Data Analysis Techniques. ©

INTRODUCTION:

Data Analysis Techniques 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.

Objectives :

1- 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
2- To give delegates the ability to recognize which types of analysis are best suited to particular types of problems
3- To give delegates sufficient background and theoretical knowledge to be able to judge when an applied technique will likely lead to incorrect conclusions
4- 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
5- To introduce some basic statistical methods and concepts
6- To explore the use of Excel 2010 or 2013 for data analysis and the capabilities of the Data Analysis Tool Pack.

Outline:

• Data Sampling, Accuracy and Completeness
• Conventional Statistics
• Basics of Data Mining and Representation
• Data Comparison, Correlation Analysis
• Histograms and Frequency of Occurrence
• Frequency Analysis, the Fourier transform
• Regression Analysis and Curve Fitting
• Probability and Confidence, Risk and Uncertainty, ANOVA (Analysis of Variance)
• Pivot tables the Data Analysis Tool Pack
• Dynamic Spreadsheets, Sensitivity Analysis