Unit Quiz
Overview
Test your mastery of data analysis concepts including scatter plots, correlation, lines of best fit, predictions, and real-world applications. This comprehensive quiz covers all unit objectives.
Quiz Questions
Question 1: A scatter plot shows points that form a tight cluster rising from lower-left to upper-right. Describe the correlation.
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Answer: Strong positive correlation
Rising = positive direction. Tight cluster = strong relationship. Combined: strong positive correlation.
Question 2: The line of best fit for study hours vs. exam scores is y = 8x + 40. Predict the score for 5 hours of study.
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Answer: 80 points
y = 8(5) + 40 = 40 + 40 = 80.
Question 3: What does a correlation coefficient of r = 0.15 indicate?
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Answer: Very weak positive correlation (almost no linear relationship)
Values close to 0 indicate weak or no correlation. The positive sign shows a slight upward trend.
Question 4: A car depreciation model is V = -3000t + 25000. What was the car's original value?
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Answer: $25,000
When t = 0 (at purchase), V = -3000(0) + 25000 = $25,000. The y-intercept is the starting value.
Question 5: Data point (10, 45) has a residual of -3. What was the predicted y-value?
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Answer: Predicted y = 48
Residual = Actual - Predicted. So -3 = 45 - Predicted. Predicted = 48.
Question 6: Temperature vs. hot chocolate sales shows negative correlation. What happens to sales when temperature increases?
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Answer: Sales decrease
Negative correlation means as one variable increases, the other decreases. Warmer weather = fewer hot drinks sold.
Question 7: The equation y = 2.5x + 100 models revenue (y) based on customers (x). Interpret the slope in context.
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Answer: Each additional customer adds $2.50 to revenue
The slope is the rate of change: revenue increases by $2.50 for each 1-customer increase.
Question 8: Why might two variables have high correlation without one causing the other?
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Answer: A third variable (lurking/confounding variable) may cause both
Example: Ice cream sales and drownings correlate because hot weather (third variable) increases both.
Question 9: A data set has r = -0.85. Another has r = 0.6. Which shows a stronger linear relationship?
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Answer: r = -0.85 is stronger
Compare absolute values: |-0.85| = 0.85 > |0.6| = 0.6. The sign only indicates direction, not strength.
Question 10: Using y = 4x + 20 (where x is hours worked and y is items produced), how many hours are needed to produce 100 items?
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Answer: 20 hours
100 = 4x + 20. Subtract 20: 80 = 4x. Divide by 4: x = 20 hours.