CHAPTER ONE From The Book of Common Prayer to the Full Monte Carlo Flashcards

1
Q

Where is the graveyard known as Bunhill Fields located?

A

Near Old Street Tube station, in Shoreditch in East London

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2
Q

Name three famous individuals buried in Bunhill Fields.

A
  • William Blake
  • Daniel Defoe
  • John Bunyan
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3
Q

Who is the most well-known person buried in Bunhill Fields, according to the text?

A

Reverend Thomas Bayes

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4
Q

What was Thomas Bayes’ profession?

A

Eighteenth-century Presbyterian minister and hobbyist mathematician

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5
Q

What is Thomas Bayes best known for?

A

His theorem, published in ‘An Essay towards Solving a Problem in the Doctrine of Chances’

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6
Q

What significant historical event took place in England in 1533?

A

Henry VIII took England out of the Catholic Church

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7
Q

What document did Archbishop Cranmer introduce in 1549?

A

The Book of Common Prayer

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8
Q

What was the Act of Uniformity passed by Parliament in 1662?

A

It required the Book of Common Prayer to be used in all services in England

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9
Q

What term refers to clergymen who refused to obey the Act of Uniformity?

A

Dissenters or Nonconformists

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10
Q

What did the Act of Toleration in 1688 allow for Dissenters?

A

Freedom of worship

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11
Q

What restrictions did Dissenters still face after the Act of Toleration?

A
  • Required licenses for places of worship
  • Banned from holding public office
  • Banned from attending English universities
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12
Q

Where did Nonconformist scholars and would-be ministers typically study?

A
  • Scottish universities, notably Edinburgh
  • Dutch universities, particularly Leiden
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13
Q

What was Richard Bayes known for?

A

Getting rich in the Sheffield steel industry, making cutlery

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14
Q

What was the fate of Samuel Bayes regarding the Act of Uniformity?

A

He was removed from his parish for refusing to obey it

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15
Q

How many children did Joshua Bayes and his wife Anne have?

A

Seven children

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16
Q

What was unusual about the survival rate of Joshua and Anne’s children?

A

All seven survived to adulthood, which was rare at the time

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17
Q

What educational background did Thomas Bayes likely have?

A

Educated by John Ward and possibly Abraham de Moivre

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18
Q

What university did Thomas Bayes attend for his studies?

A

University of Edinburgh

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19
Q

What was the purpose of Thomas Bayes’ studies in Edinburgh?

A

To prepare for his life as a minister

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20
Q

What is known about Thomas Bayes’ beliefs?

A

He was a Nonconformist, possibly an Arian or a Socinian

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21
Q

What was the title of Bayes’ first publication?

A

Divine benevolence: Or, an attempt to prove that the principal end of the divine providence and government is the happiness of his creatures

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22
Q

What philosophical issue does Bayes’ work Divine Benevolence address?

A

Theodicy: explaining why God allows evil in the world

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23
Q

What was Bayes’ view on God’s nature according to Divine Benevolence?

A

He believed God is benevolent and wants us to be happy

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24
Q

What controversial stance did Bayes likely hold regarding the Trinity?

A

He probably denied the Trinity, aligning with Arian or Socinian beliefs

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25
Q

Who was Thomas Bayes?

A

An 18th-century statistician and theologian known for Bayes’ theorem

Bayes was a Presbyterian minister with unorthodox Christian views, likely influenced by his associations with Nonconformist ministers.

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26
Q

What was the profession of Thomas Bayes’ father?

A

Moderate Calvinist minister

Bayes’ father, Joshua, tolerated a variety of views.

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27
Q

What is Arianism?

A

A belief that denies the full divinity of Jesus Christ

Arianism was deemed heretical by mainstream Christianity.

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28
Q

Who was James Foster?

A

A Dissenting minister and friend of Thomas Bayes

Foster wrote a pamphlet arguing that the Trinity was not essential to Christianity.

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29
Q

What significant financial contribution did Bayes make upon his death?

A

He left £200 to John Hoyle and Richard Price

Both were Nonconformist ministers who were Arian in faith.

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30
Q

What notable mathematical position did William Whiston hold?

A

Lucasian professor of mathematics at Cambridge

He succeeded Isaac Newton in this prestigious role.

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31
Q

What was the primary interest of Philip Stanhope, the 2nd Earl Stanhope?

A

Amateur mathematics and science

He was part of a network of scientists and mathematicians, including Bayes.

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32
Q

What was ‘An Introduction to the Doctrine of Fluxions’?

A

A paper by Thomas Bayes defending Newton’s calculus

It addressed critiques from philosopher George Berkeley.

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33
Q

What misconception did Gerolamo Cardano have regarding probabilities?

A

He believed rolling a die multiple times multiplied the probability of outcomes

This led to incorrect assumptions about the odds of rolling a six.

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34
Q

Who were Pascal and Fermat?

A

Mathematicians who contributed to the foundations of probability theory

Their correspondence addressed problems of chance and fair division of winnings.

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35
Q

What is a derivative in mathematics?

A

The rate of change of a function with respect to a variable

It represents the slope of the tangent line at a specific point on a graph.

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36
Q

Fill in the blank: The probability of rolling a six on a single die is ______.

A

1/6

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37
Q

What is an infinite series?

A

A mathematical series that continues indefinitely

Examples include sums like 1 + 1/2 + 1/4 + 1/8… which converge to a finite value.

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38
Q

What was the outcome of the correspondence between Gombaud and Pascal?

A

They discussed how to fairly divide a pot in interrupted games of chance

This led to foundational ideas in probability.

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39
Q

True or False: Thomas Bayes was a modern academic focused on research agendas.

A

False

Bayes was more of an amateur mathematician, engaging in mathematics for personal pleasure.

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40
Q

What is the probability of rolling at least one six in four rolls of a die?

A

Approximately 0.52

This is calculated by determining the probability of not rolling a six and subtracting from 1.

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41
Q

What is the significance of the theorem found in Stanhope’s papers?

A

It was a theorem related to derivatives and infinite series, discovered later by Lagrange

This shows the historical importance of Bayes’ work in calculus.

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42
Q

Fill in the blank: The chance of not rolling a double six in twenty-four rolls is ______.

A

0.51

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43
Q

What was a key observation made by Gombaud regarding betting?

A

That betting on rolling at least one six is profitable, while betting on double sixes is not

His empirical observations led to deeper questions about probability.

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44
Q

How many points does the first player have in the interrupted game?

A

Fifty points.

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45
Q

How many points does the second player have in the interrupted game?

A

Twenty points.

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46
Q

According to Pacioli, how should the winnings be split?

A

Five-sevenths of the pot to the first player.

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47
Q

What was Cardano’s criticism of Pacioli’s solution?

A

He found it absurd because it seemed unfair.

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48
Q

What does Cardano suggest should determine the division of stakes?

A

The number of rounds each player has yet to win.

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49
Q

What is the progression of a number?

A

The sum of that number and all the integers below it down to one.

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50
Q

What was Cardano’s example involving two players?

A

One player had three points to win, the other had one.

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51
Q

How did Cardano propose to divide the pot?

A

In a six-to-one ratio in favor of the second player.

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52
Q

What key insight did Pascal and Fermat realize about winning?

A

It’s the number of possible outcomes that remain that matters.

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53
Q

In Pascal’s example, what was the total pot amount?

A

Sixty-four pistoles.

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54
Q

What was the fair distribution of the pot when the score was 2-1?

A

Three-quarters of the pot to the first player.

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55
Q

How many possible outcomes are there if two players are at a score of 2-1?

A

Four possible outcomes.

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56
Q

If Player One is up 2-0, what is the fair division according to Pascal?

A

Fifty-six pistoles out of sixty-four.

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57
Q

What does Pascal’s triangle help calculate?

A

The number of possible outcomes in probability.

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58
Q

What is the formula for calculating the probability of an event?

A

Number of ways the event can occur divided by total number of outcomes.

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59
Q

What does the Law of Large Numbers state?

A

The more trials conducted, the closer the results will be to the true probability.

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60
Q

Who introduced the next stage of probability theory after Pascal and Fermat?

A

Jacob Bernoulli.

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61
Q

What happens to the probability results as the number of trials increases?

A

They get closer to the true probability.

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62
Q

What is the significance of Bernoulli’s claim?

A

It applies to real-world scenarios beyond simple games of chance.

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63
Q

What were Pascal and Fermat’s letters the beginning of?

A

The modern idea of probability theory.

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64
Q

Fill in the blank: The doctrine of chances is an early name for ______.

A

Probability theory.

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65
Q

True or False: Bernoulli’s findings only apply to games of chance.

A

False.

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66
Q

What is the difference between sampling probabilities and inferential probabilities?

A

Sampling probabilities predict about a sample given knowledge of the whole, while inferential probabilities predict about the whole based on a sample.

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67
Q

Who was Bernoulli and what was his main interest?

A

Bernoulli was a Swiss mathematician interested in games of chance and the probability of outcomes in uncertain situations.

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68
Q

What is ‘moral certainty’ as defined by Bernoulli?

A

Moral certainty is a given degree of confidence in a spread of results, rather than absolute certainty.

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69
Q

What does Bernoulli’s theorem address?

A

Bernoulli’s theorem addresses how confident we can be in the contents of an urn after drawing a sample.

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70
Q

What is the relationship between sample size and confidence in Bernoulli’s findings?

A

A larger sample size increases the likelihood that the sample result is close to the true ratio in the population.

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71
Q

Fill in the blank: Bernoulli’s theorem states that for any probability we wish, the absolute difference between the sample proportion m/n and the true proportion p is less than or equal to some number ______.

A

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72
Q

How did Bernoulli suggest one could achieve a desired level of confidence?

A

By specifying the number of observations needed to achieve a certain level of confidence in the results.

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73
Q

True or False: Bernoulli believed that we could achieve absolute certainty through sampling.

A

False

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74
Q

What significant concept did Bernoulli contribute to the understanding of empirical evidence?

A

He created a philosophically robust way of using empirical evidence to establish probabilities.

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75
Q

Who extended Bernoulli’s ideas about probability?

A

Abraham de Moivre extended Bernoulli’s ideas about probability.

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76
Q

What is a binomial distribution?

A

A binomial distribution describes the outcomes of a scenario with two equally likely outcomes, such as flipping a coin.

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77
Q

What is the mathematical significance of factorials in probability calculations?

A

Factorials are used to calculate the number of ways outcomes can occur in probability, but they can become very large and complex.

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78
Q

Fill in the blank: The factorial of five is ______.

A

120

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79
Q

What did de Moivre notice about the shape of probability distribution curves?

A

He noticed that the curves have a bulge in the middle and flattened edges, especially with larger sample sizes.

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80
Q

What is the implication of Bernoulli’s findings for fields beyond gambling?

A

His findings have implications for fields like medicine, criminal justice, and any area requiring inferential statistics.

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81
Q

What was a key limitation in Bernoulli’s approach according to Aubrey Clayton?

A

Bernoulli did not clearly distinguish between sampling probabilities and inferential probabilities.

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82
Q

What is the false positive rate Bernoulli aimed for in his studies?

A

0.001, or a false positive rate of 1 in 1,000.

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83
Q

What did de Moivre notice about the shape of the curve in probability?

A

The curve has a bulge in the middle and flattened edges.

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84
Q

What is the mathematical expression derived by de Moivre for probability outcomes?

A

Normal distribution.

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85
Q

What is the standard deviation a measure of?

A

How spread out your data is around the mean.

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86
Q

How do you calculate variance?

A

By taking each value, subtracting the mean, squaring the result, and averaging those squares.

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87
Q

If the mean height of three children is 160 cm, what does a standard deviation of 2.4 cm imply?

A

The heights vary within 2.4 cm from the mean.

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88
Q

What percentage of values fall within 1 standard deviation (SD) of the mean in a normal distribution?

A

68 percent.

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89
Q

What does a standard deviation (SD) of 42.4 indicate in the example of eight-year-olds and a basketball player?

A

The two eight-year-olds are 0.7 SD below the mean, and the basketball player is 1.4 SD above the mean.

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90
Q

How does the accuracy of data relate to sample size according to de Moivre?

A

The accuracy grows in proportion to the square root of the sample size.

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91
Q

What percentage of the time is it expected to see sixty or more heads in one hundred coin flips?

A

About 2.8 percent of the time.

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92
Q

What is the main question Bernoulli and de Moivre were trying to answer?

A

How likely am I to see this data, given a certain hypothesis?

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93
Q

What significant contribution did Thomas Simpson make to statistics?

A

He advocated using the mean of observations to estimate true positions in measurement error.

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94
Q

What was Bayes’s key insight regarding probability?

A

Probability is subjective and reflects our lack of knowledge about the world.

95
Q

What is the difference between inferential probability and sampling probability?

A

Inferential probability asks ‘How likely is a hypothesis true, given this data?’ while sampling probability asks ‘How likely am I to see this data, given a hypothesis?’

96
Q

What did Bayes argue about the use of imperfect measuring instruments?

A

More observations with an imperfect instrument will not necessarily reduce error.

97
Q

In Bayes’s view, what must be considered to make inferential probability work?

A

How likely you thought the hypothesis was in the first place.

98
Q

What metaphor did Bayes use to explain his concept of probability?

A

A table upon which balls are rolled.

99
Q

What is the relationship between the mean and the errors in measurements according to Bayes?

A

The mean will not help if the measuring instrument is biased.

100
Q

What is the main question to ask in inferential probability?

A

What are the chances that my hypothesis is true, given the data?

101
Q

What should be taken into account when making inferential probability work?

A

Your subjective beliefs about the hypothesis.

102
Q

What metaphor did Bayes use to explain his point?

A

A table upon which balls are rolled.

103
Q

What type of table did later writers refer to in relation to Bayes’ metaphor?

A

A billiard table.

104
Q

What happens to the white ball after it is rolled on the table?

A

It is removed and a line is drawn across the table where it was.

105
Q

What information is provided after rolling red balls onto the table?

A

How many balls lie to the left of the line and how many to the right.

106
Q

If five balls are thrown and two land left and three right, where does Bayes suggest the line is?

A

Three-sevenths of the way up the table from the left.

107
Q

What might be an intuitive but incorrect assumption about the line’s position?

A

That it should be two-fifths of the way up the table.

108
Q

What does Bayes emphasize must be considered in estimating the line’s position?

A

The prior probability.

109
Q

What does the lack of information about the line’s position represent?

A

A form of prior information.

110
Q

What is the subjective point of view regarding the line’s possible positions?

A

It is equally likely to be anywhere on the table.

111
Q

Fill in the blank: The distribution of probability graph would show how likely the line is to be in a given place on the _______.

112
Q

What is the probability of the next ball landing to the left of the line if you have no idea where the line is?

A

0.5 (50 percent)

This reflects the uncertainty in the position of the line.

113
Q

What does Bayes’ theorem suggest about incorporating new information?

A

You must add any new information you get to the information you already have.

114
Q

How does Bayes’ method modify the calculation of probability?

A

It adds one to the number of red balls on the left and two to the total number of red balls.

115
Q

What is the concept of posterior probability distribution?

A

It is the updated assessment of the likely position of the line after incorporating new information.

116
Q

What happens to the posterior distribution when new information is gathered?

A

It becomes the new prior for further assessments.

117
Q

True or False: Bayes’ theorem guarantees absolute certainty in probability estimates.

A

False

No matter how much evidence is gathered, absolute certainty is never achieved.

118
Q

What is the significance of Richard Price in relation to Bayes’ work?

A

He brought Bayes’ paper to wider attention and contributed to its practical applications.

119
Q

What was the primary focus of Bayes’ original paper?

A

It was all theory with no hint of application.

120
Q

What analogy does Price use to explain the application of Bayes’ theorem?

A

The odds of the sun rising again after having seen it rise multiple times.

121
Q

How does Price suggest one should view the probability of rare events?

A

They can happen, and even with many observations, one cannot reach physical certainty.

122
Q

According to Hume, what is necessary to establish a miracle?

A

Testimony that is more miraculous in falsehood than the miracle itself.

123
Q

What is a key argument Price makes against Hume’s view?

A

Even with repeated observations, one can never be physically certain about future events.

124
Q

Fill in the blank: Bayes’ theorem allows one to update their _______ based on new evidence.

A

[prior beliefs]

125
Q

What did Price argue about rolling a die with an unknown number of sides?

A

If it shows a certain face a million times, the best estimate for the next roll’s outcome is calculable.

126
Q

What does the ‘uniform probability distribution’ imply?

A

It indicates that all outcomes are initially considered equally likely until evidence is gathered.

127
Q

What type of reasoning does Bayes’ theorem exemplify?

A

Subjective probability reasoning.

128
Q

What was one of the implications of the divide among Nonconformist ministries regarding mathematics?

A

Some believed it would lead to godlessness, while others thought it helped understand God’s universe.

129
Q

What was the impact of Price’s pamphlet, ‘Observations on the Nature of Civil Liberty’?

A

It significantly influenced American independence sentiments.

130
Q

What does Price’s appendix to Bayes’ work discuss?

A

The odds of the sun rising and the implications for probability theory.

131
Q

True or False: Bayes’ theorem can be applied to inferential statistics.

132
Q

What does Bayes’ theorem imply about the certainty of future events?

A

No amount of evidence can produce absolute certainty.

133
Q

What is the relationship between prior and posterior distributions in Bayesian analysis?

A

The posterior distribution becomes the new prior when new evidence is included.

134
Q

What is the probability of the next roll coming up not-X according to Price?

A

1/1,000,002

This probability indicates the likelihood of not observing a particular outcome in a series of events.

135
Q

What is the range of probability for not seeing an X that Price calculated?

A

Between 1 in 600,000 and 1 in 3 million

This range reflects the uncertainty surrounding rare events.

136
Q

What philosophical point did Price make regarding rare events?

A

Rare events happen sometimes, and no amount of seeing them not happen will ever completely rule them out.

137
Q

How did Hume respond to Price’s criticisms of his work?

A

Hume removed disobliging comments and added an apologetic introduction in the second edition of his work.

138
Q

What did Hume call Price after their exchange?

A

A true Philosopher

Hume praised Price for his civility and reasoned arguments.

139
Q

What did Price suggest about Bayes’ theorem in his foreword to Bayes’ paper?

A

It could show that the world progressed according to fixed laws and could confirm the argument for the existence of the Deity.

140
Q

Who independently arrived at conclusions similar to Bayes after his death?

A

Pierre-Simon Laplace

Laplace provided a more detailed account of Bayesian principles.

141
Q

What major application did probability theory have in the social sciences according to Jacob Bernoulli?

A

Working out how likely someone was to live for another ten years by looking at similar individuals.

142
Q

What did Laplace find regarding birth rates in Paris?

A

A bias toward boy babies with a ratio of roughly 51:49

He calculated a 1 in 10^42 chance of seeing such an extreme result if births were equally likely.

143
Q

Who was Adolphe Quetelet and what was his main contribution?

A

A Belgian mathematician who pushed probability and statistics into the social sciences, introducing the concept of the ‘average man.’

144
Q

What did Quetelet aim to analyze through statistics?

A

Society along various axes such as physical attributes, moral and psychological characteristics.

145
Q

What did Quetelet discover about measurements like height and weight?

A

They were normally distributed, suggesting they were influenced by many small factors.

146
Q

What did Quetelet think about the average man?

A

He viewed the average man as an ideal or standard of beauty at which nature aims.

147
Q

What controversy arose from Quetelet’s work?

A

It conflicted with the idea of free will, suggesting behaviors were influenced by attributes.

148
Q

What did Francis Galton contribute to the field of statistics?

A

He advanced the use of frequentist statistics, focusing on hypothesis testing rather than data to hypothesis.

149
Q

What is the key difference between Bayesian and frequentist statistics?

A

Bayesian statistics move from data to hypothesis, while frequentist statistics move from hypothesis to data.

150
Q

What is a major challenge with Bayesian priors?

A

They are subjective and depend on individual knowledge and ignorance.

151
Q

What philosophical issue arises from Bayesian priors?

A

They suggest that truth may depend on personal beliefs and prior knowledge.

152
Q

What example illustrates the complexity of choosing priors in Bayesian statistics?

A

The urn with black and white balls, where different assumptions lead to different prior probabilities.

153
Q

What does the Bayesian model suggest about the truth of a statement?

A

Whether something is true depends on how strongly one believed it before.

154
Q

What is the distinction between subjective probability and objective probability?

A

Subjective probability is a statement about beliefs, while objective probability is about real-world phenomena.

155
Q

True or False: Subjective probability means random or baseless.

156
Q

What is the phenomenon that Galton is known for regarding offspring heights?

A

Regression to the mean.

157
Q

Fill in the blank: Galton coined the phrase ______ to refer to heredity and environment.

A

nature and nurture.

158
Q

What did Galton want to create a science of?

A

Human breeding (eugenics).

159
Q

Who was the first appointee to the chair of eugenics at University College London?

A

Karl Pearson.

160
Q

What statistical test did Karl Pearson develop?

A

Chi-square test.

161
Q

What is the term coined by Pearson that measures the dispersion of a dataset?

A

Standard deviation.

162
Q

What did Ronald Fisher contribute to statistics?

A

Analysis of variance (ANOVA), statistical significance, and maximum likelihood estimation (MLE).

163
Q

True or False: Fisher was known for his progressive views on race and eugenics.

164
Q

What did Fisher and Pearson disagree about?

A

The interpretation of the maximum likelihood method and its relation to Bayesian probability.

165
Q

What did Galton use to demonstrate the normal distribution problem?

A

A quincunx.

166
Q

What happens when multiple smaller normal distributions are combined, according to Galton?

A

They can add up to form one larger normal distribution.

167
Q

Fill in the blank: Galton’s insight regarding smaller distributions allowed statisticians to think about ______ populations forming part of a larger one.

A

different.

168
Q

What was Galton’s view on the intelligence of different races?

A

He held racist views, considering some races inferior.

169
Q

What was the general finding regarding the heritability of IQ?

A

About half of the variance in IQ is caused by genetics.

170
Q

Fill in the blank: Galton’s work inspired later statisticians like Karl Pearson and ______.

A

Ronald Fisher.

171
Q

What did Galton observe about the offspring of very tall and very short parents?

A

They tend not to be as extreme in height as their parents.

172
Q

True or False: The concept of statistical significance was developed by Ronald Fisher.

173
Q

What major conflict arose between Fisher and Pearson?

A

Their disagreement over the interpretation of likelihood ratios in statistical analysis.

174
Q

What was the focus of Galton’s book ‘Hereditary Genius’?

A

The clustering of brilliant thinkers in families.

175
Q

Who were notable supporters of eugenics in the early 20th century?

A

John Maynard Keynes, Sidney and Beatrice Webb, George Bernard Shaw, Bertrand Russell

These individuals were influential in socialist and liberal movements and supported selective breeding.

176
Q

What did Fisher argue in Eugenics Review about nations and their institutions?

A

Nations with institutions that produce better individuals will supplant those that breed decadence

This reflects the eugenic belief in improving society through selective breeding.

177
Q

What was the criticism of embryo screening and mitochondrial donation primarily associated with?

A

The religious right labeled them as eugenics

This indicates the contentious nature of eugenics in contemporary discussions.

178
Q

What was Clayton’s argument regarding the history of statistics and eugenics?

A

He argued that the history of frequentist statistics is intertwined with eugenics

Clayton suggests that the statistical methods developed were influenced by eugenic ideologies.

179
Q

What did Fisher and Pearson seek in their statistical methods regarding eugenics?

A

They sought a veneer of objectivity to support their eugenic views

They aimed to present their beliefs as scientific truths.

180
Q

What is Bayesianism characterized by in terms of probability?

A

Bayesianism treats probability as subjective, reflecting our ignorance of the world

This contrasts with frequentist views that treat probability as an objective measure.

181
Q

What did John Stuart Mill criticize about the Bayesian approach?

A

He criticized the idea that two outcomes should be treated as equally likely without evidence

Mill believed that probability should reflect real-world frequencies.

182
Q

What is a p-value in frequentist statistics?

A

The likelihood of observing results at least as extreme as those seen under the null hypothesis

It helps determine whether an observed effect is statistically significant.

183
Q

What is the null hypothesis in the context of the IQ and shoe size example?

A

The hypothesis that there is no real effect of shoe size on IQ

It serves as a baseline for testing the validity of the observed data.

184
Q

What was Fisher’s view on Bayesianism?

A

He called Bayes’ theorem a ‘staggering falsity’ and believed it should be wholly rejected

Fisher’s strong criticism reflects the tension between frequentist and Bayesian approaches.

185
Q

What did Venn contribute to the discussion on probability?

A

He emphasized that probability should reflect actual frequencies from hypothetical infinite trials

This approach underlines the frequentist perspective on probability.

186
Q

Fill in the blank: Frequentist statistics involves sampling probability, the probability that _______.

A

Bernoulli would have recognized

This highlights the historical roots of frequentist statistics.

187
Q

True or False: The eugenics movement had no influence on early scientific methods.

A

False

The eugenics movement intertwined significantly with the development of early statistical methods.

188
Q

What did Boole note about different kinds of ignorance in Bayesian statistics?

A

Different kinds of ignorance lead to different priors

This emphasizes the subjectivity in choosing priors in Bayesian analysis.

189
Q

What was Fisher’s criticism of the rule of succession in Bayesian reasoning?

A

He found it to be flawed and damaging to his own work

This illustrates the complexity and internal conflicts within Bayesian statistics.

190
Q

What is a p-value?

A

A p-value measures how likely it would be to see data like those observed under the null hypothesis.

191
Q

If a p-value is 0.1, how often would you expect to see results as extreme as the observed ones?

A

One time in every ten.

192
Q

What is the significance of a p-value of 0.05?

A

It indicates that results are sufficiently extreme that you’d see it only one time in every twenty.

193
Q

What does it mean to reject the null hypothesis?

A

It means treating the effect as though it is real when the p-value is lower than the alpha level.

194
Q

What is statistical significance?

A

Statistical significance is reached when the p-value is lower than the predetermined alpha level.

195
Q

What is a one-sample t-test?

A

A statistical test that compares the mean of a sample to a known population mean.

196
Q

In the context of hypothesis testing, what does a two-tailed test refer to?

A

A test that considers the probability of extreme results at both ends of the distribution.

197
Q

What is the probability of getting at least thirty-two heads in fifty coin flips, if it is statistically significant?

A

0.03, or 3 percent.

198
Q

What is the purpose of an alpha level in hypothesis testing?

A

It is the threshold for determining statistical significance.

199
Q

What is the fundamental bit of hypothesis testing?

A

You have a null hypothesis and an alternative hypothesis, and you reject the null if the data is sufficiently extreme.

200
Q

What does it mean if p < 0.05 results occur more often than expected?

A

It suggests evidence of some correlation if the null hypothesis is true.

201
Q

What is Bayesianism?

A

A statistical model that incorporates prior knowledge and updates beliefs based on new evidence.

202
Q

Who was Harold Jefferies?

A

A key figure in early scientific Bayesianism who applied Bayes’ theorem to uncertain data.

203
Q

What did Jefferies demonstrate about the Earth’s core?

A

He showed that the core of the Earth is liquid.

204
Q

What does David Howie say about Jefferies’ inferences?

A

They were tentative and advanced with degrees of confidence that were updated with new information.

205
Q

What is the relationship between probability and uncertainty according to Jefferies?

A

Probability describes all uncertainty, not just that associated with data.

206
Q

What was Frank Ramsey’s contribution to probability theory?

A

He suggested that probabilities are beliefs and can be quantified through betting.

207
Q

How does Ramsey’s model help in decision-making?

A

It allows calculation of expected subjective utility based on beliefs and desires.

208
Q

What problem arises if your probabilities do not add up?

A

You can be misled by anyone offering you bets.

209
Q

What was the significance of Bayesian methods during World War II?

A

They were used by scientists to make good inferences from limited data.

210
Q

What role did Alan Turing play during World War II?

A

He helped crack German codes using early computers and Bayesian principles.

211
Q

What was the challenge faced by Turing in decoding messages?

A

The extraordinary number of different possible combinations made it impractical to check all.

212
Q

What did Turing have to assume about combinations of letters?

A

Some combinations were more likely than others based on context.

213
Q

What is the significance of the three-letter sequence E-I-N in Turing’s reasoning?

A

It is considered more likely than other sequences like J-X-Q.

This reasoning reflects Turing’s use of priors in Bayesian statistics.

214
Q

What term did Turing create to refer to a unit of information?

A

ban

This term is comparable to the modern bit or byte.

215
Q

Which statistical methods were being used by insurance underwriters and military quality-control assessors?

A

Bayesian methods

These methods were used to set premiums and minimize testing respectively.

216
Q

Who was the head of the Department of Statistics at University College London in the 1970s?

A

Dennis Lindley

He played a significant role in advancing Bayesian statistics.

217
Q

What was the perception of Bayesianism outside of University College London during the 1970s?

A

It was viewed as a sideshow

Bayesianism faced skepticism and resistance in broader statistical communities.

218
Q

What did Lindley, Bernardo, and de Finetti decide during the first international Bayesian conference in 1976?

A

To hold similar conferences in the future

This led to a series of international Bayesian meetings.

219
Q

When was the first Bayesian world meeting held?

A

1979

It was organized in Valencia as Spain was emerging from fascist dictatorship.

220
Q

What unique tradition developed during the Valencia conferences?

A

The Bayesian cabaret

This included humorous performances related to Bayesian statistics.

221
Q

What was a common sentiment expressed by attendees of the Valencia conferences regarding the experience?

A

They were a lot of fun

Attendees balanced work with leisure activities like siestas and parties.

222
Q

What did George Box parody at the first conference?

A

There’s No Theorem Like Bayes’ Theorem

This was a parody of Irving Berlin’s song ‘There’s No Business Like Show Business.’

223
Q

What is the humorous claim about Bayesian statistics made during the Valencia conferences?

A

Bayesians have more fun

This was reflected in the light-hearted nature of the conferences.

224
Q

What has contributed to the resurgence of Bayesian methods in recent decades?

A

The passing down of Jeffreys’ book and practical applications in various fields

Software engineering and data science have also embraced Bayesian methods.

225
Q

What did Dennis Lindley state about Bayesian statistics in a 1975 conference?

A

It is the only method that can produce sound inferences and decisions

This reflects the strong advocacy for Bayesian methods among its proponents.

226
Q

How did frequentists view Bayesians during the development of Bayesian statistics?

A

As underdogs and up-and-comers

This dynamic created tension between the two camps in statistics.

227
Q

What did George Box admit about the nature of statistical inference in his 1985 paper?

A

Scientific method employs both Bayesian and frequentist inference

This reflects a more ecumenical approach to statistics.

228
Q

What is the term used in professional wrestling that describes maintaining an illusion of reality?

A

kayfabe

This concept was likened to the public debates between Bayesians and frequentists.

229
Q

What does Bayesian inference allow statisticians to do in decision theory?

A

Make statements about the plausibility of a hypothesis

Bayesian methods are essential for evaluating the likelihood of different hypotheses.

230
Q

What is the value of grabbing the snitch in Quidditch compared to scoring a goal?

A

Grabbing the snitch is worth fifteen times scoring a goal

This significantly diminishes the importance of scoring goals for the team.

231
Q

How do you pronounce ‘Lester-shire’?

A

It is pronounced ‘Lester-sher’

This reflects the peculiarities of English place names.

232
Q

What is the implication of the word ‘posterior’ in the context of the text?

A

It suggests that the term will be frequently used throughout the book

The author anticipates humor regarding the word.

233
Q

Who are two notable Bayesians mentioned in the text?

A
  • Harold Jeffreys
  • E. T. Jaynes

They discuss ‘objective Bayesianism’ and the use of logical principles for priors.

234
Q

What did Kevin McConway say about E. T. Jaynes’ attempt at ‘objective Bayesianism’?

A

He stated that Jaynes did not succeed, but he had a good try

This reflects differing opinions on the effectiveness of Jaynes’ approach.