Data analysis and business forecasting in Excel - Workshop 2017

Microsoft Excel is the world’s most commonly used application for data analysis – it was designed for this purpose. Learn about Excel’s statistical tools and vast collection of functions and how they can be used to extract useful information from data.

Building forecasting models in Excel requires a sound understanding of some of the extensively used predictive models employed by forecasters and how to implement them in Excel.

Key topics:

• Common statistical tools to model data and identify relationships between variables
• Excel’s Data Analysis Add-in – the Analysis ToolPak
• Excel’s common statistical functions
• Build commonly used forecasting models for stationary and non-stationary data
• Select an appropriate forecasting model for a given data series
• Develop models to identify trend and seasonality in business data, as well as choosing appropriate forecasting models to deal with time series data

Offered in Excel 2013 and compatible with Excel versions 2007, 2010.

Learning objectives

• Select statistical functions in Excel
• Use the Data Analysis Add-In to obtain descriptive measures and apply regression analysis
• Quantify the nature and strength of relationships between variables
• Create basic statistical distributions
• Describe some of the concepts behind ‘big data’
• Appreciate the benefits of forecasting models
• Identify patterns in data and identify suitable forecasting models using charts
• Compare forecasting models and select a "best" model
• Describe some limitations of forecasting models
• Integrate judgment with a statistical model
• Describe the importance of forecasting in the budgeting process
• Use Solver to select the optimal parameters for a model
• Develop a Seasonal Index
• Appreciate Classical Decomposition
• Use predictive models in Excel

Audience

This workshop is designed specifically for finance and accounting professionals who use Excel in their day to day roles.

Please note enrolments close 2 working days prior to the workshop date.

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