Managing Business Statistics with Excel

23rd-24th September 2008

The Course

Much of the statistical analysis and many of the important statistical insights required by managers and business analysts can be achieved using Excel. This 2-day course is designed to:

• introduce all the most important concepts relevant to business use
• enable you to do your own analysis for the simpler situations
• have a clearer understanding of statistical issues
• extract maximum benefit from your business data

All of the techniques we introduce are available in Excel – there is no need to purchase special software.

Course Objectives:

We have designed this course for managers and business analysts who want to make better business decisions through the application of simple statistical techniques.

Following the course delegates should be able to:

• Understand the role and advantages of data visualisation
• Make the most appropriate data summary measures to compare business performance in different sectors or periods
• Understand how to measure the risk in any decision making based on a data sample
• Build simple trend models to identify and investigate relationships between business metrics
• Make simple forecasts of future business performance

Course Details:

Venue: QA-IQ training facility in central Reading

Dates: 23rd-24th September 2008

Cost: £600 +VAT

To include lunch plus a CD containing the data used on the course together with a bound set of course notes, worked examples and several EXCEL spreadsheets with additional analysis tools.

For further information and an application form please email us or call us on +44 (0)118 934 4265

Course Outline

Day 1: Data summary, uncertainty, significance

Data display and summary statistics:

• Constructing histograms and time trend plots – one picture is worth a thousand numbers
• Summary statistics, mean, median, standard deviation – interpretation and application
  • Calculations using Excel statistical functions and pivot tables

Data distributions and comparison of groups:

• How different sources of data give rise to different distributions and why this matters
• Choosing the most appropriate data summary ( mean, median, percentile) for comparison of performance in different groups
• Cumulative distributions and deciles for comparing performance in different groups or time periods?
• Pareto Analysis for identifying the problems with the largest effect

Decision making from sample data:

• Samples and uncertainty; trying to see the bigger picture with limited data
  • Standard error and confidence interval, calculation and interpretation
• Statistical significance; to help us assess risk
  • What does it measure?
  • Is it really useful?
• Tests for differences in sample means (T-Test); are we seeing a real difference when we make changes?
• Tests for differences in response or failure rates; is our new marketing better? Have we improved performance?
• Sample size – how to decide how large a sample is needed and not waste money

Day 2: Modelling concepts

Correlation and simple linear regression to identify trends in business performance

• Correlation and its interpretation
• The linear regression model to make simple predictions of performance
• How to measure prediction accuracy

Multiple linear regression for when more than one factor affects performance

• How to incorporate several predictors in the model
• The special role of correlation in multiple regression
• The meaning of the model

Simple forecasting for better predictions

• Issues in forecasting future business performance from historical data
• Moving average
• Trend analysis
• Exponential smoothing