Trainings & Webinars

This course covers the easy to use features in EXCEL & XLSTAT for investigating, visualising and performing basic statistical analyses on data sets typical to business, research and industry settings.

Getting to Grips With Basic Data Analysis Using XLSTAT

You will learn how to understand your data better through simple data visualisations and how to test simple hypotheses to help inform business decisions using data. Mathematical details are kept to a necessary minimum and we focus on the interpretation of the outputs from XLSTAT and illustrate applications with case studies using data from surveys, instrumental analysis, manufacturing processes, clinical trials and biological data. There is plenty of opportunity for practice using XLSTAT through "hands on exercises" for which annotated solutions are provided.

Course Outline
Day 1
• Assessing Business/Process Performance Data.
• Data Distributions• Data characterisation (Mean, Variance, Median, Percentiles)
• Data visualisation using box plots and histograms
• Categorical Data - frequency tables and bar charts
• EXCEL Pivot tables for easy data summary
• Decision Making Based on Sample Data
• Comparing sample data to business targets
• Use and interpretation of confidence intervals
• Statistical significance - what it measures, what it does not measure
• Comparison of Sample Data Sets
• Quantifying differences
• T tests to compare means
• Significance tests v Confidence Intervals
• Presenting Results
• Data Requirements
• Generalisation to Analysis of Variance

Day 2
• Comparing Response/Success Rates
• Estimating Response Rates
• Measuring uncertainty using confidence intervals
• Testing for significance
• Investigating Associations between Categorical Variables
• Chi-Squared test
• Graphical visualisations using CHAID
• Investigating Relationships between Variables
• Correlation - what is measures
• Correlation v Causation
• Simple trend modelling - assessment of fit
• Diagnostics
• Multiple Regression & Further Modelling
• Variable selection techniques
• Pitfalls for the unwary
• Modelling curvature
• Project/ Study Design
• Issues to consider
• Sample Size
• Avoiding Confounding 

Anne Hasted

Anne is senior consultant at Qi Statistics Ltd, a UK based consultancy offering a full portfolio of statistical support through training, data analysis, project consultancy and software development. She is a chartered statistician with over 25 years of consultancy experience in a wide range of companies. She has run training workshops worldwide and is recognised for providing “user friendly” training.

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Training actions