Midterm Vocabulary

Question 1

Trade-Off

Answer 1

A sacrifice that must be made in order to get a certain product / experience.

Question 2

“On-A-Par”

Answer 2

When neither option is better than the other but they are also not equally good.

Question 3

Opportunity Cost

Answer 3

The opportunity you couldn’t take in order to take another one.

Question 4

Heuristic

Answer 4

(Descriptive) Simple strategy that usually gives the normative answer but leads to systematic bias in some circumstances.

Question 5

Pre-Commitment

Answer 5

Strengthen your position by cutting off other options to make threats more credible.

Question 6

Gambler’s Fallacy

Answer 6

Mistaken believe that if something happens more frequently than normal during a given period, it will happen less frequently in the future.

Question 7

Hot Hand Fallacy

Answer 7

A person who experiences a successful outcome with a random event has a greater probability of success in further attempts (due to psychology).

Question 8

Law of Small Numbers

Answer 8

Judgmental bias that assumes the characteristics of a sample population can be estimated from a small number of observations or data points.

Question 9

Improper Linear Model

Answer 9

Unit weighted regression with random assignment, weights of the predictor variables are obtained by some non-optimal method

Question 10

Compensatory Model

Answer 10

Alternative good attributes and / or acceptable bad attributes can be traded off / compensated with or by each other within a given decision making situation

Question 11

Bootstrapped Model

Answer 11

Statistical model of resampling, can be used to estimate mean or standard deviation, the process of building a proper linear model of an expert’s judgments about an outcome criterion and then using that linear model in place of the judge

Question 12

Calibration

Answer 12

The extent to which a probability judgment correspond to actual events in the world / outcomes

i. predicted 80% and actually rained 80%
ii. can do for group of probability judgments
iii. data points on diagonal line = good calibration

Question 13

Discrimination

Answer 13

The extent to which you gave different probability judgments when the outcome occurs than when it doesn’t occur

i. data points near top + bot of calibration graph = good calibration
ii. for each judgment “bin”, compare the percentage of outcomes to the overall base rate
iii. higher scores = better, want big difference

Question 14

Evidence-Based Medicine

Answer 14

Approach to medical practice intended to optimize decisions by using evidence from well-designed and conducted research. Although all medicine based on science has some degree of empirical support, EBM classifies strong evidence with strong recommendations and weak with weak.

Question 15

Numeracy

Answer 15

Depends on negative vs. positive frame

Question 16

Arbitrage

Answer 16

Selling U1 and U2 in order to buy (U1+U2)

Question 17

Double-Price Auction

Answer 17

Potential buyers and sellers submit their bids / prices simultaneously and then auctioneer chooses some p that clears the market (sellers who asked <= p sell and buyers who bid >= p buy).

Question 18

Experimenter Degrees of Freedom

Answer 18

(a) Choosing among dependent variables
(b) Choosing Sample size
(c) Using covariates, and
(d) reporting subsets of experimental conditions. – researchers search for a combination that yields “statistical significance” and report only what “worked”