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E5 Data analysis techniques and the learning curve

اے سی سی اے · ایکسپرٹیز لیول میں نیا · 8 سوالات

نام: ____________________   تاریخ: ____________

  1. A correlation coefficient of +0.95 shows:

    • A A perfect negative relationship
    • B A weak negative relationship
    • C A strong positive linear relationship
    • D No relationship
  2. A regression forecast is most reliable when:

    • A The correlation is strong and the forecast is within the range of the data
    • B The forecast is far outside the data
    • C The relationship has changed
    • D There are only two points
  3. In an 80 percent learning curve, what happens when cumulative output doubles?

    • A The total time falls to 80%
    • B The time of the last unit falls by 80%
    • C Nothing
    • D The cumulative average time per unit falls to 80% of its previous level
  4. The first unit takes 100 hours and the learning rate is 80 percent. What is the total time for the first 4 units?

    • A 320 hours
    • B 64 hours
    • C 256 hours
    • D 400 hours
  5. Using an 80 percent curve with a first unit of 100 hours, the total for 3 units is 210.6 hours and for 4 units is 256 hours. How long does the fourth unit take?

    • A 45.4 hours
    • B 80 hours
    • C 64 hours
    • D 51.2 hours
  6. What is the steady state in the learning curve?

    • A The point of maximum learning
    • B The break-even point
    • C The first unit
    • D The point at which the learning effect ends and the time per unit is constant
  7. Which method separates fixed and variable costs using the highest and lowest activity levels?

    • A Time series
    • B The learning curve
    • C The high-low method
    • D Regression
  8. Which of these is a limitation of data analysis techniques for forecasting?

    • A They need no data
    • B They rely on past data that may not predict the future
    • C They use future data
    • D They can never be used

جوابی کلید

1. C, 2. A, 3. D, 4. C, 5. A, 6. D, 7. C, 8. B

  1. Values close to +1 mean a strong positive relationship.

  2. Extrapolation is risky.

  3. This is the cumulative average time model.

  4. Cumulative average for 4 units = 100 x 0.8 x 0.8 = 64. Total = 256.

  5. 256 - 210.6 = 45.4.

  6. Later output uses the steady state time.

  7. It uses only two points.

  8. Data quality and change affect reliability.