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6 Forecasting
36問 • 1年前
  • Sab Sescon
  • 通報

    問題一覧

  • 1

    Is the projection of future sales, revenues, earnings, costs, and other possible variables that are helpful in the firm's operation

    forecasting

  • 2

    To reduce the risk or uncertainty that the firm will face in making a decision

    objective of forecasting

  • 3

    User of forecast

    top management production manager purchasing manager marketing manager finance manager human resource manager colleges and universities

  • 4

    Are generally used in forecasting when data, necessary to use time series or causal model, are not available

    qualitative methods of forecasting

  • 5

    Qualitative models of forecasting

    delphi market research salesforce opinion, judgement or grassroot forecast historical analogy

  • 6

    Experts panel respond to a series of questionnaires. They have access to all information

    delphi

  • 7

    Range of forecast: delphi

    long range

  • 8

    Range of forecast: market research

    short or medium range

  • 9

    Range of forecast: salesforce opinion, judgement or grassroot forecast

    short range

  • 10

    Range of forecast: historical analogy

    long range

  • 11

    Relative cost: delphi

    medium

  • 12

    Relative cost: market research

    low

  • 13

    Relative cost: historical analogy

    low to medium

  • 14

    Relative cost: salesforce opinion, judgement or grassroot forecast

    low

  • 15

    Time to forecast: delphi

    high

  • 16

    Use of survey questionnaire for testing the hypothesis regarding consumer behavior

    market research

  • 17

    Time to forecast: market research

    high

  • 18

    Life cycle of similar products or services are compared.

    historical analogy

  • 19

    Demand pattern for each stage of life cycle as assumed to be analogous for comparable

    historical analogy

  • 20

    Time to forecast: historical analogy

    quick

  • 21

    Projection of estimates by grassroot level people like salesforce who are close to consumers

    salesforce opinion, judgement or grassroot forecast

  • 22

    Time to forecast: salesforce opinion, judgement or grassroot forecast

    quick and frequent

  • 23

    Application: new product and new technology

    delphi

  • 24

    Application: new product, references of consumers, pre-poll forecast

    market research

  • 25

    Application: new products and new series

    historical analogy

  • 26

    Application: estimate of medicine of a particular type or government contract which may be procured

    salesforce opinion, judgement or grassroot forecast

  • 27

    Accuracy: delphi

    fair to good

  • 28

    Accuracy: market research

    excellent in short ranges. fair in long term range.

  • 29

    Accuracy: historical analogy

    poor to fair

  • 30

    Accuracy: salesforce opinion, judgement or grassroot forecast

    fair to poor

  • 31

    Models of time series analysis

    simple moving average weighted moving average exponential smoothing

  • 32

    How to solve for simple moving average 3 week

    start with the first three weeks and add all of those divide the sum with three and you get the forecast for the fourth week

  • 33

    How to get the weighted moving average 3 week

    start with the three week in descending order, following the three weighted average just starting from big to small multiply it with their respective weighted moving averages and add all the three week averages

  • 34

    How to get exponential smoothing

    start with the second week by copying the sales of the first week get the alpha and multiply it with the second week sale get the alpha again and solve it by 1 - alpha then multiply it by the forecast of the second week add both of the numbers and get the forecast for the third week

  • 35

    How to get the mean absolute deviation

    u minus the forecast from the sales to get the error after getting the error of all the weeks add it all up and divide it with the number of weeks with forecasts

  • 36

    How to compute for mean square error

    square the amount in the error column or mad and divide it with the number of weeks with forecasts

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    問題一覧

  • 1

    Is the projection of future sales, revenues, earnings, costs, and other possible variables that are helpful in the firm's operation

    forecasting

  • 2

    To reduce the risk or uncertainty that the firm will face in making a decision

    objective of forecasting

  • 3

    User of forecast

    top management production manager purchasing manager marketing manager finance manager human resource manager colleges and universities

  • 4

    Are generally used in forecasting when data, necessary to use time series or causal model, are not available

    qualitative methods of forecasting

  • 5

    Qualitative models of forecasting

    delphi market research salesforce opinion, judgement or grassroot forecast historical analogy

  • 6

    Experts panel respond to a series of questionnaires. They have access to all information

    delphi

  • 7

    Range of forecast: delphi

    long range

  • 8

    Range of forecast: market research

    short or medium range

  • 9

    Range of forecast: salesforce opinion, judgement or grassroot forecast

    short range

  • 10

    Range of forecast: historical analogy

    long range

  • 11

    Relative cost: delphi

    medium

  • 12

    Relative cost: market research

    low

  • 13

    Relative cost: historical analogy

    low to medium

  • 14

    Relative cost: salesforce opinion, judgement or grassroot forecast

    low

  • 15

    Time to forecast: delphi

    high

  • 16

    Use of survey questionnaire for testing the hypothesis regarding consumer behavior

    market research

  • 17

    Time to forecast: market research

    high

  • 18

    Life cycle of similar products or services are compared.

    historical analogy

  • 19

    Demand pattern for each stage of life cycle as assumed to be analogous for comparable

    historical analogy

  • 20

    Time to forecast: historical analogy

    quick

  • 21

    Projection of estimates by grassroot level people like salesforce who are close to consumers

    salesforce opinion, judgement or grassroot forecast

  • 22

    Time to forecast: salesforce opinion, judgement or grassroot forecast

    quick and frequent

  • 23

    Application: new product and new technology

    delphi

  • 24

    Application: new product, references of consumers, pre-poll forecast

    market research

  • 25

    Application: new products and new series

    historical analogy

  • 26

    Application: estimate of medicine of a particular type or government contract which may be procured

    salesforce opinion, judgement or grassroot forecast

  • 27

    Accuracy: delphi

    fair to good

  • 28

    Accuracy: market research

    excellent in short ranges. fair in long term range.

  • 29

    Accuracy: historical analogy

    poor to fair

  • 30

    Accuracy: salesforce opinion, judgement or grassroot forecast

    fair to poor

  • 31

    Models of time series analysis

    simple moving average weighted moving average exponential smoothing

  • 32

    How to solve for simple moving average 3 week

    start with the first three weeks and add all of those divide the sum with three and you get the forecast for the fourth week

  • 33

    How to get the weighted moving average 3 week

    start with the three week in descending order, following the three weighted average just starting from big to small multiply it with their respective weighted moving averages and add all the three week averages

  • 34

    How to get exponential smoothing

    start with the second week by copying the sales of the first week get the alpha and multiply it with the second week sale get the alpha again and solve it by 1 - alpha then multiply it by the forecast of the second week add both of the numbers and get the forecast for the third week

  • 35

    How to get the mean absolute deviation

    u minus the forecast from the sales to get the error after getting the error of all the weeks add it all up and divide it with the number of weeks with forecasts

  • 36

    How to compute for mean square error

    square the amount in the error column or mad and divide it with the number of weeks with forecasts