Lesson 2c.03

2c.03 Comment on outliers with reference to the original data Quiz: Pearson Edexcel Statistics, Unit 2

20 questions

Written by Revision Ninja · Last reviewed 11 October 2026

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Lesson 2c.03, Comment on outliers with reference to the original data: 20 multiple choice questions for the Pearson Edexcel GCSE Statistics (1ST0), Unit 2: Processing, representing and analysing data, written with Revision Ninja.

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The 20 questions

  1. What common issue besides genuine extreme values can cause data outliers?

    • Large sample size
    • Class width
    • Recording errors
    • Using the median

  2. What should you check before removing an outlier from a data set?

    • Original records
    • Class frequency
    • New sample size
    • The mode

  3. A height of 2.5 m appears alongside heights around 1.5 m. What is this likely to be?

    • Genuine giant
    • Normal variation
    • Data entry error
    • Modal height

  4. How should genuine, non-erroneous outliers normally be treated in analysis?

    • Ignored completely
    • Kept and discussed
    • Changed to median
    • Deleted instantly

  5. What is the best way to handle a data outlier explained by a major event?

    • Double it
    • Average it
    • Delete it
    • Keep it

  6. What action checks whether an outlier is a true value or recording mistake?

    • Median split
    • Range test
    • Source check
    • Mean shift

  7. What is the most likely cause of a human age value of 220?

    • Valid anomaly
    • Natural growth
    • Recording error
    • Genuine peak

  8. Which summary statistic is most noticeably affected when removing an outlier from a small sample?

    • Range
    • Median
    • Mean
    • Mode

  9. Which outlier in a data set is most likely to be genuine?

    • Temperature five thousand
    • Age two hundred
    • High house price
    • Negative height

  10. What recording error turns the number 4.5 into 45?

    • Added zero
    • Swapped digits
    • Misplaced decimal
    • Rounded up

  11. Why should outliers be explicitly discussed in a statistical report?

    • Zero variance
    • Always illegal
    • Required sorting
    • Averages affected

  12. What is the best comment on a reaction time of 0.02 seconds among data around 0.3 seconds?

    • Perfect score
    • Genuine record
    • Expected value
    • Implausible error

  13. Which statement correctly describes the nature of statistical outliers?

    • Always mistakes
    • Never relevant
    • Must be deleted
    • Can be genuine

  14. Why might investigating an unexpected outlier be valuable in a health study?

    • Improves typing speed
    • Removes bias
    • Increases sample size
    • Reveals unusual case

  15. What is the most likely cause of a value like 9999 in a column of normal data?

    • True maximum
    • Running total
    • Placeholder code
    • Mean value

  16. What is the correct approach for a weight of 150 kg in a dataset averaging 60 kg?

    • Replace with zero
    • Delete instantly
    • Ignore completely
    • Check original

  17. What should be done when an unusually high exam mark appears in a class set?

    • Subtract average
    • Check records
    • Lower grade
    • Discard paper

  18. What key detail must follow the discussion of an outlier in a statistical report?

    • Graph dimensions
    • Sample formula
    • Data collector name
    • Decision and reason

  19. What should a report include if analysts treat the same outlier differently?

    • Analyst salaries
    • Effect on average
    • Software version
    • Only the mean

  20. What must be done to a genuine measurement recorded in different units before analysis?

    • Ignore measurement
    • Delete data point
    • Convert units
    • Calculate median

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