Comparing Two Or More Distributions In Terms Of Their Shapes, Centre And Spread

Describing Any Overall Pattern And Any Striking Deviations From The Overall Pattern With Reference To Context

Relating The Choice Of Measures Of Central Tendency To The Shape Of The Data Distribution And The Context

Relating The Choice Of Measures Of Variability To The Shape Of The Data Distribution And The Context

Recognising A Statistical Question

Choosing And Interpreting The Scale In Graphs And Data Displays

Distinguishing Between Qualitative And Quantitative Data

Investigating And Describing Patterns Such As Clustering And Outliers

Representing Data Using Box-and-whisker Plots

Representing Data Using Dot Plots

Representing Data Using Histograms

Calculating Interquartile Range And Mean Absolute Deviation

Recognising That There Are Data Sets For Which Normalisation Cannot Be Done

Using Tables/technology To Estimate Areas Under The Normal Curve And Calculate Population Percentage.

Using The Mean And Standard Deviation Of A Data Set To Fit It To A Normal Distribution

Developing A Margin Of Error Through The Use Of Simulation Models

Explaining How Randomisation Relates To Sample Surveys, Experiments And Observational Studies

Recognising The Purposes Of And Differences Among Sample Surveys, Experiments And Observational Studies

Understanding Representative Samples And The Idea That Examining A Sample Can Lead To Useful Information About The Population

Using Data From A Sample Survey To Estimate A Population Mean Or Proportion