Statistics In caculation be replace in can python ริ จึ จั วั วิ จั = & & - · - = = ↓ ⑨ 6 = ⑤ - = : = +> ~ · / · จ site % - %:: % is = = = %ไ - * & % = is # %ร% & = #6 = & จ งios↳ & % ง % % * ⑤ ↓ & - ⑤ => จ ⑤ ไ = % · ฐ · · % : ⑤ % ⑨ ⑨ & ⑨ 1 * # = = · ว -ร = ~ : = = * ( · ↓ ~ <ไ -> . ~ - รั้ รั จั รั จั ที สี จั สั ร้ รี จี อี - - ⑤ :( =" - aso · == I %. . . . = I ⑤ = ร = = · = - - -> - -ร & - * -ร 5 = % .. = เร 9 = - ⑨ = % % : * * ⑤ ⑨ 5 = จ & % & = & = * =:: ⑤ · · 1 - => * % ⑨ & · - / · ~ -ร % ↓ % = = ( ~ - · · อ 1 / < 3 * · <- * S = => ว % = ::: = : - * = & · &- · : - = · # · ⑨ - - 5 = ↓) = = ⑨ - · / = => : · =ร - · - -& => i = = * % : :ร 1 : > * - % + = = ↓ & %เ · * จึ ร่ สิ สิ จีจึ รี จี จั ที่ จั =(↳ = :โร :ใ - - / :- 1) = : < = = * => 6 % ~> # = ① * & = : * %: ง : : 3 - <- * ง = ↓) /: · = · % 1) ↓s ?, : & ↓ <- ⑤ <- : = = S 3 % ⑤ ⑤ = : = = % % % = = : : น % โ · = % =" งบเ ง :sssssssssss :x : <- - - = / = # · # % ↓ ⑨ I => ( < # ⑤ วั วิ วั <- - - - = 5 ↓ ~s =? * % & = ( & 1 ⑨ # % ↓ ⑤ : 5 = % : - · -( * ว - · % % ↳ % = = 1 - · +- : ↓ & 3 = ①@@@ -- = % = = · - = #ส ↓ ( ↓ = = * % = ( & ( · = I s : = <- -> I % % * = , ( = - { 11 = · + ~- - * = ⑨ # % ⑨ = = ~- # จ => ↑ / %- ท = ~> · ↑ : · & - -> ⑨ & ~ -ร : = ⑤ % = = => - % % & =s = & =sss * % # % = % · % => % % · = :s .. = % <- รี วิ รี วี % - % = = · * / = = % - %3 = =S · = * = % - ว ร + · - = => a1a - * * 1 & % / 3 > % % / % # ~ส # % # * - & & - = 3. = % -> -ก = %" % ⑨ %:: · ( / =ร ! * => % - · - <- &- % - - % · - ; = = จ # ⑤ => ↓I ·pos ↳ * &> / 3 = 3 3- · = S จั จั รี จั วั วิ = % = x = % * % & = ~ ~ & -ก = ⑨ ⑤ 1 / : · = - น = & · · & * = * : = 6 · =ร 1 => % = * % = ↓ + / ⑤ = & - · = + ⑨ * % / ว · % 9 = = ·> + S + · * - = * / ร =ง * ~ = & => ว ( =จ :: = * ⑤ 1 ⑤ * 5 * ~ -ร = 1 => # / = * · · ⑤ / => - & = % · - # ⑤ = % s 3 = = · · = : : ( วี รั วั จี รั มี รั สั่ : : % : + : & # ↓ = - เ จ = = = & " % # :" · · 5 = = 6 - % : 3 · · & < <- & = ↓ & = 5 จ S - ~> & 1 - = ~ ร ⑤ = ⑨ % = % % & I s / · =: 1: ? จะ * & 1 % * = / - () =S % - -ส = · + * = sils, % I = 3) 1, = ↓ · · * ↓ % ·ร ·S = 3) = ⑤ = · · = = % ↓ % ⑤ 5 = - : · > = % - # 3 = = & = < : so F ⑤ = = > & - จุ ต่ ที จุ ที่ วีวี รี วีวั สี รั ทั้ S - = : = ส = % = % + ! ร = + * ⑤ - :จ % ↓I : -ร ( · & - % * = ↓ = ,= ↳( # % /9 แ งจ 1+ * : * ~ = - = ⑨ : ( : = : 1 · = - · = / ⑤ ↓) # % = + & / จ & ร ง = =ฐ = = & · ฐ · ( %สร = / = %S : % = * =5 ⑨ ( = - % · & ! " /จ สี วั % + & & & % = * · slot " 7 % - · # +- · ⑤ : - = => % · 1 ~- = ว + * & · & = + ⑤ · = & % =8 -I ·= - ( ⑨ is t % : % * Glass · ooooooooooooooooooooolo : ·ร 3 = - st · +- ⑨ ⑤ * = s => & สี < · &@ @ # * = & = = 9 : : / - ⑤ · => - - : : ⑤ ⑨ = " = / # = % % · I · foliatiss * สี จึ วั วั จี ที จั ล ⑤ = I = %: = & =I ⑤ : · & & - 5 * = # * = · · - = - · - ⑤ => : + # · = ( = ร = s · = = · % * = : - = = ⑤ < + # + & = & = ⑤ % ·ฐ · %ร & = ว & - · · : ↓ · & : #= ! : * + ↓ ⑨ - + · = : · · - : = & * 5 & => - % = - ง. ( & ↓ % ·@ = => => = % * ⑤ 5 - - % ~> => - < = ~ + # ว = ⑤ * 5 ⑤ & * - + # + ↓ ⑤ S = จ = - - & *ไ · ~ % = % · S = · / · * S % · & # =s & = น · ~ = % : : ⑤ * Uniform Distribution ( the probability 29: Guessing Rolling between a a Birthday a to be is every day is pie => roll discretel a die one equally can time be the same someone birthday probability of 1 probability = is every day 16 1 = 2 : "G : / Wating Bus stops => if bus arrives every when PCX) " b he 6: minutes the you arrived in 16 probability the of found every times a bus Bernoulli Distribution ( Any events 99: Flipping with only coin a discretel single a is only trial and get only head + ails true false Quiz => Only get True False PC success) = 1 PC Failure ): 1- 1 &2x) 1- PCX two out comes ริ รั วี คิ วิ -> ,D ⑤ = = : => "" ~"21 -LI % , % & % · = ~ ( <- 1 => * = = % = S & (1) - จ S โ : & · > = - % & o ,LLllId = &> : · + => < # ~ -ร ล * # จ = เท = ⑨ " + · ร & * -> % % = · <ร - - ~ : = ~ + ⑤ · · + = = % : : = = = · - ·จ ง & opens ss to : - · · · & ⑨@ - I - - ⑤ : S · ⑤ : · < => i # S % = 5 · 5 => Poisson Distribution deals is discrete requried, with a a 0 Es: A dog Events bark three times p2X = x) = in two 15 the represents are times in a occurring in frequency expected with which an event occurs number of event and randomly can take want to independently know the 1: 1 PCX x 0 that period. a sacound. We second. e' st the specific interval place 8 with 1 2 3 4 .... . likelihood of dos bart รั วิ % % S ~> & ~- = % : = ↑ ⑤ - & > 2 / = - · % - - - - - - = · % = I + ⑤ + T I / % = = - % S S + & = # I = &> · ~ ↓ S · =: s - : - -> Exponential Distribution I continues - PLx) mostly used inverse off with length of time poisson distribution ป much a How time given between a of events events long the next Will OCCUV M: How many in How this events occur a time many interval ง - 2 3 ' cline poisson Exponential is How C interval events in will occur Fax : I - effi รั จุ รี ร้ สั ฐิ &> - · = ⑨ = - ↓ · = & - - - & ด · ↳ - 9 = ⑤ · : - * · ⑨ ·ร * = = asos deses = : 5 % = = * ~ ⑨ * = = จ -ร = = = <- = - ↓ & & = = % % : :ร - = 5 o ร # = % = # = S = - 1 % ↓ + = ↓ = => = = + : = & ⑨ 5- : & is is == s ⑤ร ว % - S & so % ↓ · /ร - - จึ จี้ จึ จั จี จึ จั ที % = ง : % = * * . % % . · - : ⑨ = - % = = > # => = * = = = = -ง 1 % & = % # = > · % จ - % = -> & - % = => - # - : * % =ก * · - & 8) ง & < & => : = +- · = 3: : 1 - # 8+ : · - ·C ⑤ 2. * ⑤