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Statistical Data Analysis

Statistical Data Analysis
Summary

Corporate ethos which sees change as a survival necessity, coupled with continual demands to achieve greater production efficiencies and reduced operating / maintenance costs, means that Engineers and Technologists are faced with ever-increasing plant and process performance targets.

As a consequence, more and more reliance is being placed upon the accurate and reliable analysis, representation and interpretation of data. This course aims to provide engineers and technologists with the understanding and practical capabilities needed to convert data into information, and then to represent this information in ways that it can be readily exploited.

A Working vocabulary of analytical terms which will enable you 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. 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 engineering problems.

This 3-day B. Khebra’s Statistical Data Analysis training course provides you with the ability to recognize which types of analysis are best suited to particular types of problems. It will give you a sufficient background and theoretical knowledge to be able to judge when an applied technique will likely lead to incorrect conclusions..

Reference
Statistical Data Analysis
Objective

Upon successful completion of this course, the delegates will be able to:

  • Provide delegates with a working vocabulary of analytical terms to enable them to converse with people who are experts in the area of data analysis, statistics and probability and to be able to read and comprehend common textbooks in this field. 
  • Provide delegates with both 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 analytical problems. 
  • Give delegates the ability to recognize which types of analysis are best suited to particular types of problems. 
  • Provide delegates with an overview of the main data analysis applications within Engineering Systems 
  • Give Delegates sufficient background and theoretical knowledge to be able to judge when an applied Techniques will likely lead to incorrect conclusions.
Who should attend

This training program is suitable for anyone who needs to use data analysis in their job role, including strategists, programme/project managers, business analysts, business process managers, etc.

Additional Information


Statistical Data Analysis
  • 1.1 Sources of Data
  • 1.2 Data Sampling
  • 1.3 Data Accuracy
  • 1.4 Simple Representations
  • 1.5 Dealing with Practical Issues
  • 2.1 Mean, Average, Median, Mode & Rank
  • 2.2 Lies and Statistics
  • 2.3 Compensations for small sample Sizes
  • 2.4 Descriptive Statistics
  • 2.5 Workshop using Production Data from a batch Fermentation process
  • 3.1 Single and Multi-dimensional Data Visualization
  • 3.2 Trend Analysis
  • 3.3 Box and Whisker Charts
  • 3.4 Common Pitfalls and Problems
  • 3.5 Workshop using Plant Data
  • 4.1 Probability Theory
  • 4.2 Properties of Distributions
  • 4.3 Expected Values
  • 4.4 Weibull Distribution
  • 4.5 Binomial Distribution
  • 4.6 Workshop using Statistical Processes
  • 5.1 Histograms
  • 5.2 Pareto Analysis
  • 5.3 Cumulative percentage Analysis
  • 5.4 Percentile Analysis
  • 5.5 Workshop using Historical Failure Data
  • 6.1 The Fourier Transform
  • 6.2 Periodic and a-periodic Data
  • 6.3 Inverse Transformation
  • 6.4 Practical Implications of Sample Rate
  • 6.5 Dynamic Range
  • 6.6 Workshop using Vibration Data from Machine
  • 7.1 Linear and Non-Linear Regression
  • 7.2 Min Variance, Max Likelihood
  • 7.3 Least Squares Fits
  • 7.4 Curve Fitting Theory
  • 7.5 Linear, Exponential and Polynomial Curve Fits
  • 7.6 Predictive Methods
  • 7.7 Workshop using Data from Large Equipment
  • 8.1 Correlation Analysis
  • 8.2 The Autocorrelation Function
  • 8.3 Practical Considerations of Data Set Dimensionality
  • 8.4 Workshop using Diesel Engine Performance and Pollutant Emission Data.
  • 9.1 Pivot Tables
  • 9.2 The Analytical Toolbox
  • 9.3 Internet-based Analysis Tools
  • 9.4 Dynamic Spreadsheets
  • 9.5 Sensitivity Analysis
  • 9.6 Visualization
  • 9.7 Workshop involving step-by step Examples
  • 10.1 Terminology
  • 10.2 Control Charts
  • 10.3 Statistical Control
  • 10.4 Estimating the Process Mean and Variation
  • 10.5 Capability Indexes
  • 10.6 Workshop on Constructing the X bar and R Charts
  • 11.1 Terminology
  • 11.2 Reliability Definition and Concepts
  • 11.3 Reliability Functions
  • 11.4 Reliability Process
  • 11.5 Workshop on Evaluating the hazard Rate, Survivor Function, Failure Density and Cumulative Distribution Function.
BK Instructor
BK Instructor
 Instructor
  • BK Management Team believe that learning is not only about acquiring technical skills, it is also about learning behaviors & Competencies that are desirable for work in plant operation & maintenance critical dimensions. Our holistic teaching develops our delegates' personal effectiveness to function both as an individual and as a team player. The course delivery & modes of instruction will incorporate theory , practical skills and Q&A sessions. 
  • To enhance learning outcomes, theory sessions will comprise classroom based lecture that will intersperse with interactive discussions, scenario-based, case-study, group exercises, video clips, power point slides, learners' Guide and the application of various tools which will be provided to help in the delegates and participants of the learning’s objectives. With successful implementation of the learnt skills they are bound to enhance Individual & Organizational growth.
  • For online / Interactive Virtual sessions, Delegate should have a stable & good Internet connection on his Laptop.

On successful completion of this training course, BK’s Certificate with eligible Continuing Professional Education credits (CPE), will be awarded to the delegates , one CPE credit is granted per 50 minutes of attendance.

Course Features

  • Core : Training
  • Category : Asset Management
  • Days : 3
  • Duaration : 24 Hours

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