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Science · Grade 7

Experimental Design and Data Quality

Learners turn observations into testable questions, hypotheses and predictions, then design fair tests with one independent variable, a measured dependent variable, controlled variables and a control group. They use simulations to see why repeated trials and larger, representative samples matter, summarise repeated measurements with mean, median and range, decide what to do with outliers, and judge data quality by separating accuracy from precision and spotting bias.

  • 5 lessons
  • About 115 minutes
  • Experimental design and data quality check: 10 questions
  • Ways to answer: fill in the blanks, choose an answer, highlight a text, match pairs, type a number and place on a number line
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What learners will discover

  • Distinguish a testable question, a hypothesis (a testable explanation) and a prediction (an if–then statement of expected results), and identify the independent, dependent and controlled variables and the control group in an investigation.
  • Explain, using simulation data, why repeated trials and larger, representative samples give more reliable results than a single trial or a small or biased sample.
  • Summarise repeated measurements with mean, median and range, and decide how to treat an outlier with a recorded reason.
  • Distinguish accuracy from precision, tell systematic error from random variation, and identify sources of bias and the design choices that reduce them.

Lessons

  1. Questions, hypotheses and predictions 8 steps4 practiceabout 18 min
  2. Variables, controls and fair tests 9 steps5 practiceabout 22 min
  3. Repeated trials and sample size 9 steps4 practiceabout 20 min
  4. Summarising data: mean, median, range and outliers 9 steps6 practiceabout 22 min
  5. Accuracy, precision and bias 8 steps5 practiceabout 20 min
  6. Experimental design and data quality check 10 questions at the end

Keep exploring

Games to practice with

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Guide for grown-ups