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Zusammenfassung Statistics & Probability cheat sheet $11.32   Add to cart

Summary

Zusammenfassung Statistics & Probability cheat sheet

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Cheat sheet über Statistik aus dem zweiten Semester. Halb deutsch / englisch

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  • February 26, 2023
  • 5
  • 2021/2022
  • Summary
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Cheat Sheef


absolute frequency relative frequency frequency function distribution function
now offen hi in normal
histogram step
by all hi
a hi step
occurs sum of

the Xi -
ni ->
H;.


↑is 1. everywhere least
at continous to the right histgram
amount
2. monotonically
increasing =-



limit 0 & width - Axis
3. lower upper limit




mediEaneven
Mode Arithmetic mean Geometric mean Harmonic mean


Highest sum R


frequency I amount=




6,- in
Quantile / Quartile

rit-quantile given-point y-Axis
-
follow until ifh its the =
point
al at that straightdown
on
graph
to y-Axis is result

YearlXnia*Xnqf b) if interval take &
->
or ithits mean


down to X-Axis

Measures of variation
mean absolute deviation
interquartie range quartile deviation
a as an das-az/+laz-an,
MAD à 414; -
-
=




2
=




①D= 2



variance standard deviation coefficientofvariation

54 E(Xi nj
=
-




1x +,
=




cu =
two dimensional distribution
Scaterprot Marginal distribution Conditional distribution
In z
hij *his hoj
De he Si Ehj./X- 4;sy=Ehijly: r
=




for i=1....k&j 1....independent=




-2 me


↳. nor 1 T =




Shi.Xii 4 hos li =




Variance of
sum

syy sy sy
=


+ +
2.2(yj -




y)14 4)
-




Covariance
difference -sit si-2. Ery-)/y- y
(y 2514j )(yi
= - -




4)
Correlation coefficient
independant Cyy 0
* =

hot other way around CA

(11 0 ->
y are dependent 54 Sy. Sy
=




SSE
rank correlation coeffient coefficient ofdetermination Yi a
=




bj
+




~5 TrgrX),rgry
=

R I",rie
=




Strabl- Ely:- Yi


, Classical probability


↑A oteement
=




->
probability complementary A PA 1 -P(A) =




Conditional probability
->
impossible prob. Zero Dra) 0
has
event - =
Pra
->
events pairwise disjoint PrAnUAnU... An)-EPrAj pralB PrB =




->
difference SetAlB prAB) Pra) -PrAn =
=




->
2 arbitrary events->Prau)=PrA)+ prB)
-


Pran Stochastic independance
-> if A implies =1 = -> PrAl PrB
->
prob. two events simultaneously PrArb)=pra).pisia prai)=PrA &pIBIA pr) =




->
if independent prob. Thats simultan.-PrA1= prat.pr)
partion of it each event Al - > PrAr SprAlj).prj) pri).pri)
-> =




->
Bayes theorem In partition 2; P/B)
-
0 -> each ti holds Pli)=[pril. pri


4fal prob./partition Bayes theorem
He. n. ....
n fills sample +itj 0
=




space entirely HeuteU... Weil pril -
prior prob.; Plib)-> posteriori prob.

Distribution function Discrete random variables
1. each continuous to right a**(x+1y) *(y) 1. f(x) 0
=

=
at




2. monotonically
increasing Fal*(b), if acb 2. EfrXi) 1
=




3. lower limit o &
upper limit 1 3. From 1. & 2. if directly follows frei - 1



Density function xpected values
=

1. f(x) 0
frar a
=



=

Frx) 2...Sofrydx 1
=

=
(x) Exjf)4j)
= ->
if discrete


Variance random variables y=
= fre/axif continuously

V(x (1x =
-




xx)) Rules:
1. Constant al a


Standard deviation 2. Factor =(b.g(y) b. = 5g(y)]
=




3. Sum
(g1(x) g2(x)] ygn(x)] f(gz(X))
* =
+ +




Öx
=
+
Vy) 4. Linear transformation lath. 41 -ab. (y



Variances Standardization
1. Constant Val 0
=

-e
1
always mean O

2. Shift vixtal vix E 0 variance 1
=

=




3. Factor Vib.y bvrx)
=




Ob=(b10x

4. Linear transformation Vatb.y b. VIy =




Garb. (b/Ox
=

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