Data Handling

    OCR
    GCSE

    Data Handling requires the rigorous application of statistical techniques to process, represent, and analyse discrete and continuous data. Candidates must demonstrate competence in calculating measures of central tendency and dispersion, including the mean, median, interquartile range, and standard deviation, from both raw and grouped data. The topic demands the precise construction of graphical representations such as histograms with unequal class widths, cumulative frequency diagrams, and box plots to facilitate the comparison of distributions. High-level responses must evaluate the validity of sampling methods, identify bias, and interpret correlation within the context of the variables presented.

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    Objectives
    4
    Exam Tips
    4
    Pitfalls
    4
    Key Terms
    4
    Mark Points

    What You Need to Demonstrate

    Key skills and knowledge for this topic

    • Award M1 for correct calculation of Σ(f × x) when determining the estimated mean from grouped data
    • Award B1 for plotting points correctly within ±½ small square tolerance on scatter graphs or cumulative frequency diagrams
    • Credit responses that compare distributions by explicitly referencing both a measure of central tendency (median) and a measure of spread (IQR) in context
    • Award 1 mark for identifying that the area of a bar represents frequency in a histogram, not the height, when class widths are unequal

    Marking Points

    Key points examiners look for in your answers

    • Award M1 for correct calculation of Σ(f × x) when determining the estimated mean from grouped data
    • Award B1 for plotting points correctly within ±½ small square tolerance on scatter graphs or cumulative frequency diagrams
    • Credit responses that compare distributions by explicitly referencing both a measure of central tendency (median) and a measure of spread (IQR) in context
    • Award 1 mark for identifying that the area of a bar represents frequency in a histogram, not the height, when class widths are unequal

    Examiner Tips

    Expert advice for maximising your marks

    • 💡When comparing box plots, use the phrase 'on average' when comparing medians and 'more consistent' or 'less spread' when comparing IQRs
    • 💡For histogram questions, always create a 'Frequency Density' column immediately; never plot frequency on the y-axis for unequal class widths
    • 💡In probability tree diagrams, ensure the sum of probabilities on each set of branches equals 1; this is a quick check to avoid calculation errors
    • 💡When criticising a graph, look for non-linear scales, axes that do not start at zero, or missing labels

    Common Mistakes

    Pitfalls to avoid in your exam answers

    • Plotting cumulative frequency at the midpoint of the class interval instead of the upper bound
    • Calculating the mean of the frequencies rather than the weighted mean (Σfx / Σf) in grouped data questions
    • Stating there is 'no correlation' when points show a weak correlation, or failing to interpret the correlation in the context of the specific variables provided
    • Confusing frequency density with frequency when reading values from a histogram

    Study Guide Available

    Comprehensive revision notes & examples

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    Key Terminology

    Essential terms to know

    Measures of Central Tendency and Dispersion
    Graphical Representation (Histograms, Box Plots, Cumulative Frequency)
    Sampling Techniques, Bias, and Data Collection
    Bivariate Data and Correlation Analysis

    Likely Command Words

    How questions on this topic are typically asked

    Calculate
    Construct
    Interpret
    Compare
    Criticise
    Estimate

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