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32 Cards in this Set
- Front
- Back
varience in percent means
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sq rt of P*(1-P)/N
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covarience
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1/n-1 * sigma of xi-xm*yi-ym
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what factors contribute to observed corrilation of x and y
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reserve causality
unboserved heterogeneity selection bias |
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n=16 use t or z
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t!
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if the mean is less than the median then?
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skewed to left
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beta1=
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cov(x,)/var (X) or corr xy * sdy/sdx
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bayes theorum: all of it
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b|a= a|b*b/a
A= A|B* B+A|not b* not b |
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when can we use beta?
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unbais: cov x,e=0
existence= var x does not equal zero var e =0 efficency |
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discreate random variable mean
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n*p+n*p+n*p etc
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discreate random varaible varience
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sigma (xi-xm)^2*pi
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random binaomial variance
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n*p*(1-p)
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random binomial mean
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n*p
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beta= zero means?
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no effect of x on y
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centeral tendency?
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mean median and mode
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var of x,y in solving x-y
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sq rt (varx/nx+vary/ny)
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how to make OLS more persise?
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more observations (greater n)
more varaition in explanatory variable better fit to the data in the first place |
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estimate SD
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1/4th the range of the data
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five number summary?
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min 25th median 75th max
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chebyshevs theorum
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1-1/k^2 of the data is within k SD of the mean
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good way to use pie charts?
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when placed side by side its easy to see diffference
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type 1 error
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rejecting the correct thing
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type 2 error
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accepting something you should reject
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varience in beta1
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sq rt (vare)/((n-2)*(var x))
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difference in a prediction or forecast?
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prediction gives average values of y
forecast gives actual values of y |
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slope of beta
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cov x,y/sx^2
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y intercept
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mean of y- beta1*mean of x
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corr
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covxy/(sx*sy)
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e(fx))=F(e(x))
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false
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e(a+b*x)= a+B*e(x)
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true
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whats an estimator
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a rule, formula, or method for trying to determine the parameter of a population
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binomial variance
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n*p*(1-p)
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uniform distribution variance
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1/12*(x1-x2)^2
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