3.1 Analysis of data

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



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appreciating the difference between qualitative and quantitative data

including the difference between discrete and continuous quantitative data


appreciating the difference between primary and secondary data

including the use of secondary data that have been processed eg grouped


collecting quantitative and qualitative primary and secondary data


D2 Collecting and sampling data



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inferring properties of populations or distributions from a sample, whilst knowing the limitations of sampling



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

D3 Representing data numerically



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calculating/identifying mean, median, mode, quartiles, percentiles, range, interquartile range, standard deviation

either from raw data or from cumulative frequency diagrams, stem-and-leaf diagrams or box plots


interpreting these numerical measures and reaching conclusions based on these measures


D4 Representing data diagrammatically



Additional information


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)