Data Analysis Techniques
Effective Business Decisions using Data Analysis
08-12 April 2024
Sandton
Johannesburg South Africa
Cost per Delegate
R19,999.00
Course Overview
The statistical analysis of numerical information is proven to be a powerful tool, providing businesses with everyday insight into matters like corporate finance, manufacturing processes, service provision and product quality control.
Data Analysis Techniques course aims to provide those involved in analyzing numerical data with the understanding and practical capabilities needed to convert data into information via appropriate analysis, how to represent these results in ways that can be readily communicated to others in the organization, and how to use the information to make evidence-based business decisions.
The training will show delegates how to make the most of Excel by explaining and demonstrating many of the very powerful analytical, visualization and interpretation capabilities that it is capable of.
• Approach a data analysis problem in a logical manner
• Maximize the accuracy of analysis and minimize the chance of errors
• Extract and represent information from complex numerical data
• Interpret features from within data and make evidence-based decisions
• Perform a ‘what if’ scenario analysis
• Predict the future behavior of a system or a process using regression analysis
• Predict the future behavior of a system or a process, using data science methods
• Use analysis of variance (ANOVA) to minimize the risk of false interpretation
• Make the most of Microsoft Excel by using many of the advanced features that it contains
Course Objectives
At the end of this Data Analysis Techniques training course, you will have:
• A good understanding and extensive practical experience of a range of common analytical techniques and interpretation methods for numerical data
• The ability to recognize which types of analysis are best suited to particular types of problems
• The ability to judge when an applied technique will likely lead to incorrect conclusions
• A good understanding of a wide range of common statistical methods and approaches
• The ability to use Microsoft Excel 2016, 2019 or 365 to analyze and interpret a wide range of real data types
• Experience of how to transform numerical data into evidence and hence how to make informed business decisions
Who should Attend?
• Performance assessment and monitoring
• Planning
• Data analysis
• Management and leadership
• Finance
• Human resources
• Quality control
• Engineering and technology
Course Outline
DAY 1
Logical and Reliable Data Analysis, Descriptive Statistics, and Pivot Tables
• Importing data into Excel
• Best practice when analyzing data
• Analyzing and representing coded data
• Descriptive statistics and their real meanings
• Performing a frequency analysis
• The use of pivot tables and pivot charts
• Noisy and incomplete data, statistical significance and dealing with outliers
DAY 2
Data Mode Shape Analysis
• Plotting data against time
• Generating data mode shapes
• Fitting curves to data
• Correlating mode shape to time-based events
• Interpreting time series analyses
• Moving average calculations
DAY 3
Scenario Analysis and Interactive Spreadsheets
• Representing analytical problems as multi-input, single-output (MISO) systems
• Deterministic systems analysis
• What if and visual scenario analysis
• Dynamic / interactive spreadsheets and the use of forms control
• Moving window, conditional and adaptive calculations
• Measuring the sensitivity of calculated variables
DAY 4
Regression Analysis and Correlation
• Equations of curves
• The prediction of future behavior using data shape – regression analysis
• Linear, polynomial, exponential and power curve fits
• The dangers of over-fitting
• Data end effects
• Goodness of fit (sum of square error – SSE) and R2
• Evaluating equations, solving equations, and using Solver
• Correlation and causality
DAY 5
Data Driven Methods and Analysis of Variance
• Non-deterministic system
• Data driven methods
• One step ahead future prediction using data science (multivariate correlation)
• Single factor analysis of variance (ANOVA)
• Two factor analysis of variance
• A demonstration of artificial intelligence – the travelling salesman problem
End of the Workshop
For Training arrangements call us on the detail below
TANZANIA: +255 749 50 26 78
SOUTH AFRICA: +27 694 31 79 73
KENYA: +255 749 50 26 78
DUBAI: +27 694 31 79 73
