presents and  exemplifies the  need for a different data analysis approach. For reasons of time constraint it will not be possible to develop solutions during the training course to all of the problems posed. Nevertheless, all delegates will be given comprehensive solutions to all of the problems, to take away with them at the end of the training course, as future learning resources.
The training course is entirely applications-oriented, minimizing the time spent on the mathematics of analysis and maximizing the time spent on the use of practical methods in Excel, along with the understanding why such methods work.
Delegates will spend almost all of the time exploring Excel's data analysis and representation functionality, including the Data Analysis Tool Pack, to investigate the totally realistic data analysis problems.
Organisational Impact
Organisations that are able to make optimum decisions will enhance their ability to compete on the global stage. The participants on this training course, and therefore the teams that they work within will, as a result of their training, be better positioned to influence the organisation with recommendations based on objective data analysis that in turn produce a higher performing business.
Individuals exposed to this training will develop new insights to the usefulness of Excel and the field of data analysis, and they will learn why the best companies in the world see data analysis as being essential to delivering the right quality products and services at the lowest  costs.
Personal Impact
Participants will gain an understanding and  practical experience of a range of the more common analytical techniques and data representation methods, which have direct relevance to a wide range of issues. The ability to recognize which types of analysis are best suited to particular types of issue will be addressed, and delegates will be given sufficient background and theoretical knowledge to be able  to judge when an applied technique will likely lead to incorrect conclusions.
Who Should Attend?
The training course has been designed for professionals whose jobs involve the manipulation, representation, interpretation and/or analysis of data. Familiarity with a PC and in particular with Microsoft Excel (2003, 2007, 2010 or 2013) is assumed.
The training course involves extensive computer-based data analysis using Excel 2010 and therefore delegates will be expected to be numerate and to enjoy working with numerical data on a computer.
Seminar Outline
The Basics
  • Sources of data, data sampling, data accuracy, data completeness, simple representations, dealing with practical
Fundamental Statistics
  • Mean, average, median, mode, rank, variance, covariance, standard deviation, “lies, more lies and  statistics”, compensations for small  sample sizes,  descriptive statistics, insensitive
Basics of Data Mining and  Representation
  • Single, two and  multi-dimensional data visualization, trend analysis, how to decide what  it is that you want  to see, box and  whisker  charts, common pitfalls  and 
Data Comparison
  • Correlation analysis, the autocorrelation function, practical considerations of data set dimensionality, multivariate and  non-linear
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
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 
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 spreadsheets, sensitivity
Introduction and Descriptive Statistics                       
  • What is data analysis
  • A reminder of elementary statistics
  • A quick-start tutorial for Excel
  • Describing data sets using statistics
  • Representing data sets graphically
  • How to create infographic in Excel
  • The normal distribution
  • Mini-Case studies
Frequency and Time Series Analysis              
  • Frequency of occurrence
  • Histograms
  • Pareto analysis
  • Pivot tables and pivot charts
  • Creating Excel dashboard
  • Time series analysis
  • Trending data
  • Estimation theory
  • Mini-Case studies
Scenario Analysis, Confidence and Six Sigma
  • Modeling scenario
  • Interactive spreadsheets
  • Confidence intervals
  • Control charts
  • An Introduction to Six Sigma
  • Error bars
  • Mini-Case studies
Regression Analysis Equations and System Modeling 
  • Simple regression analysis
  • Curve fitting
  • Describing data using equations
  • Prediction
  • Modeling single input single output systems
  • Modeling multiple input single output systems
  • Constraint optimization using Solver
  • Mini-Case studies 
Correlation Analysis and Anova     
  • Differences between data sets
  • Correlation analysis
  • Analysis of variance (ANOVA)
  • Mini-Case studies
  • Overall review of concepts learned and how they can be applied in practice

United Kingdom

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07:30 – 19:00
Monday to Friday


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+995 706 070161
07:30 – 19:00
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