Effective Use of Data and Analytics for Organisations

Session 1: How can data and analytics enhance human decision making in organisations in a way that’s legally, ethically, and culturally appropriate?

• Provides an introduction to the course and to each other.
• Introduces the types of questions that can and can’t be answered using data and analytics.
• Shows how data and analytics complement, rather than substitute for, human judgment as part of decision making
• Discusses the legal, ethical, and cultural considerations that need to be taken into account when working with data. 

Session 2: What types of data are there and how does data need to be prepared for analysis?

• Discusses different categories and sources of data and which tend to be most useful for different purposes. 
• Discusses some of the challenges associated with preparing data for analysis and how to find and deal with bad and missing data. 
• Describes different types of variables and how the type of variable influences the type of analysis you can do. 

Session 3: How do we answer ‘how many’, ‘what proportion’, and ‘what’s normal’ type questions using Excel?

• Introduces different ways of answering ‘how many’, ‘what proportion’, and ‘what’s normal’ type questions using Excel. 
• Introduces histograms and show how to make them in Excel. 
• Describes when statistical tests are needed to answer questions such as  ‘how many’, ‘what proportion’, and ‘what’s normal’, and show how to execute them in Excel. 

Session 4: How do we answer questions about differences in ‘how many’, ‘what proportion’, and ‘what’s normal’ using Excel?

• Describes why it’s often useful to check for differences in averages and proportions by group or variable. 
• Explains when tests for statistical significance are needed, and also why they are not the same as establishing practical relevance. 
• Outlines the statistical tests that need to be applied in different situations and how to execute them in Excel. 

Session 5: How can we use Excel to answer questions involving predictions?

• Teaches you how to make predictions using regression using Excel. 
• Explains how to interpret regression output. 
• Describes how to evaluate and compare different regression models. 

Session 6: How can you tailor the way you communicate your analytical results based on your objective and audience?

• Discusses the importance of understanding what your audience knows and cares about, and their core assumptions about the domain.
• Explains the importance of having a clear objective for your data communication, and being disciplined about sticking to it. 
• Provides tips for making your data communication more interesting. 

Session 7: How can you make an impactful data visualisation?

• Covers basic principles of data communications
• Discusses which common forms of data visualisation are best suited to particular circumstances. 

Session 8: How can we take what we’ve learned back to our organisations?

• Discusses more complex data visualisation issues. 
• Provides an overview of common organisational use cases for analytics. 
• Offers tips for incorporating what you’ve learned into your own work situation. 
• Is a final opportunity to ask about anything covered in the course.