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Demonstration: Decision-Making Under Uncertainty

Demonstration: Decision-Making Under Uncertainty

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Page 1: Demonstration: Decision-Making Under Uncertainty

Demonstration: Decision-Making Under Uncertainty

Page 2: Demonstration: Decision-Making Under Uncertainty

21.03 • Decision-Making Under Uncertainty

We will demonstrate the principles using a simple (but real) example.

• This is a personal investment decision.

• The outcome is uncertain.

• The potential gains/losses are real.

What is the most that you are willing to invest?

Page 3: Demonstration: Decision-Making Under Uncertainty

31.03 • Decision-Making Under Uncertainty

1. The selected participant plays the game once.

2. The cost to play is 20.

3. Payment is cash or check; no refunds.

Thumbtack Sweepstakes Rules

VISA MasterCard

4. I will “flip” a thumbtack.

5. The player calls: “Point up”“Point down”

6. If the call is correct, the player wins and keeps 100.

7. If the call is incorrect, the player wins nothing.

8. I keep the amount paid to play, regardless of the outcome.

Page 4: Demonstration: Decision-Making Under Uncertainty

41.03 • Decision-Making Under Uncertainty

A decision tree organizes and displays important factors of a decision in chronological sequence.

Invest

Don’t Invest

Decision

– 20

Decision

Correct Call

Incorrect Call

Uncertainty

Uncertainty

Outcome

100

0

0

– 20

Net Profit

80

0

Time

Page 5: Demonstration: Decision-Making Under Uncertainty

51.03 • Decision-Making Under Uncertainty

We define a decision as an “irrevocable” allocation of resources.

We have a certificate acknowledging this first “decision” of the day.

Page 6: Demonstration: Decision-Making Under Uncertainty

61.03 • Decision-Making Under Uncertainty

Probabilities quantify the player’s judgment about the likelihood of winning.

Correct Call

Incorrect Call

Probability = p

Probability = 1 – p

This uncertain situation is called a “deal” or a “lottery.”

Page 7: Demonstration: Decision-Making Under Uncertainty

71.03 • Decision-Making Under Uncertainty

To evaluate the tree, we must establish a value for the deal, assuming that we’ve made the investment.

Invest

Don’t Invest

Decision

0

– 20

Correct Call

Incorrect Call

Uncertainty Outcome

100

0

p =

1 – p =

Correct Call

Incorrect Call

Uncertainty Outcome

100

0

p =

1 – p =

Deal

To value the deal going forward, ignore the “sunk” 20; that’s behind us now.

Page 8: Demonstration: Decision-Making Under Uncertainty

81.03 • Decision-Making Under Uncertainty

The value of the deal is the player’s minimum selling price or “certain equivalent.”

The player is indifferent between having the deal or its certain equivalent.

Correct Call

Incorrect Call

Uncertainty Outcome

100

0

p =

1 – p =

Deal

CertainEquivalent

Page 9: Demonstration: Decision-Making Under Uncertainty

91.03 • Decision-Making Under Uncertainty

Another way to value the deal is to calculate its “expected value” (probability-weighted average).

The expected (or “mean”) value is the average return from each flip if it were repeated many times.

Correct Call

Incorrect Call

Uncertainty Outcome

100

0

p =

1 – p =

Deal

p x 100 + (1 – p) x 0

ExpectedValue

Page 10: Demonstration: Decision-Making Under Uncertainty

101.03 • Decision-Making Under Uncertainty

The difference between “expected value” and “certain equivalent” reflects attitude toward risk.

This is a matter of preference; there is no “correct” risk attitude.

MonetaryValue

RiskAverse

RiskNeutral

RiskPreferrin

g

Expected Value

Risk Attitude

Certain Equivalent

Page 11: Demonstration: Decision-Making Under Uncertainty

111.03 • Decision-Making Under Uncertainty

Is it worthwhile to gather information to reduce or to eliminate uncertainty?

Correct Call

Incorrect Call

Uncertainty Outcome

100

0

p =

1 – p =

No Info

Buy Information

Decision

?–?

What is the most that our player should pay for perfect information?

Page 12: Demonstration: Decision-Making Under Uncertainty

121.03 • Decision-Making Under Uncertainty

CertainEquivalent

Perfect information about the outcome of the flip guarantees winning the 100.

Correct Call

Incorrect Call

Uncertainty Outcome

100

0

p =

1 – p =

Decision

No Info

Buy PerfectInformation

100Correct Call

p = 1.0 –?

Here the value added by perfect information is 100 – the certain equivalent.How many opportunities do you have to buy perfect information in your business?

ValueAdded

Page 13: Demonstration: Decision-Making Under Uncertainty

131.03 • Decision-Making Under Uncertainty

Perfect information may not be available. Here are imperfect sources.

• Experiments—5 trial flips of the tack

• Opinion polls

• Experts

• Mathematical models

SURVEY

Page 14: Demonstration: Decision-Making Under Uncertainty

141.03 • Decision-Making Under Uncertainty

What is your call?

Point up? Point down?

Page 15: Demonstration: Decision-Making Under Uncertainty

151.03 • Decision-Making Under Uncertainty

We must distinguish between good decisions and good outcomes.

Preferred Results

Good Outcomes

Balances the probabilities of good and

bad outcomesconsistent with preferences

Good Decisions

40

–6

15

4

.6

.4

.7

.3

Page 16: Demonstration: Decision-Making Under Uncertainty

161.03 • Decision-Making Under Uncertainty

Making good decisions may not lead to good outcomes.

Good decisionsguarantee

good outcomes.

Decisions with Certainty

CorrectInvest

Don’t Invest

Good decisionsdo not guaranteegood outcomes.

Decisions with Uncertainty

Correct

Incorrect

Invest

Don’t Invest

The goal of decision analysis is make the best decisions in the face of uncertainty.

Page 17: Demonstration: Decision-Making Under Uncertainty

171.03 • Decision-Making Under Uncertainty

Several insights emerge from the demonstration.

• A decision is an irrevocable allocation of resources.

Invest

Buy Info.

... 30% ...• Probability is the quantitative language for communicating about uncertainty.

• Probabilities represent judgment, which includes experience and information.

• The value of an uncertain deal depends on its characteristics and one’s attitude toward risk.

• The economic value of gathering more information can be calculated before making a decision.

• We must distinguish between the quality of the decision and its outcome.