Operational Management Practice Exam: Quiz!

30 Questions | Total Attempts: 669

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Operational Management Practice Exam: Quiz!

Do you know anything about operational management, and would you be interested in trying this quiz? Operational management is an area concerned with designing and regulating production and recreating business operations in the production of goods and services. It entails the responsibility of safeguarding the business operations using a few resources when necessary and meeting customer requirements. Try this quiz now and check your knowledge about operation management.


Questions and Answers
  • 1. 
    Forecasts
    • A. 

      Become more accurate with longer time horizons

    • B. 

      Are more accurate for individual items than for group of items

    • C. 

      Are rarely perfect

    • D. 

      All of the above

    • E. 

      None of the above

  • 2. 
    Exponential smoothing is a form of weighted averaging.
    • A. 

      True

    • B. 

      False

  • 3. 
    The following equation is used to predict quarterly demand: Yt = 300 - 2t where = 1 in the second quarter of last year. quarterly seasonal indices are Q1 = 1.5; Q = .8; Q3 = 1.1; and Q4 = .6, What is the seasonally adjusted forecast for the third quarter of this year? (show all your work)
    • A. 

      314.6

    • B. 

      316.6

    • C. 

      316.8

    • D. 

      314.8

    • E. 

      None of the above

  • 4. 
    In order to increase the responsiveness of a forecast made using the simple moving average technique, the number of data points in the average (n) should be
    • A. 

      Decreased

    • B. 

      Increased

    • C. 

      Multiplied by a larger alpha

    • D. 

      Multiplied by a smaller alpha

    • E. 

      None of the above

  • 5. 
    Which of the following is not a type of judgmental forecasting?
    • A. 

      Executive opinions

    • B. 

      Sales force opinions

    • C. 

      Consumer surveys

    • D. 

      The delphi method

    • E. 

      Time series analysis

  • 6. 
    Forecasts for groups of items tend to be less accurate than forecasts for individual items because forecasts for individual items don't include as many influencing factors.
    • A. 

      True

    • B. 

      False

  • 7. 
    The mean absolute deviation (mad) is used to
    • A. 

      Estimate the trend line

    • B. 

      Eliminate forecast errors

    • C. 

      Measure forecast accuracy

    • D. 

      Seasonally adjust the forecast

    • E. 

      All of the above

  • 8. 
    St month's actual demand is the same as a forecast for this month if the forecast is based on
    • A. 

      Exponential smoothing (or weighting) with aplha equal to .5

    • B. 

      Naive forecast

    • C. 

      Weighted moving average

    • D. 

      Moving average with a period of at least two months

  • 9. 
    Forecast is a statement about the future value of a variable of interest.
    • A. 

      True

    • B. 

      False

  • 10. 
    Error-difference between the actual value and the value that was predicted for a given period.
    • A. 

      True

    • B. 

      False

  • 11. 
    Mean absolute deviation (MAD)
    • A. 

      The average of squared forecast errors

    • B. 

      The average absolute forecast error

  • 12. 
    Mean squared error (MSE)
    • A. 

      The average of squared forecast errors

    • B. 

      The average absolute forecast error

  • 13. 
    Mean absolute percent error (MAPE) is the average absolute percent error.
    • A. 

      True

    • B. 

      False

  • 14. 
    Judgmental forecasts
    • A. 

      Forecasting technique that uses explanatory variables to predict future demand

    • B. 

      Forecasts that project patterns identified in recent time series observations

    • C. 

      Forecasts that use subjective inputs such as opinions from consumer surveys, sales staff, managers, executives, and experts

  • 15. 
    Times series forecasts
    • A. 

      Forecasting technique that uses explanatory variables to predict future demand

    • B. 

      Forecasts that project patterns identified in recent time series observations

    • C. 

      Forecasts that use subjective inputs such as opinions from consumer surveys, sales staff, managers, executives, and experts

  • 16. 
    Associative model
    • A. 

      Forecasting technique that uses explanatory variables to predict future demand

    • B. 

      Forecasts that project patterns identified in recent time series observations

    • C. 

      Forecasts that use subjective inputs such as opinions from consumer surveys, sales staff, managers, executives, and experts

  • 17. 
    Delphi method is an iterative process in which managers and staff complete a series of questionnaires, each developed from the previous one, to achieve a consensus forecast.
    • A. 

      True

    • B. 

      False

  • 18. 
    Trend
    • A. 

      Residual variations after all other behaviors are accounted for

    • B. 

      Caused by unusual circumstances, not reflective of typical behavior

    • C. 

      Wavelike variations lasting more than one year

    • D. 

      Short term regular variations related to the calendar or time of day

    • E. 

      A long term upward or downward movement in data

  • 19. 
    Seasonality
    • A. 

      Residual variations after all other behaviors are accounted for

    • B. 

      Caused by unusual circumstances, not reflective of typical behavior

    • C. 

      Wavelike variations lasting more than one year

    • D. 

      Short term regular variations related to the calendar or time of day

    • E. 

      A long term upward or downward movement in data

  • 20. 
    Cycle
    • A. 

      Residual variations after all other behaviors are accounted for

    • B. 

      Caused by unusual circumstances, not reflective of typical behavior

    • C. 

      Wavelike variations lasting more than one year

    • D. 

      Short term regular variations related to the calendar or time of day

    • E. 

      A long term upward or downward movement in data

  • 21. 
    Random variations
    • A. 

      Residual variations after all other behaviors are accounted for

    • B. 

      Short term regular variations related to the calendar or time of day

    • C. 

      Wavelike variations lasting more than one year

    • D. 

      Short term regular variations related to the calendar or time of day

    • E. 

      A long term upward or downward movement in data

  • 22. 
    A forecast for any period that equals the previous period that equals the previous period's actual value.
    • A. 

      Naive forecast

    • B. 

      Delphi method

    • C. 

      Moving average

  • 23. 
    Moving average is a technique that averages a number of recent actual values, updated as new values become available.
    • A. 

      True

    • B. 

      False

  • 24. 
    The weighted average is more recent values in a series are given more weight in computing a forecast.
    • A. 

      True

    • B. 

      False

  • 25. 
    Exponential smoothing is a weighted averaging method based on the previous forecast plus a percentage of the forecast error.
    • A. 

      True

    • B. 

      False