A) A mental tool employed to simplify complex decisions. B) A bias that is observed when an individual faces complex decisions. C) A mental tool employed to reduce the number of choices in a choice set. D) A bias that results in an individual preferring complex decisions. A) A mental tool employed to simplify complex decisions. B) A bias that is observed when an individual faces complex decisions. C) A mental tool employed to reduce the number of choices in a choice set. D) A bias that results in an individual preferring complex decisions.

Exam 7: Representativeness and Availability

Holly has a fair coin and a 10-sided die. If the coin comes up heads, then Holly rolls the die: if a 1 or 2 is rolled Holly wins $\$ 1$ and if a 3,4,5,6,7,8,9,10 is rolled Holly win a mug. If the coin comes up tails, then Holly rolls the die: if a 1,2,3,4,5,6,7 Holly wins $\$ 1$ and a mug and if $8,9,10$ is rolled Holly only wins a mug. A. What is the probability that Holly wins $\$ 1$ ? B. Holly wins a mug. What is the probability that the coin came up heads?

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(Essay)

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Question 1

Correct Answer:

Verified

A. $P(\$ 1)=P($ heads $) * P(1,2)+P($ tails $) P(1,2,3,4,5,6,7)=\frac{1}{2}\left(\frac{2}{10}+\frac{7}{10}\right)=\frac{9}{20}$
B. $P($ heads $\mid$ mug $)=\frac{P(\text { heads } n \text { mug })}{P(\text { mug })}=\frac{P(\text { mug } \mid \text { heads }) P(\text { heads })}{P(\text { mug })}=\frac{\frac{8}{10} \frac{1}{2}}{\frac{9}{10}}=\frac{4}{9}$

I have spun the roulette wheel 5 times in a row and each time I have landed on red. Which of the following statements reflects the "law of small numbers"?

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(Multiple Choice)

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Question 2

Correct Answer:

Verified

B

All else equal, as the variance of the random variable increases then the probability of rejecting the null at the $5 \%$ -level decreases.

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(True/False)

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Question 3

Correct Answer:

Verified

True

What is a heuristic?

(Multiple Choice)

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Question 4

What is the conjunction bias?

(Multiple Choice)

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Question 5

Representativeness is:

(Multiple Choice)

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Question 6

The gambler's fallacy is an example of the law of small numbers.

(True/False)

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Question 7

Suppose event $A$ and event $B$ are independent. Which of the following is not true?

(Multiple Choice)

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Question 8

In the taxi cab example, the concept that describes the mistake the individual made by identifying the taxi as blue despite the fact that $P($ taxi is blue $)=.15$ is called the base rate neglect.

(True/False)

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Question 9

In one week Kay predicts that it will rain with a $50 \%$ chance on Monday-Saturday and she predicts $0 \%$ chance of rain on Sunday. Kay is calibrated if it rains:

(Multiple Choice)

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Question 10

In the United States, the campaign against smoking has taken advantage of individuals' availability bias. By making these ads highly visible, Americans overestimate the likelihood of death from smoking.

(True/False)

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Question 11

I estimate that the probability of heads when tossing a coin to be $\hat{p}=\frac{6}{10}$ . Which test will I use to test whether the coin is a fair coin?

(Multiple Choice)

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Question 12

Which of the following is an example of a two-tailed test?

(Multiple Choice)

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Question 13

This chapter discusses how individuals use available information to form beliefs when facing uncertainty and how those beliefs translate into choices.

(True/False)

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Question 14

A one-tailed test is a test in which the alternative hypothesis is an inequality.

(True/False)

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Question 15

I toss a fair coin 4 times and observe heads 3 times. a. Using equation 7.1, what is the probability of observing 3 or fewer heads in 4 tosses of a fair coin? b. Using equation 7.1, what is the probability of observing 3 or more heads in 4 tosses of a fair coin? c. Write the formal test to test whether my estimate is a result of a fair coin. d. What do you conclude?

(Essay)

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Question 16

A normal distribution with $\mu=0$ and $\sigma=1$ is called a standard normal.

(True/False)

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Question 17

The interval on which we believe the true value of a parameter falls is called

(Multiple Choice)

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Question 18

The $95 \%$ confidence interval for a random variable with a standard normal distribution is $[1.96,-1.96]$ . Thus, that the probability of observing $\hat{\mu} \in[1.96,-1.96]$ is $95 \%$ .

(True/False)

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Question 19

A normal distribution can be fully described by which parameters.

(Multiple Choice)

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Question 20

I have spun the roulette wheel 5 times in a row and each time I have landed on red. Which of the following statements reflects the "law of small numbers"?

All else equal, as the variance of the random variable increases then the probability of rejecting the null at the $5 \%$ -level decreases.

What is a heuristic?

What is the conjunction bias?

Representativeness is:

The gambler's fallacy is an example of the law of small numbers.

Suppose event $A$ and event $B$ are independent. Which of the following is not true?

In the taxi cab example, the concept that describes the mistake the individual made by identifying the taxi as blue despite the fact that $P($ taxi is blue $)=.15$ is called the base rate neglect.

In one week Kay predicts that it will rain with a $50 \%$ chance on Monday-Saturday and she predicts $0 \%$ chance of rain on Sunday. Kay is calibrated if it rains:

In the United States, the campaign against smoking has taken advantage of individuals' availability bias. By making these ads highly visible, Americans overestimate the likelihood of death from smoking.

I estimate that the probability of heads when tossing a coin to be $\hat{p}=\frac{6}{10}$ . Which test will I use to test whether the coin is a fair coin?

Which of the following is an example of a two-tailed test?

This chapter discusses how individuals use available information to form beliefs when facing uncertainty and how those beliefs translate into choices.

A one-tailed test is a test in which the alternative hypothesis is an inequality.

A normal distribution with $\mu=0$ and $\sigma=1$ is called a standard normal.

The interval on which we believe the true value of a parameter falls is called

The $95 \%$ confidence interval for a random variable with a standard normal distribution is $[1.96,-1.96]$ . Thus, that the probability of observing $\hat{\mu} \in[1.96,-1.96]$ is $95 \%$ .

A normal distribution can be fully described by which parameters.

Rationality, Irrationality, and Rationalization

Transaction Utility and Consumer Pricing

Mental Accounting

Status Quo Bias and Default Options

The Winners Curse and Auction Behavior

Bracketing Decisions

Confirmation and Overconfidence

Decision Under Risk and Uncertainty

Prospect Theory and Decision Under Risk or Uncertainty

Disagreeing With Ourselves: Projection and Hindsight Biases

Naïve Procrastination

Committing and Uncommitting

Selfishness and Altruism

Fairness and Psychological Games

Trust and Reciprocity

Filters

Exam 7: Representativeness and Availability

I have spun the roulette wheel 5 times in a row and each time I have landed on red. Which of the following statements reflects the "law of small numbers"?

All else equal, as the variance of the random variable increases then the probability of rejecting the null at the 5%5 \%5% -level decreases.

What is a heuristic?

What is the conjunction bias?

Representativeness is:

The gambler's fallacy is an example of the law of small numbers.

Suppose event AAA and event BBB are independent. Which of the following is not true?

In the taxi cab example, the concept that describes the mistake the individual made by identifying the taxi as blue despite the fact that P(P(P( taxi is blue )=.15)=.15)=.15 is called the base rate neglect.

In one week Kay predicts that it will rain with a 50%50 \%50% chance on Monday-Saturday and she predicts 0%0 \%0% chance of rain on Sunday. Kay is calibrated if it rains:

In the United States, the campaign against smoking has taken advantage of individuals' availability bias. By making these ads highly visible, Americans overestimate the likelihood of death from smoking.

I estimate that the probability of heads when tossing a coin to be p^=610\hat{p}=\frac{6}{10}p^​=106​ . Which test will I use to test whether the coin is a fair coin?

Which of the following is an example of a two-tailed test?

This chapter discusses how individuals use available information to form beliefs when facing uncertainty and how those beliefs translate into choices.

A one-tailed test is a test in which the alternative hypothesis is an inequality.

A normal distribution with μ=0\mu=0μ=0 and σ=1\sigma=1σ=1 is called a standard normal.

The interval on which we believe the true value of a parameter falls is called

The 95%95 \%95% confidence interval for a random variable with a standard normal distribution is [1.96,−1.96][1.96,-1.96][1.96,−1.96] . Thus, that the probability of observing μ^∈[1.96,−1.96]\hat{\mu} \in[1.96,-1.96]μ^​∈[1.96,−1.96] is 95%95 \%95% .

A normal distribution can be fully described by which parameters.

Rationality, Irrationality, and Rationalization

Transaction Utility and Consumer Pricing

Mental Accounting

Status Quo Bias and Default Options

The Winners Curse and Auction Behavior

Bracketing Decisions

Confirmation and Overconfidence

Decision Under Risk and Uncertainty

Prospect Theory and Decision Under Risk or Uncertainty

Disagreeing With Ourselves: Projection and Hindsight Biases

Naïve Procrastination

Committing and Uncommitting

Selfishness and Altruism

Fairness and Psychological Games

Trust and Reciprocity

Filters

All else equal, as the variance of the random variable increases then the probability of rejecting the null at the $5 \%$ -level decreases.

Suppose event $A$ and event $B$ are independent. Which of the following is not true?

In the taxi cab example, the concept that describes the mistake the individual made by identifying the taxi as blue despite the fact that $P($ taxi is blue $)=.15$ is called the base rate neglect.

In one week Kay predicts that it will rain with a $50 \%$ chance on Monday-Saturday and she predicts $0 \%$ chance of rain on Sunday. Kay is calibrated if it rains:

I estimate that the probability of heads when tossing a coin to be $\hat{p}=\frac{6}{10}$ . Which test will I use to test whether the coin is a fair coin?

A normal distribution with $\mu=0$ and $\sigma=1$ is called a standard normal.

The $95 \%$ confidence interval for a random variable with a standard normal distribution is $[1.96,-1.96]$ . Thus, that the probability of observing $\hat{\mu} \in[1.96,-1.96]$ is $95 \%$ .