Mathematical Models of Judgment

Description: Mathematical Models of Judgment Quiz
Number of Questions: 15
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Tags: mathematical psychology judgment and decision making signal detection theory psychophysics
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In signal detection theory, the probability of a hit is defined as the probability of:

  1. Correctly identifying a signal when it is present.

  2. Incorrectly identifying a signal when it is absent.

  3. Correctly identifying a noise when it is present.

  4. Incorrectly identifying a noise when it is absent.


Correct Option: A
Explanation:

In signal detection theory, the probability of a hit is the probability of correctly identifying a signal when it is present.

In signal detection theory, the probability of a false alarm is defined as the probability of:

  1. Correctly identifying a signal when it is present.

  2. Incorrectly identifying a signal when it is absent.

  3. Correctly identifying a noise when it is present.

  4. Incorrectly identifying a noise when it is absent.


Correct Option: B
Explanation:

In signal detection theory, the probability of a false alarm is the probability of incorrectly identifying a signal when it is absent.

The receiver operating characteristic (ROC) curve is a graphical representation of the relationship between:

  1. The probability of a hit and the probability of a false alarm.

  2. The probability of a hit and the probability of a miss.

  3. The probability of a false alarm and the probability of a miss.

  4. The probability of a hit and the probability of a correct rejection.


Correct Option: A
Explanation:

The ROC curve is a graphical representation of the relationship between the probability of a hit and the probability of a false alarm.

The area under the ROC curve (AUC) is a measure of:

  1. The overall accuracy of a signal detection system.

  2. The sensitivity of a signal detection system.

  3. The specificity of a signal detection system.

  4. The efficiency of a signal detection system.


Correct Option: A
Explanation:

The AUC is a measure of the overall accuracy of a signal detection system.

The Weber-Fechner law states that the just noticeable difference (JND) between two stimuli is:

  1. A constant proportion of the original stimulus.

  2. A constant difference between the two stimuli.

  3. A logarithmic function of the original stimulus.

  4. An exponential function of the original stimulus.


Correct Option: A
Explanation:

The Weber-Fechner law states that the JND between two stimuli is a constant proportion of the original stimulus.

The Fechner equation is a mathematical expression of the Weber-Fechner law that states that:

  1. $$S = k log R$$

  2. $$S = kR$$

  3. $$S = kR^2$$

  4. $$S = kR^3$$


Correct Option: A
Explanation:

The Fechner equation is a mathematical expression of the Weber-Fechner law that states that $$S = k log R$$, where S is the sensation, R is the stimulus, and k is a constant.

The Stevens power law is a mathematical expression of the relationship between the perceived magnitude of a stimulus and the physical magnitude of the stimulus that states that:

  1. $$S = kR^n$$

  2. $$S = k log R$$

  3. $$S = kR$$

  4. $$S = kR^2$$


Correct Option: A
Explanation:

The Stevens power law is a mathematical expression of the relationship between the perceived magnitude of a stimulus and the physical magnitude of the stimulus that states that $$S = kR^n$$, where S is the sensation, R is the stimulus, k is a constant, and n is an exponent.

The Thurstone model of judgment is a mathematical model that assumes that:

  1. Judgments are based on a single underlying dimension.

  2. Judgments are based on multiple underlying dimensions.

  3. Judgments are based on a combination of underlying dimensions and noise.

  4. Judgments are based on a random process.


Correct Option: B
Explanation:

The Thurstone model of judgment is a mathematical model that assumes that judgments are based on multiple underlying dimensions.

The Shepard-Kruskal model of judgment is a mathematical model that assumes that:

  1. Judgments are based on a single underlying dimension.

  2. Judgments are based on multiple underlying dimensions.

  3. Judgments are based on a combination of underlying dimensions and noise.

  4. Judgments are based on a random process.


Correct Option: C
Explanation:

The Shepard-Kruskal model of judgment is a mathematical model that assumes that judgments are based on a combination of underlying dimensions and noise.

The Luce choice model is a mathematical model that assumes that:

  1. The probability of choosing one option over another is proportional to the ratio of their subjective values.

  2. The probability of choosing one option over another is proportional to the difference between their subjective values.

  3. The probability of choosing one option over another is proportional to the product of their subjective values.

  4. The probability of choosing one option over another is proportional to the sum of their subjective values.


Correct Option: A
Explanation:

The Luce choice model is a mathematical model that assumes that the probability of choosing one option over another is proportional to the ratio of their subjective values.

The Tversky-Kahneman prospect theory is a mathematical model of decision making under risk that assumes that:

  1. People are more sensitive to losses than to gains.

  2. People are more risk-averse in the domain of gains than in the domain of losses.

  3. People overweight small probabilities and underweight large probabilities.

  4. All of the above.


Correct Option: D
Explanation:

The Tversky-Kahneman prospect theory is a mathematical model of decision making under risk that assumes that people are more sensitive to losses than to gains, people are more risk-averse in the domain of gains than in the domain of losses, and people overweight small probabilities and underweight large probabilities.

The cumulative prospect theory is a mathematical model of decision making under risk that is an extension of the prospect theory that assumes that:

  1. The value of a gain or loss is a function of its magnitude and its probability.

  2. The value of a gain or loss is a function of its magnitude and its rank in the distribution of possible outcomes.

  3. The value of a gain or loss is a function of its magnitude, its probability, and its rank in the distribution of possible outcomes.

  4. None of the above.


Correct Option: C
Explanation:

The cumulative prospect theory is a mathematical model of decision making under risk that is an extension of the prospect theory that assumes that the value of a gain or loss is a function of its magnitude, its probability, and its rank in the distribution of possible outcomes.

The rank-dependent utility model is a mathematical model of decision making under risk that assumes that:

  1. The value of an outcome is a function of its rank in the distribution of possible outcomes.

  2. The value of an outcome is a function of its magnitude and its rank in the distribution of possible outcomes.

  3. The value of an outcome is a function of its probability and its rank in the distribution of possible outcomes.

  4. The value of an outcome is a function of its magnitude, its probability, and its rank in the distribution of possible outcomes.


Correct Option: A
Explanation:

The rank-dependent utility model is a mathematical model of decision making under risk that assumes that the value of an outcome is a function of its rank in the distribution of possible outcomes.

The mean-variance model of portfolio selection is a mathematical model that assumes that:

  1. Investors are risk-averse and seek to maximize their expected return for a given level of risk.

  2. Investors are risk-neutral and seek to maximize their expected return regardless of the level of risk.

  3. Investors are risk-seeking and seek to maximize their level of risk for a given expected return.

  4. None of the above.


Correct Option: A
Explanation:

The mean-variance model of portfolio selection is a mathematical model that assumes that investors are risk-averse and seek to maximize their expected return for a given level of risk.

The capital asset pricing model (CAPM) is a mathematical model of asset pricing that assumes that:

  1. The expected return of an asset is a linear function of its beta.

  2. The expected return of an asset is a linear function of its alpha.

  3. The expected return of an asset is a linear function of its Sharpe ratio.

  4. The expected return of an asset is a linear function of its Treynor ratio.


Correct Option: A
Explanation:

The CAPM is a mathematical model of asset pricing that assumes that the expected return of an asset is a linear function of its beta.

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