Students will be expected to develop and demonstrate confidence and competence in the understanding and application of statistical techniques, interpreting data and drawing conclusions in the solution of problems.
D1 Data
Content
Additional information
D1.1
appreciating the difference between qualitative and quantitative data
including the difference between discrete and continuous quantitative data
D1.2
appreciating the difference between primary and secondary data
including the use of secondary data that have been processed eg grouped
D1.3
collecting quantitative and qualitative primary and secondary data
D2 Collecting and sampling data
Content
Additional information
D2.1
inferring properties of populations or distributions from a sample, whilst knowing the limitations of sampling
D2.2
appreciating the strengths and limitations of random, cluster, stratified and quota sampling methods and applying this understanding when designing sampling strategies
appreciating that improving accuracy by removing bias and increasing sample size may cost/save both time and money
either from raw data or from cumulative frequency diagrams, stem-and-leaf diagrams or box plots
D3.2
interpreting these numerical measures and reaching conclusions based on these measures
D4 Representing data diagrammatically
Content
Additional information
D4.1
constructing and interpreting diagrams for grouped discrete data and continuous data, knowing their appropriate use and reaching conclusions based on these diagrams
including histograms with equal and unequal class intervals and cumulative frequency graphs, box and whisker plots, stem-and-leaf diagrams (including back-to-back)