The purpose of this module is to provide introduction to data analysis and interpretation, sources of data, methods of data presentation and description, and how to conduct simple hypothesis tests and make inferences. On completion of the module, there should be an ability to draw on statistics appropriately to support arguments and be able to better understand and critique statistical analysis encountered in academic papers in subsequent courses.
At the end of this module you will be able to:
- Demonstrate an understanding for different levels of measurement and data types.
- Demonstrate an understanding and apply underlying probability principles and distribution examples.
- Demonstrate and be able to distinguish between descriptive and inferential statistical quantities in the theory and practice of statistics and in data analytics.
- Perform calculations and manipulate data via a suitable package using a range of analytical statistical techniques and interpret outcomes for a range of business scenarios.
- Define and calculate basic statistics used to describe distributions for given business scenarios.
- Present data in a meaningful way, using graphs and tables.
Demonstrate an ability to use data mining applications and provide business value metrics to the organisation.
Hours for module: 35 hours
How will the module be taught: Blended
Delivery sessions plan: 7 hours per week for 5 weeks
Audience for module: Would suit Business leaders, Middle managers, Someone wanting to improve their knowledge in data analysis for business decisions, Someone looking to develop an awareness of fundamental data analysis skills.
Course leader: Mark Barnett
Good to know: Parking onsite, refreshments etc.