9: Decision Making
- Page ID
- 54109
\( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)
\( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)
\( \newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\)
( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\)
\( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)
\( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\)
\( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)
\( \newcommand{\Span}{\mathrm{span}}\)
\( \newcommand{\id}{\mathrm{id}}\)
\( \newcommand{\Span}{\mathrm{span}}\)
\( \newcommand{\kernel}{\mathrm{null}\,}\)
\( \newcommand{\range}{\mathrm{range}\,}\)
\( \newcommand{\RealPart}{\mathrm{Re}}\)
\( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)
\( \newcommand{\Argument}{\mathrm{Arg}}\)
\( \newcommand{\norm}[1]{\| #1 \|}\)
\( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)
\( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\AA}{\unicode[.8,0]{x212B}}\)
\( \newcommand{\vectorA}[1]{\vec{#1}} % arrow\)
\( \newcommand{\vectorAt}[1]{\vec{\text{#1}}} % arrow\)
\( \newcommand{\vectorB}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)
\( \newcommand{\vectorC}[1]{\textbf{#1}} \)
\( \newcommand{\vectorD}[1]{\overrightarrow{#1}} \)
\( \newcommand{\vectorDt}[1]{\overrightarrow{\text{#1}}} \)
\( \newcommand{\vectE}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash{\mathbf {#1}}}} \)
\( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)
\( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)
\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)- 9.1: Representativeness
- Humans are drawn to stimuli that are salient, such as unique or negative experiences. This influences how we make judgments using cognitive shortcuts like the representativeness heuristic. Cognitive accessibility determines how readily available knowledge is to guide our reactions, potentially leading to errors such as the availability heuristic or false consensus bias. Understanding these concepts helps to recognize how we may think accurately or inaccurately about ourselves and others.
- 9.2: Availability
- Our perceptions of others and ourselves are influenced both by the salience of certain characteristics and individual differences in cognitive schemas. When a schema is highly accessible, it is more likely to be used in processing information and making judgments. This accessibility can result from both personal predispositions and situational factors, such as recent exposure to a concept (priming).
- 9.3: Anchoring
- The concept of the anchoring heuristic is explored, using Mt. Everest's height as an example. Anchoring involves making numerical estimates biased by an initial number provided or self-generated. Research shows that even arbitrary anchors can influence judgments, such as guesses about the number of African countries in the UN or willingness to spend money. These biases persist even when numbers are peripheral or unrelated.
- 9.4: Framing
- The page discusses a decision-making problem adapted from Tversky & Kahneman, where people must choose between two programs to combat a deadly avian disease. Though the outcomes of Programs (A and B) and (C and D) are objectively identical, framing them differently (focus on lives saved vs. lives lost) leads to different choices. People tend to be risk-averse with gains and risk-seeking with losses, illustrating how framing influences decision-making.
- 9.5: Sunk Cost Effect
- The concept of sunk cost in economics involves unrecoverable investments of time or money, leading to a trap where fear of loss prompts further investments in a failing venture. This can be manipulated, particularly in situations like cults, where more time and energy invested increases the perceived loss of leaving. Warren Buffet advises against this tendency, suggesting that the best course of action when faced with a failing situation is to "stop digging."
- 9.6: Hindsight Bias
- Hindsight bias is the tendency to view past events as having been predictable after they have already occurred. This bias often leads individuals to assume they "knew it all along," affecting how they judge others' decisions. For example, a company driver might face criticism for not acting on unusual engine sounds if the car later malfunctions, though she may have reasonably assessed the risk based on her previous experiences.
- 9.7: Illusory Correlations
- The text discusses how people often misinterpret data, particularly through illusory correlations???believing relationships exist between unrelated things. It highlights the myth that lunar phases affect human behavior, despite studies proving otherwise. Illusory correlations can stem from confirmation bias, where people seek evidence supporting their beliefs while ignoring contrary evidence. These false correlations can contribute to the formation of prejudicial attitudes.
- 9.8: Confirmation Bias
- Confirmation bias is a tendency to process information in a way that aligns with existing beliefs, often leading to poor judgments, belief justifications, and hostile reactions toward dissent. It can result in stereotype perpetuation or inaccurate diagnoses. While generally viewed negatively, the Argumentative Theory suggests it aids in constructing persuasive arguments by avoiding distractions.
- 9.9: Belief Perseverance Bias
- Belief perseverance bias occurs when individuals cling to their initial beliefs despite clear evidence to the contrary. This cognitive bias frustrates skeptics who present sound arguments to persuade others, yet fail to change beliefs. Rooted in confirmation bias, belief perseverance arises from a desire for certainty and linear knowledge. People prefer consistency and resist acknowledging errors, as the effort to reassess and integrate new information is daunting.
- 9.10: Overconfidence
- This page explores the concept of overconfidence in human judgment, showcasing it through a task requiring estimation of uncertain quantities with confidence intervals, revealing that most people are overly confident about their accuracy. The story of Jennifer Thompson highlights the impact of overconfidence in eyewitness testimony. Research confirms this cognitive bias's prevalence, with examples like flashbulb memories, which are vividly recalled but often inaccurately.