8 Summary

In this module, you have been introduced to the basics of data collection, data management and data analysis, including descriptive and inferential analyses.

You have seen that data collection and management are two key stages of the information cycle, as they determine the quality of AMR data. Without following best practice in these areas, we would not be able to work with reliable data, and therefore any data analysis effort would be of limited use. You have learned the key statistics used to summarise categorical and numeric variables and some of the possible applications to AMR data analysis. Last, you have been introduced to the basics of statistics for AMR data analysis.

You should now be able to:

• describe components of the information cycle
• list and explain principles of best practice for data collection
• list and explain principles of best practice for data management
• explain the difference between descriptive and inferential statistics
• calculate measures of central tendency
• understand concepts related to hypothesis testing
• interpret reported findings from a hypothesis test, including strength of statistical evidence, and potential sources of error and bias.

Now that you have completed this module, consider the following questions:

• What is the single most important lesson that you have taken away from this module?
• How relevant is it to your work?
• Can you suggest ways in which this new knowledge can benefit your practice?

When you have reflected on these, go to your reflective blog [Tip: hold Ctrl and click a link to open it in a new tab. (Hide tip)]   and note down your thoughts.