Unit 4: Statistics and Probability
Topic 4.10: Prediction from Regression Questions
Practice 16 exam-style questions for IB Math AA SL Topic 4.10. Review the question stems below, then unlock the full Question Bank to access markschemes, model answers, and AI grading.
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Write down the predicted value of when .
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The regression line of weight y (kg) on age x (months) for puppies is . Predict the weight of a puppy aged 5 months.
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The regression line of weight y (kg) on age x (months) for puppies is y = 1.8x + 2. Predict the weight of a puppy aged 5 months.
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A regression line y = −0.4x + 95 models exam score y against hours of part-time work x. Predict the score for a student working 10 hours.
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The regression line of x on y is x = 0.6y − 4. Use it to estimate x when y = 30.
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The regression line of x on y is . Use it to estimate x when .
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A regression line models exam score y against hours of part-time work x. Predict the score for a student working 10 hours.
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Data on house size x (m2) was collected from 60 to 200 m2. A regression line predicts price. Comment on the reliability of predicting the price of a 120 m2 house and of a 320 m2 house.
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A regression line is found for data with correlation coefficient . A prediction is made for an x-value inside the data range. Comment on its reliability.
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A regression line of temperature on time x (hours after 6 am) is , found from data for .
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A regression line is found for data with correlation coefficient r = 0.28. A prediction is made for an x-value inside the data range. Comment on its reliability.
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A study of plant height y (cm) against fertiliser x (g) gives with , from data for g.
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Data on house size was collected from 60 to . A regression line predicts price. Comment on the reliability of predicting the price of house and of house.
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A study of plant height y (cm) against fertiliser x (g) gives y = 3.2x + 12 with r = 0.97, from data for 0 ≤ x ≤ 20 g.
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A regression line of temperature y (°C) on time x (hours after 6 am) is y = 1.5x + 9, found from data for 0 ≤ x ≤ 8.
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Explain why you should not use a regression line of y on x to predict an x-value from a given y-value.
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