Decision Trees

A decision tree is a _____ used to help managers make decisions.

• scientific model

• mathematical model

• geographical model

• super model

A decision tree uses _________ to calculate likely outcomes.

• stakeholder information

• facts and statistics

• estimates and probabilities

• shareholder data

A decision tree helps to decide whether the _____from a decision is worthwhile.

• net gain

• net present value

• payback period

• future value of cash

A decision tree starts with a ____ to be made and the options that can be taken.

• dividend

• decision

• net present value assumption

• payback period estimate

Don't forget that there is always an option to decide _____.

• to choose the project that is not worthwhile

• to add further options

• to choose both options

• to do nothing!

Net gain is calculated by _____ the expected value of each outcome and deducting the costs associated with the decision.

• deducting

• adding together

• multiplying

• dividing

BENEFITS OF USING DECISION TREES include:

• Uses quantitative data only – ignores qualitative aspects of decisions

• It is based on assumptions and estimates

• Choices are set out in a logical way

• Assignment of probabilities and expected values prone to bias

BENEFITS OF USING DECISION TREES include:

• Decision-making technique doesn’t necessarily reduce the amount of risk

• Uses quantitative data only – ignores qualitative aspects of decisions

• Probabilities are just estimates – always prone to error

• Potential options & choices are considered at the same time

BENEFITS OF USING DECISION TREES include:

• Probabilities are just estimates – always prone to error

• Use of probabilities enables the “risk” of the options to be addressed

• Uses quantitative data only – ignores qualitative aspects of decisions

• Assignment of probabilities and expected values prone to bias

BENEFITS OF USING DECISION TREES include:

• Likely costs are considered as well as potential benefits

• Probabilities are just estimates – always prone to error

• Uses quantitative data only – ignores qualitative aspects of decisions

• Assignment of probabilities and expected values prone to bias