Lesson 3p.10

3p.10 Comment on the differences between experimental and theoretical values in terms of... Quiz: Pearson Edexcel Statistics, Unit 3

20 questions

Written by Revision Ninja · Last reviewed 11 October 2026

In partnership with Revision Ninja

Lesson 3p.10, Comment on the differences between experimental and theoretical values in terms of...: 20 multiple choice questions for the Pearson Edexcel GCSE Statistics (1ST0), Unit 3: Probability, written with Revision Ninja.

Host it live on the board and students join with a game code on their own devices, or revise alone with Free Play. The answers are revealed in the game.

Host this setFree Play

The 20 questions

  1. Which comparison helps check for data bias using a probability model?

    • Observed versus expected
    • Range versus IQR
    • Sample versus quota
    • Mean versus median

  2. What is the requirement for formal significance tests in GCSE Statistics?

    • Not required
    • Mandatory for higher tier
    • Required for normal distribution
    • Required for binomial only

  3. In a binomial experiment with n = 10 and p = 0.5, what is the expected number of successes?

    • 10
    • 2.5
    • 5
    • 0.5

  4. What observation may suggest potential bias in experimental results?

    • Exact match
    • Small variation
    • Large discrepancy
    • Zero difference

  5. What is the appropriate action when experimental and theoretical values differ slightly?

    • Retract study
    • Reject hypothesis
    • Mandatory t-test
    • No formal test

  6. Why do statisticians compare experimental results with theoretical probabilities?

    • Check consistency
    • Eliminate all errors
    • Calculate averages
    • Prove absolute truth

  7. Observed 3 heads in 10 tosses, expected 5 under a binomial model. What is the observed minus expected difference?

    • -8
    • 2
    • -2
    • 3

  8. What factor can cause observed binomial results to differ from theoretical expectations?

    • Perfect randomness
    • Biased equipment
    • Correct probability
    • Large sample size

  9. A binomial model has n = 8 and p = 0.25. What is the expected number of successes?

    • 2
    • 8
    • 0.25
    • 6

  10. In 12 trials with p=0.5, a model expects 6 successes but 9 are observed. What does this suggest?

    • Zero error
    • Possible bias
    • Pure certainty
    • Guaranteed fraud

  11. A fair coin is tossed 80 times. What are the expected heads?

    • 0.5
    • 8
    • 40
    • 80

  12. A binomial model predicts 30 successes but 20 are observed. What is the observed minus expected difference?

    • 10
    • -10
    • -30
    • 50

  13. When observed survey results vastly exceed expected values, what should be suspected?

    • Perfect accuracy
    • Random fluctuation
    • Zero error
    • Sampling bias

  14. A binomial model has n = 10 and p = 0.6. What are the expected successes?

    • 60
    • 4
    • 0.6
    • 6

  15. If observed successes are lower than expected in trials, what could be the cause?

    • Absolute certainty
    • Fixed parameter
    • Chance or bias
    • Guaranteed error

  16. Which method can be used to find expected frequencies from a binomial model?

    • Frequency polygon
    • Bar chart
    • Pie chart
    • Pascal triangle

  17. Why does a single unusual experimental result not definitively prove bias?

    • Model failure
    • Chance variation
    • Biased sample
    • Calculated error

  18. Observed 16 heads in 20 tosses with p=0.5. What is the correct conclusion?

    • Possible bias
    • Proven fraud
    • Definite certainty
    • Expected outcome

  19. Observed successes exceed binomial expectations. What are the two main possible reasons?

    • Theory or fact
    • Sample or total
    • Mean or median
    • Chance or bias

  20. What is the primary purpose of comparing experimental data with theoretical models?

    • Prove absolute certainty
    • Eliminate all variables
    • Calculate exact means
    • Assess chance versus bias

All Pearson Edexcel Statistics quizzes