Collecting Data

Students learn how to design a questionnaire without bias  to collect primary qualitative and quantitative data sets.  As learning progresses they use stratified sampling to determine sample size and how to design two-way tables and frequency trees to organise these data.

This unit takes place in Year 9 Term 4 and follows on from calculating statistical measures.


Collecting Data Lessons
Prerequisite Knowledge
  • Interpret and construct statistical diagrams for discrete and continuous data and know their appropriate use.
  • interpret, analyse and compare the distributions of data sets from univariate empirical distributions through:
    • appropriate graphical representation involving discrete, continuous and grouped data
    • appropriate measures of central tendency (median, mean, mode and modal class) and spread
Success Criteria
  • Infer properties of populations or distributions from a sample, whilst knowing the limitations of sampling.
  • apply statistics to describe a population
  • Interpret, analyse and compare the distributions of data sets from univariate empirical distributions through appropriate graphical representation involving discrete, continuous and grouped data.
Key Concepts
  • Students need to understand the benefits of using two-way tables as a means to exhaustively cover each outcome for multiple events and use them to calculate probabilities.
  • When designing questionnaires students need to consider time periods, multiple check boxes which do not overlap and the need to collect a wide ranging sample to reduce bias.
  • It is important to recognise the different statistical techniques that are used to analyse and represent qualitative, quantitative, discrete and continuous data.
Common Misconceptions
  • Students often have difficulty designing two-way tables.
  • When designing questionnaires common errors include:
    • No time period
    • Overlapping responses
    • Lack of ‘none’ or ‘other’ option.
    • Check boxes with unequal widths.
    • Double negative questions.
  • Students often try to represent continuous data using methods that are only applicable for discrete sets.

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