qu.1.topic=Randomness@ qu.1.1.mode=key words@ qu.1.1.name=Frequentist approach@ qu.1.1.question=

Assigning probability $1∕2$to the event that a coin will land heads and probability $1∕2$to the event that a coin will land tails is a mathematical model that summarizes our experience with many coins. In the context of statistics, this is called the whatto probability.

@ qu.1.1.answer=(frequentist approach)@ qu.1.1.info=@ qu.1.2.mode=key words@ qu.1.2.name=Assigning probability as summary@ qu.1.2.question=

Assigning probability $1∕2$to the event that a coin will land heads and probability $1∕2$to the event that a coin will land tails is a mathematical model that what? with many coins.

@ qu.1.2.answer=(summarizes our experience)@ qu.1.2.info=@ qu.1.3.mode=true false@ qu.1.3.name=Deterministic process@ qu.1.3.question=

A coin flip is a deterministic physical process, subject to the physical laws of motion.

@ qu.1.3.choice.1=

True

@ qu.1.3.choice.2=

False

@ qu.1.3.info=@ qu.1.3.answer=1 @ qu.1.4.mode=key words@ qu.1.4.name=Bands of initial conditions@ qu.1.4.question=

A coin flip is a deterministic physical process, subject to the physical laws of motion. For high initial velocities there are very narrow bands of whatdetermine the outcome of heads or tails.

@ qu.1.4.answer=(initial conditions)@ qu.1.4.info=@ qu.1.5.mode=key words@ qu.1.5.name=Assignment of half and half@ qu.1.5.question=

The assignment of probabilities $12$to heads and tails is actually a statement of the whatof the initial conditions that determine the outcome precisely.

@ qu.1.5.answer=(measure)@ qu.1.5.info=@ qu.1.6.mode=key words@ qu.1.6.name=Market theory@ qu.1.6.question=

The whatof asset prices claims that market prices follow a random path, without any influence by past price movements.

@ qu.1.6.answer=(Random Walk Theory)@ qu.1.6.info=@ qu.1.7.mode=key words@ qu.1.7.name=Predicting the market@ qu.1.7.question=

This [Random Walk] theory says it is impossible to predict which direction the market will move at any point, especially when.

@ qu.1.7.answer=in the (short term)@ qu.1.7.info=@ qu.1.8.mode=key words@ qu.1.8.name=Postulating a distribution@ qu.1.8.question=

More refined versions of the random walk theory postulate a whatfor the market price movements.

@ qu.1.8.answer=(probability distribution)@ qu.1.8.info=@ qu.1.9.mode=key words@ qu.1.9.name=Mimicing a coin flip@ qu.1.9.question=

The random walk theory mimics the mathematical model of a coin flip, substituting a whatof outcomes for the ability to predict what will really happen.

@ qu.1.9.answer=(probability distribution)@ qu.1.9.info=@ qu.1.10.mode=key words@ qu.1.10.name=Technical analysis@ qu.1.10.question=

Whatclaims to predict security prices with the assumption that market data, such as price, volume, and patterns of past behavior predict future (usually short-term) market trends.

@ qu.1.10.answer=(Technical analysis)@ qu.1.10.info=@ qu.1.11.mode=true false@ qu.1.11.name=Simplest model@ qu.1.11.question=

The simplest, most common, and in some ways most fundamental example of a random process is stock market prices.

@ qu.1.11.choice.1=

True

@ qu.1.11.choice.2=

False

@ qu.1.11.info=@ qu.1.11.answer=2 @ qu.1.12.mode=key words@ qu.1.12.name=Mathematical model@ qu.1.12.question=

To assign the probability $12$to the event that the coin will land heads and probability $12$to the event that the coin will land tails is a whatthat summarizes our experience with many coins.

@ qu.1.12.answer=(mathematical model)@ qu.1.12.info=@ qu.1.13.mode=key words@ qu.1.13.name=Inability@ qu.1.13.question=

The assignment of probabilities $12$to heads and tails is actually a statement of our whatto measure the initial conditions and the dynamics precisely.

@ qu.1.13.answer=(inability)@ qu.1.13.info=@ qu.1.14.mode=true false@ qu.1.14.name=Precision in coin-flipping@ qu.1.14.question=

True or False: It is possible to construct a precise coin-flipping machine that can flip many heads in a row by controlling the initial conditions precisely.

@ qu.1.14.choice.1=

True

@ qu.1.14.choice.2=

False

@ qu.1.14.info=@ qu.1.14.answer=1 @ qu.1.15.mode=true false@ qu.1.15.name=Testing the random walk theory@ qu.1.15.question=

Random walk theory does not yet have predictions that can be tested against evidence.

@ qu.1.15.choice.1=

True

@ qu.1.15.choice.2=

False

@ qu.1.15.info=@ qu.1.15.answer=2 @ qu.1.16.mode=true false@ qu.1.16.name=Hawking’s definition of a theory@ qu.1.16.question=

The cosmologist Stephen Hawking says in his book A Brief History of Time A theory is a good theory if it satisfies two requirements: it must accurately describe a large class of observations on the basis of a model that contains only a few arbitrary elements, and it must make definite predictions about the results of future observations. True of False: The random walk theory of markets does both.

@ qu.1.16.choice.1=

True

@ qu.1.16.choice.2=

False

@ qu.1.16.info=@ qu.1.16.answer=1 @ qu.1.17.mode=true false@ qu.1.17.name=True Randomness@ qu.1.17.question=

True or False: True randomness does not exist. All of the physical universe is deterministic, anything less is a mere summary of our inability to completely describe the situation.

@ qu.1.17.choice.1=

True

@ qu.1.17.choice.2=

False

@ qu.1.17.info=@ qu.1.17.answer=2 @ qu.1.18.mode=key words@ qu.1.18.name=When numbers are not random@ qu.1.18.question=

In algorithmic complexity theory, a number is not random if it is what?

@ qu.1.18.answer=(computable)@ qu.1.18.info=@ qu.1.19.mode=key words@ qu.1.19.name=What makes a number computable@ qu.1.19.question=

Roughly, a computable number has a whatthat will generate its decimal digit expression.

@ qu.1.19.answer=(algorithm)@ qu.1.19.info=@ qu.1.20.mode=true false@ qu.1.20.name=Irrational numbers@ qu.1.20.question=

True of False: Irrational numbers, such as some square roots, which have nonrepeating, nonterminating decimal expansions are necessarily random, in the sense of algorithmic complexity theory.

@ qu.1.20.choice.1=

True

@ qu.1.20.choice.2=

False