Topic 5 Flashcards

1
Q

How is a standardised variable calculated?

A
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2
Q

Give the formula for estimated population variance

A
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3
Q

Show the formula for a beta1/beta2 hat confidense internal

A
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4
Q

Show the confidense interval for the variation estimate

A
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5
Q

What are confidense intervals?

A

Random intervals, which once calculated can’t be said to have a probability of containing their parameter, as they either do or don’t. The formula however, has 1-alpha chance of containing the parameter.

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6
Q

How is a two tail test conducted?

A

Null: beta-x = a

Alt: beta-x = b

Use t-alpha/2

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7
Q

Show an ANOVA table for CNLRM

A
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8
Q

What influences our prediction of Yi?

A
  • Distance from mean X increases variation
  • large n decreases variation
  • low sample variance decreases variation
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9
Q

How is a one tail test conducted?

A

Null: beta-x < a
Alt: beta-x > a
Using t-(1 - alpha)

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10
Q

How is the t & F test related?

A

t^2 = F,
where the null is beta2 = 0 and alt beta2 != 0

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11
Q

How can we test to confirm normality

A
  • Histogram of residuals
  • Normal probability plot
  • Jarque - Bern test of normality
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12
Q

How do we examine the normality assumption using a histogram?

A

We make a histogram of eresiduals (ie, residuals in frequency bins) and examine it to see if it looks normal). Can’t say much at all with low sampl numbers.

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13
Q

How do we use normal probability plots to cooberate the normality assumption?

A

Use special graph paper to graph the error terms on the x-axis and on the y-axis, the expected value if they were normal is shown. Hence, a roughly straight line indicates the assumption is pretty dec. Ps. Excel is a cheating liar

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14
Q

How do we use the Jarque - Bern test of normality?

A
  • Only with large samples
  • Measures skewness and kurtosis (concentration around mean)
  • Compares these values with the normal distibution (S = 1 K=2) *maybe* **totally bad memory**
  • Gives a test statistic that is totally chi square
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