Apply basic statistical analysis to support improvement in food and drink operations
Overview
This standard is about the skills and knowledge needed to apply the basic statistical analysis as part of your organisation's drive to increase the effectiveness and productivity of food and drink operations. This is important in the achievement of excellence and the success of manufacture, processing and supply across the food and drink supply chain.
You will need to apply and understand basic statistics, and provide an informed approach to the analytical techniques and procedures used within your organisation. You will need to show and know how to present findings of analysis to relevant people within the organisation, including management colleagues. You will need to know how to comply with your company policy for improvement, take responsibility for your actions, and refer any issues outside of the limit of your authority to others.
This standard is for you if you work in food and drink operations including, manufacturing, processing, packing or supply chain activities. You may have responsibilities for aspects of organisational improvement in a team leadership or management role.
Performance criteria
You must be able to:
Knowledge and Understanding
You need to know and understand:
- the organisation's improvement vision, strategy, objectives and the reasons for implementation of improvement programmes
- how the health, safety and hygiene requirements of a work area can influence the process of analysis
- the food and drink operational activity that is being analysed
- how to use basic statistical techniques
- the meaning of `variation', and how this can be detected with statistics
- how variation can affect a process
- why data points are important to statistics
- why we need to use basic statistics
- the meaning of the terms
population' and
sample' when applied to basic statistics - distribution curves and the properties of a normal curve
- the creation and use of charts and diagrams
- how to calculate mean, median, mode, standard deviation, range and variance
- the difference between descriptive and inferential statistics
- levels of authority linked to problem resolution
- the use of statistical measurement and meanings, abbreviations and symbols in the collection of performance data
- how to use graphical data representation in data analysis
- how to interpret and evaluate data
- how to present analysis findings
- how to make recommendations about improvement opportunities and targets