Class Notes (1,100,000)
CA (640,000)
UTSG (50,000)
PSY (4,000)
PSY270H1 (200)
Lecture 10

PSY270H1 Lecture Notes - Lecture 10: Pay Television, Phineas Gage, Stomach Cancer


Department
Psychology
Course Code
PSY270H1
Professor
Gillian Rowe
Lecture
10

This preview shows pages 1-3. to view the full 10 pages of the document.
LECTURE 10: DECISION MAKING
AND PROBLEM AND SOLVING
OUTLINE:
Decisions making and Theories
Factors Influencing Decision making
What is Problem Solving?
Insight Problems and Functional Fixedness
Overconfidence
Conformational Bias and High Sight Bias
Neural basis of thinking
DECISION MAKING AND THEORIES
Decision making is the reasoning about choices under conditions of uncertainty.
“Normative” theories in decision making are theories about ideal performance
under ideal circumstance. Usually used in marketing and business school. This
normative theory is obviously not realistic.
In expected utility theory we try to maximize “utility”. Expected value is the
largest objective payoff. Expected utility is the greatest personal value that it
has for you.
oDon’t need to memorize this formula: expected utility/ value= (prob. of
outcome) x (value of outcome).
oExample: deciding whether to buy a lottery ticket; its $5, 1/100 chance of
winning $200 x .01=$2. <$5 is not worth it, except maybe if it involves
games. The general idea is whether or not you will get more.
oLimitations of utility theories: to what extent does human decision making
follow the predictions from utility theories? Under many situations, utility
theories do not fully describe decision making. Emotions, personal choice
etc are also involved.

Only pages 1-3 are available for preview. Some parts have been intentionally blurred.

FACTORS INFLUENCING DECISION MAKING
1. Framing of outcomes or questions. Example: how a doctor presents a
suggestion to surgery, or how commercials are presented—these help us make
decisions
a. Framing Effect: the same information presented differently can affect
people’s choices.
EXPERIMENT: Tversky & Kahneman, 1987
Problem 1: positive frame: the outbreak of unusual disease is expected to kill 600
people.
-If Program A is adopted, 200 people will be saved
-If program B is adopted, there is a 1/3 probability that 600 will be saved, and 2/3
probability that no people will be saved.
Problem 2: negative frame: the outbreak of unusual disease is expected to kill 600
people.
-If Program A is adopted, 400 people will die
-If program B is adopted, there is a 1/3 probability that nobody will die, and 2/3
probability that 600 people will die.
Framing of outcomes (Tversky & Kahneman, 1987). Identical problem was posed 2
ways. In problem 1, 72% choose option A and inn problem 2, 78% choose option B. A
really focuses on a large number of people dying, but B only talks about a small number
of people dying. But they are both the same problem. It is how they are presented that
is important.
EXPERIMENT: Ronnlund et al (2005). They examined the impact of framing on risky
decisions; manipulated age (young/old) and type of framing (positive/ negative). The
participants read one of 2 scenarios and selected either a risky or certain outcome.
Conducted at same time, and framed in similar ways to each age group. Scenario:
Suppose you have invested in stock equivalent to the sum of $60,000 in a company
that just filed a claim for bankruptcy. They offer two alternatives in order to save some
of the invested money: Which choice would you make?

Only pages 1-3 are available for preview. Some parts have been intentionally blurred.

Positive Framing : If Program A is adopted, $20,000 will be saved (certain outcome). If
Program B is adopted, there is a 1/3 probability that $60,000 will be saved and a 2/3
probability that no money will be saved (risky outcome)
Negative Framing: If program A is adopted $40,000 will be lost (certain outcome). If
program B is adopted, there is a 1/3 probability that no money will be lost, and 2/3
probability that $60,000 will be saved (risky outcome).
RESULTS: 70% of both age groups chose positive. There is however a slight tendency
for the older adults to choose the negative.
2. Heuristics: rules of thumb. The proceedings to a solution by rules hat are only
loosely defined. Generally produce a good decision but are not guaranteed to.
You are not really aware of it. Sometimes it helps us make good decisions by
influencing us that we are not aware of.
a. Tversky and Kahneman’s influential proposal: people are more likely to
make decisions based on heuristics than utility theories suggest.
b. Though often useful, they can bias your decisions; it helps us do things
fast.
c. Major heuristics :
Availability Heuristic: strategy based on how easily relevant example can be
retrieved from memory
o. Example of ‘bias’ due to this heuristic: in the English language is ‘L more
likely appear in the first position of a worked or the third position of a
word?
oExample of bias due to media exposure (also marketing): which pair is
more likely cause of death in the US? Thus it is very hard of being
resentful to information from media.
diabetes vs. homicide
tornado vs. lightning
Car accident v. stomach cancer
You're Reading a Preview

Unlock to view full version