M3.1 statistical learning Flashcards

1
Q

What does statistical learning primarily study?
A) Human behavior
B) Historical trends
C) Patterns in data
D) Biological systems
E) Chemical reactions

A

Patterns in data

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2
Q

Which type of learning is often unconscious and yields abstract knowledge?
A) Supervised learning
B) Unsupervised learning
C) Implicit learning
D) Explicit learning
E) Reinforcement learning

A

Implicit learning

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3
Q

Who is noted for their research in perceptual learning within the realm of statistical learning?
A) Jennifer Saffran
B) Reber
C) Watanabe
D) Seitz
E) Tim Brady

A

Watanabe

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4
Q

What role does the hippocampus play in statistical learning?
A) Muscle coordination
B) Visual processing
C) Inference and memory formation
D) Digestive processes
E) Hearing acuity

A

Inference and memory formation

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5
Q

In the context of language, what does a transition probability of P=1 within words suggest?
A) High likelihood of transitioning within the word
B) Low likelihood of error
C) High probability of grammatical mistakes
D) Independence from syntax
E) None of the above

A

High likelihood of transitioning within the word

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6
Q

Which type of learning includes a labeled dataset for training?
A) Unsupervised learning
B) Semi-supervised learning
C) Supervised learning
D) Reinforcement learning
E) Implicit learning

A

Supervised learning

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7
Q

What is a key feature of reinforcement learning?
A) No feedback involved
B) Uses labeled data only
C) Learns from delayed rewards
D) Always requires a teacher
E) Unrelated to predictions

A

Learns from delayed rewards

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8
Q

Which research involved using artificial grammars to explore implicit learning mechanisms?
A) Saffran et al., 1996
B) Reber, 1965
C) Watanabe, 2001
D) Turk-Browne et al., 2006
E) Seitz, 2009

A

Reber, 1965

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9
Q

Which learning type is characterized by the absence of direct feedback about the correctness of responses?
A) Supervised learning
B) Unsupervised learning
C) Reinforcement learning
D) Perceptual learning
E) Rule-based learning

A

Unsupervised learning

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10
Q

What distinguishes implicit from explicit learning?
A) Implicit learning is always visual.
B) Explicit learning cannot involve memory.
C) Implicit learning occurs without conscious awareness.
D) Explicit learning uses only auditory cues.
E) Implicit learning is faster.

A

Implicit learning occurs without conscious awareness.

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11
Q

Statistical learning is essential for which field?
A) Computational linguistics
B) Mechanical engineering
C) Organic chemistry
D) Maritime navigation
E) Urban planning

A

Computational linguistics

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12
Q

Which scenario best represents an application of statistical learning?
A) Determining the structure of proteins
B) Predicting consumer behavior
C) Solving algebraic equations
D) Composing symphonic music
E) Diagnosing mechanical faults in engines

A

Predicting consumer behavior

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13
Q

In statistical learning, what does ‘unsupervised’ refer to?
A) Learning without any prior data
B) Learning without explicit labels
C) Learning without any algorithms
D) Learning without error correction
E) Learning without historical precedent

A

Learning without explicit labels

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14
Q

Who contributed to the understanding of reward-based learning in statistical contexts?
A) Jennifer Saffran
B) Reber
C) Watanabe
D) Seitz
E) Poggio

A

Seitz

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15
Q

What is a common tool used in the analysis of statistical learning data?
A) Microscope
B) Oscilloscope
C) ANOVA
D) Stethoscope
E) Spectroscope

A

ANOVA

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16
Q

Which of the following best describes incidental learning?
A) Learning through structured courses
B) Learning that occurs without deliberate intention
C) Learning only relevant in children
D) Learning that requires direct feedback
E) Learning associated exclusively with motor skills

A

Learning that occurs without deliberate intention

17
Q

What is a key concept introduced by Reber in the context of implicit learning?
A) Structured Query Language
B) Artificial grammar learning
C) Calculus of variations
D) Quantum mechanics
E) Behavioral economics

A

Artificial grammar learning

18
Q

Which learning theory is most associated with statistical learning in auditory perception?
A) Classical conditioning
B) Operant conditioning
C) Perceptual learning
D) Cognitive behavioral therapy
E) Transactional analysis

A

Perceptual learning

19
Q

In the context of the lectures, what does supervised learning primarily involve?
A) Learning without any guidance or labels
B) Learning with the aid of labeled data
C) Learning that depends on physical activities
D) Learning exclusively through observation
E) Learning without any prior data

A

Learning with the aid of labeled data

20
Q

Which method is often used to validate models in statistical learning?
A) Cross-validation
B) Peer review
C) Double-blind testing
D) Hypothesis testing
E) Random sampling

A

Cross-validation

21
Q

What is the primary focus of reinforcement learning within the context of AI and machine learning?
A) Syntax and grammar enhancement
B) Decision-making based on reward systems
C) Visual recognition accuracy
D) Emotional intelligence development
E) Enhancing logical reasoning skills

A

Decision-making based on reward systems

22
Q

How is perceptual learning typically demonstrated in experiments?
A) Through linguistic skills
B) Through sensory and perception tasks
C) Through mathematical equations
D) Through emotional responses
E) Through economic modeling

A

Through sensory and perception tasks

23
Q

Which experiment highlighted the role of transition probabilities in statistical learning of language?
A) Saffran et al., 1996
B) Reber, 1965
C) Watanabe, 2001
D) Seitz, 2009
E) Chomsky, 1956

A

Saffran et al., 1996

24
Q

Which learning type heavily relies on datasets with known outcomes?
A) Unsupervised learning
B) Supervised learning
C) Implicit learning
D) Perceptual learning
E) Explicit learning

A

Supervised learning

25
What aspect of learning is primarily focused on during unsupervised learning? A) Feedback and corrections B) Pattern discovery without labels C) Reward systems D) Memorization techniques E) Skill acquisition
Pattern discovery without labels
26
Which component is not typically involved in the process of statistical learning? A) Data collection B) Pattern recognition C) Random guessing D) Model validation E) Hypothesis generation
Random guessing
27
What is the typical outcome of effective statistical learning? A) Improved physical coordination B) Enhanced data prediction capabilities C) Increased historical knowledge D) Better artistic skills E) Advanced language proficiency
Enhanced data prediction capabilities
28
What role do algorithms play in statistical learning? A) They provide historical context B) They solve mathematical problems C) They detect patterns in data D) They enhance physical abilities E) They create visual art
They detect patterns in data
29
Which researcher's work is pivotal for understanding reinforcement learning's application in real-world scenarios? A) Jennifer Saffran B) Arthur Reber C) Watanabe D) Seitz E) Sutton and Barto
Sutton and Barto
30
What distinguishes statistical learning from traditional learning methods? A) Its reliance on large data sets B) Its use in physical training C) Its application in historical studies D) Its focus on biological processes E) Its method of teaching languages
Its reliance on large data sets
31
Which techniques are crucial for statistical analysis in learning models? A) Regression analysis B) ANOVA C) T-tests D) Chi-square tests E) Factor analysis
Regression analysis, ANOVA, T-tests
32
What subjects intersect with statistical learning in research? A) Neuroscience B) Psychology C) Computer science D) Mechanical engineering E) Literature
Neuroscience, Psychology, Computer science
33
Which factors influence effective statistical learning? A) Quality of data B) Computational power C) Theoretical knowledge D) Physical tools used E) Algorithm complexity
Quality of data, Computational power, Algorithm complexity
34
What outcomes can result from the application of statistical learning in technology? A) Improved machine learning models B) Enhanced predictive analytics C) Better user interface design D) More efficient data storage E) Faster computational speeds
Improved machine learning models, Enhanced predictive analytics
35
Which areas benefit from perceptual learning through statistical methods? A) Music recognition B) Speech recognition C) Pattern recognition D) Emotional recognition E) Color recognition
Music recognition, Speech recognition, Pattern recognition
36
Which are components of statistical learning? A) Data collection B) Pattern recognition C) Hypothesis testing D) Algorithm development E) Physical experimentation
Pattern recognition, Hypothesis testing, Algorithm development
37
Identify the researchers associated with developments in statistical learning. A) Jennifer Saffran B) Arthur Reber C) Noam Chomsky D) Watanabe E) Seitz
Jennifer Saffran, Arthur Reber, Watanabe, Seitz
38
What are recognized applications of statistical learning? A) Medical diagnosis B) Stock market analysis C) Weather forecasting D) Legal advising E) Educational curriculum design
Medical diagnosis, Stock market analysis, Weather forecasting
39
Which aspects are studied in statistical learning courses? A) Neural networks B) Decision trees C) Cluster analysis D) Fourier transforms E) Differential equations
Neural networks, Decision trees, Cluster analysis