Content-specific conceptual understandings
Concepts of population, sample, random sample, discrete and continuous data.
This is designed to cover the key questions that students should ask when they see a data set/analysis.
Reliability of data sources and bias in sampling.
Dealing with missing data, errors in the recording of data.
Interpretation of outliers.
Outlier is defined as a data item which is more than 1.5 × interquartile range (IQR) from the nearest quartile.
Awareness that, in context, some outliers are a valid part of the sample but some outlying data items may be an error in the sample.
Sampling techniques and their effectiveness.
Simple random, convenience, systematic, quota and stratified sampling methods.