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BNAD 276 Week 4 Notes

by: madelinef

BNAD 276 Week 4 Notes BNAD 276 001

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Class notes from week 4 of BNAD 276
Statistic Inference in Management
Dr. Suzanne Delaney
Class Notes
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This 2 page Class Notes was uploaded by madelinef on Friday September 16, 2016. The Class Notes belongs to BNAD 276 001 at University of Arizona taught by Dr. Suzanne Delaney in Fall 2016. Since its upload, it has received 5 views.


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Date Created: 09/16/16
BNAD 276 Week 4 Class Notes  Deviation Score- average-number. o 0 means average o a negative number can be good or bad. It depends on the situation it is in. o Example: the average is 6’0”.  6’2”= +2 above average  5’8”= -4 below average o (x-) x= your data and =average  average deviation score- add up deviation scores and divide by amount. It will always be 0 unless you did it wrong.  To get a standard deviation you want to square the deviation, add it up x−¿ ¿ ¿2 and square root it. ( ¿ ) ¿ ¿ Σ √¿  Standard deviation- the average amount by which observations deviate on either side of their mean  4 equations to know o Notes: o = sigma o S and = standard deviation sample (s) and population () o S^2 and ^2= variance sample (s) and population () x−¿ ¿ 2 x−x )2 o Sum of squares= ¿ and Σ Σ¿ √ n−1 ¿ o n-1= degree of separation  standard deviation squared= variance  n-1 is degrees of freedom o you lose a degree of freedom every time you guess (for every parameter you estimate) o it’s a mathematical correction because of estimating  difference is standard deviation squared is variance. Variance square rooted is standard deviation. o Numerator= sum of squares.  Example X Deviation Standard deviation 1 -4 (-4)^2 = 16 2 -4 (-3)^2= 9 3 -2 (-2)^2= 4 4 -1 (-1)^2= 1 5 0 0^2= 0 6 1 1^2= 1 7 2 2^2= 4 8 3 3^2= 9 9 4 4^2= 16 Σ=45 60 Deviation: square root of 60/9= 6.67 (this is the standard deviation)  1 Standard deviation above and below mean is 68% of population  2 standard deviations above and below mean is 95% of population  3 standard deviations above and below mean is 99.7% of population  Z-Score o 100% under curve o 50% (0.5) Is above mean and 50% of below mean o Why do we care about raw scores?  Because they give us the ACTUAL number o Proportions= percent of/ percentile o The raw scores and proportions do not correrlate naturally. But they do both correrlate to Z scores so we change them to that to compare!  Z= x-/


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