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Transcript of 14s L01 Intro
8/9/2019 14s L01 Intro
http://slidepdf.com/reader/full/14s-l01-intro 1/39
STAT 344 Probability and
Statistics for Engineers andScientists I
Section 01: MW 1:30 PM – 2:4 PM
Professor: !r" #ennet$ Stra%%eri
E&ail: 'stra%%e(g&)"ed)
8/9/2019 14s L01 Intro
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Introd)ction
#ennet$ Stra%%eri
◦ Mat$e&atics Ed)cation *P$"!+ 2013+,-A."
◦ Statistics *MS+ 2004+ ,-A.◦ /inance *S+ 2001+ T.
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Infor&ation
My areer oals: Teac$ingstatistics"
◦ I&5ro6e t$e 7ay statistics is ta)g$t
to all )ndergrad)ate st)dents"◦ En$ance st)dent8s )nderstanding
and reasoning abo)t statistics"
9obbies: 5laying dr)&s+ eercise+and slo7 5itc$ softball"
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W$at is *or are. Statistics;
Statistics as a <eld of st)dy is t$escience of learning fro& data"
T$e ter& Statistics can also be)sed to describe n)&erical facts*co&&on 5erce5tion.
/irst+ 7e 7ill consider so&ede<nitions of statistics =
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Wi'i5edia !e<nition of Statistics
A &at$e&atical science5ertaining to t$e collection+
analysis+ inter5retation ore5lanation+ and 5resentation ofdata" Also )sed for &a'inginfor&ed decisions"
$tt5:>>en"7i'i5edia"org>7i'i>Statistics
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My /irst ,ndergrad StatProfessor
A body of conce5ts and
&et$ods )sed to collect andinter5ret data concerning a5artic)lar area of
in6estigation and to dra7concl)sions in sit)ations7$ere )ncertainty and
6ariation are 5resent"
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?)r Tetboo'
Statistics is a science t$at $el5s )s&a'e decisions and dra7 concl)sionsin t$e 5resence of 6ariability"
Statistics deals 7it$ t$e collection+5resentation+ analysis+ and )se ofdata to &a'e decisions+ sol6e
5roble&s"
Statistics is t$e science of data"
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Si&ilarities of t$e!e<nitions
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oncl)sions abo)tStatisticsStatistics is deals 7it$:
◦ @easoning 7it$ data"
◦ ollecting+ organi%ing+ s)&&ari%ing+ andanaly%ing infor&ation fro& data to dra7concl)sions+ ans7er )estions+ or gain
)nderstanding"
◦ !escribing and )nderstanding 6ariability"
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oncl)sions abo)tStatisticsStatistics is a science t$at in6ol6es
t$e etraction of infor&ation fro&
data obtained fro& a st)dy or a
sa&5le" It in6ol6es:
• !esigning t$e st)dy or sa&5ling
5roced)re• ollecting and analy%ing t$e data
• Ma'ing inferences abo)t t$e 5o5)lation
based )5on infor&ation in a sa&5le"
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Ty5es of Statistical St)dies
@etros5ecti6e st)dies: Analysis of datacollected in t$e 5ast *$istorical data."
?bser6ational st)dies: )rrent 5assi6eobser6ation of s)bBects 7it$o)tin6estigator8s inter6ention"
!esigned E5eri&ents: )rrentobser6ation of s)bBects 7it$in6estigator control of obser6ationalconditions"
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T7o ranc$es of Statistics
!escri5ti6e Statistics – consistsof &et$ods of collecting+
organi%ing+ s)&&ari%ing+ and5resenting data in an infor&ati6e7ay"
Ea&5les
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T7o ranc$es of Statistics
Inferential Statistics – a body of&et$ods )sed to dra7
concl)sions or inferences abo)tc$aracteristics of 5o5)lationsbased on sa&5le data"
An )nderstanding of 5robability7ill be necessary *$a5ters 2 – 4.
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?rgani%ation of Statistics
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ote
All t$e de<nitions of statistics&ention data"
W$at are data;
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!ata
Data are n)&erical facts aren)&bers 7it$ a contet"
◦ Ea&5les=
ote+ data are &ostly n)&erical+ b)tnot al7ays"
◦ Ea&5les=
We 7ill be concerned 7it$ $o7 dataare collected and organi%ed"
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Syllab)s+ o)rse Policies+ CSc$ed)le
See lac'board=
$tt5:>>&y&ason"g&)"ed)
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Ter&s relating to data
Indi6id)als *s)bBects or e5eri&ental )nits. –obBects described by a set of data *Peo5le orot$er t$ings.
-ariable – any c$aracteristic of an indi6id)al*can ta'e diDerent 6al)es for diDerentindi6id)als.
-al)es of a 6ariable are t$e 5ossibleobser6ations of t$e 6ariable
!ata are t$e obser6ed 6al)es of t$e 6ariable
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M)sic Ea&5le
Most of yo) $a6e an iPod oriT)nes *or so&e ot$er &)sic
5rogra&."
Ass)&e t$at t$e songs listed in
yo)r iT)nes 5rogra& are t$eindi6id)als" Pro6ide so&e6ariables t$at describe t$ese
indi6id)als=
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Ty5es of -ariables
ategorical – 5laces an indi6id)al intoone of se6eral gro)5s" Also+ a6ariable t$at can be identi<ed si&5ly
by noting its 5resence"
◦ o&inal data do not $a6e any nat)ralorder"
◦ ?rdinal data do $a6e a nat)ral order
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Ty5es of )antitati6e !ata
!iscrete – ass)&es 6al)es t$atcan be co)nted
◦ Ea&5les
ontin)o)s – can ass)&e all
6al)es bet7een any t7o s5eci<c6al)es
◦ Ea&5les
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!ata !istrib)tion
T$e distrib)tion of a 6ariable tells)s 7$at 6al)es it ta'es and $o7often it ta'e t$ese 6al)es"
9o7 n)&erical data fall or liealong t$e Fais"
an be seen 7it$ a table orgra5$"
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Po5)lations and Sa&5les
Po5)lation – consists of all s)bBects or ite&sof interest" It is t$e gro)5 being st)died"
Sa&5le – a gro)5 selected fro& t$e
5o5)lation *a s)bset of t$e 5o5)lation." It5ro6ides infor&ation )sed to inferinfor&ation abo)t 5o5)lations"
Sa&5les are often )sed beca)se gettingaccess to t$e entire 5o5)lation isi&5ractical"
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P)r5ose of Sa&5ling
As 7e 5roceed+ t$e idea is t$at 7e7ant to &a'e inferences abo)t5o5)lations fro& t$e collection and
analysis of sa&5le data"
T$e design of t$e sa&5ling 5rocessbeco&es i&5ortant"
A good sa&5ling design 5er&its 6alidinferences to be &ade"
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o&5)ter Tools ,sed in t$eo)rse
Minitab – )sed for data&ani5)lation+ calc)lations+gra5$ics 5resentation for
$o&e7or'"◦ Men) syste&
◦ ra5$ics
◦ o&5le co&5)tations andsi&)lation
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Statistics and Engineering
W$y ta'e a statistics co)rse asan engineering &aBor;
9o7 are t$ese t7o <eldsconnected;
To start+ bot$ <elds can bedescribed )nder t$e real& ofscience"
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Science
Science: t$e st)dy of t$e nat)ral7orld
◦ *Gatin: scientia H 'no7ledge.
Scientists as' )estions abo)tt$e 7orld=
◦ W$at is o)t t$ere;◦ 9o7 do t$ings 7or';
◦ W$at r)les can be ded)ced toe5lain t$e 5atterns 7e see;
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Engineering
Engineering is t$e 5rocess ofdesigning t$e $)&anF&ade7orld"
◦ *engineer: fro& Gatin ingeniare Hdesign and ingeni)& H cle6erin6ention.
Engineers &odify t$e 7orld tosatisfy 5eo5le8s needs and 7ants"
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onnection: Science andEngineering
Scienti<c 'no7ledge infor&sengineering design"
In addition+ &any scienti<cad6ances 7o)ld not be 5ossible7it$o)t tec$nological tools
de6elo5ed by engineers"
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Engineering
Anot$er )sef)l de<nition: design)nder constraint"
So&e constraints◦ Ti&e
◦ Money
◦ A6ailable &aterials◦ En6iron&ental reg)lations
◦ Ga7s of nat)re *i"e" science.
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onnection to Statistics
-ariability a&ong any constraint is nearlycertain to eist"
Statistical &et$ods 5ro6ide an ecellent
7ay to 6is)ali%e+ )nderstand+ &eas)re+and analy%e t$is 6ariation"
-ariability &eans t$at s)ccessi6eobser6ations of a syste& or 5$eno&enondo not 5rod)ce eactly t$e sa&e res)lt"
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Engineering Met$od *fro&tet.
Ste5s 2 – 4 &ay need se6eraliterations to obtain <nal sol)tion"
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Anot$er connection
onse)ently+ engineers &)st'no7 $o7 to
◦ eciently 5lan e5eri&ents
◦ collect data◦ analy%e and inter5ret data
◦ )nderstand $o7 t$e obser6ed data
are related to t$e &odel 5ro5osedfor t$e 5roble& )nder st)dy"
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Ea&5le: -ariability
lass Mil' ontainers+ ist$ere eactly a gallon *12Jo%". of &il' in t$ere;
T$ese bottles are <lled 7it$an a)to&atic &ac$ine"
T$e ca5acity is deter&ined
by t$e eternal 5ro<le oft$e bottle and t$e glass7all t$ic'ness"
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-ariability
T$e bottles are &ade on &)ltiF$ead a)to&atic &ac$ines bydro55ing gobs of &olten glass
into &etal &olds+ &a'ing t$e&$allo7+ and t$en inKating t$e&7it$ co&5ressed air )ntil t$ey <ll
t$e &old"
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-ariability
T$e eternal 5ro<le can beaDected by diDerent settings ateac$ 7or' station"
◦ Mold diDerences◦ /l)ct)ations in air 5ress)re
◦ Sagging after release fro& &old
◦
Malf)nctioning of a)to&atic ti&inggear"
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-ariability
Wall t$ic'ness is aDected by◦ ob feeder settings
◦ -iscosity of t$e glass
◦ Te&5erat)re◦ T$e action of t$e s$ears 7$ic$ c)t
s)ccessi6e gobs fro& t$e contin)o)sKo7 of t$e feeder"