M8 - Flashcards

1
Q

Whats correlation?

A

The association between two quantitative variables.

perfect positive correlation = 1
no correlation = 0

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2
Q

Cenral limit Theorem

  • def
  • implication
A
  • The distribution of mean values of samples of the size N that were drwan from the population converges with increasing N towards a normal distribution
  • For samples of a size of above N =30, probabilities can be quantifies as estimates of the mean
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3
Q

Estimates of the mean - sigma

A
  • with a probability of 68% the mean of a random sample is in the range
    müh +-sigma
    (müh - mean value in the population, sigma = standard error of the sample mean)
  • with a probability of 95,5% the mean of the sample is in the range of
    2müh +-sigma
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4
Q

Standardization
-when is it standardized?
-

A
  • a random varable is called standardized when its expected value is 0 and its variance is 1.
  • define a new random variable Sn=x1+x2+xn
  • expected value of Sn: mühn; variance ns²
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5
Q

Hypotheses

  • def
  • criteria for sctientific hypotheses
A
  • are assumptions about structral properties among phenomena
    they point beyond an individual situationa nd can be disproved by empirical data
  • general validity
  • falsifiable
  • phrased as conditional clause/ equality/inequality
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6
Q

general validity

A

is the extent to which a concept, conclusion or measurement is well-founded and corresponds accurately to the real world.

universal proposition / generalizable

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7
Q

falsifable

A

it must be possible to imagine events that are in conflict with conditional clauses

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8
Q

Null hypothesis

Alternative hypothesis

A

H0 contains the statement to be disproved
–> typically claims “there is no difference / effect” –> a statement that can be falsified by finding a significant difference

H1 claims the opposite
–> typically “there is a difference/effect” –> cannot be falsifed since a non-finding of a difference may be due to the fact that the difference was too small

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9
Q

z-test

  • def
  • distribution of z
  • what if p-value is less than the given level of sign
A

compare sample mean with pop mean

z-test: tells us whether the bcoeff for that IV is sign different from zero

  • -> if b is different from zero, then this IV is making a sign contribution to the prediction of the outcome.
  • normally distributed
  • for N > 30
  • KNOWN SD
  • z is normally distributed
  • p-value is less than the given level of sign., H0 must therefore be rejected
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10
Q

one-tailed hypothesis

two-tailed hypothesis

A
  • H1 unequal 10; its either smaller or bigger, may be both

- H1 avg > 20; its bigger but not smaller

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11
Q

difference one and two-tailed tests
- p-value
z-value

A

ONE: compares the sample mean with the pop mean
TWO: compares 2 (in)dependent samples

  • with equal z-values the critical p-value of the on-sd-t. is half as large as the one of the two-s-t.
  • with equal p-values, the critial z-value o the one-s-t is less than the one of the two-s-t
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12
Q

t-test

  • purpose?
  • p-value
A

ONE: compares sample mean with pop mean
TWO: compares (in)dependent samples

  • for N < 30
  • varibles normally distributed
  • almot similar variation
  • UNKOWN SD!
  • p-value states at which significance level we can reject the null hypothesis

t-test: know how well the model fits the data and the contribution of individual predictors
–> linear regression

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