lecture 4 Flashcards

1
Q

what are the 2 properties of estimators

A

unbiased: expected value= unknown true value
2. estimator is efficient: has lowest possible variance in the class of estimators under considerations

there will be a tradeoff between bias and efficiency

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2
Q

what are the Guass markov assumptions

A

The error has expected value zero

The errors are serially uncorrelated

The errors have constant variance

The X variable is non-stochastic
(fixed in repeated samples)

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3
Q

under markov assumptions what is the best linear unbiased estimator

A

OLS, lowest vairance in the class

so it the most efficient

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4
Q

what is statical inference using an OLS estiamtor

A

process of using data to make inferences
about unknown population parameters

for example hypothsis tests

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5
Q

what do you need to conduct a hypothesis

A

A hypothesis to be tested (usually described as the null
hypothesis) and an alternative against which it can be tested.

  1. A test statistic whose distribution is known under the null
    hypothesis.
  2. A decision rule which tells us when to reject the null
    hypothesis and when not to reject it.
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6
Q

what is a type 1 error

A

null hypothesis is true but rejected

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7
Q

what is a type 2 error

A

null hypothesis is false but accepted

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8
Q

what is a critical value

A

a value corresponding to a predetermined
p-value. For example a 5% critical value is a value of the test
statistic which would yield a p-value of 0.05.

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