Notes for SAS Programming Fall2009

7/25/2019 Notes for SAS Programming Fall2009

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Notes for SAS programming

Econ424

Fall 2009


2/88

Why SAS?

Able to process large data sets!

Easy to cope "ith m#ltiple $ariables

Able to trac% all the operations on the data sets!

&enerate systematic o#tp#t

S#mmary statistics

&raphs 'egression res#lts

(ost go$ernment agencies and pri$ate sectors #se

SAS


3/88

Where to find SAS?

)he (S Windo" $ersion of SAS is only a$ailable on camp#s* class "ebsite+ ,comp#ter reso#rces-+ ,.n/camp#s comp#ter lab-* list comp#ter lab location+ ho#rs and soft"are

o# can access SAS remotely $ia gl#e1#md1ed#+ b#t yo# cannot #se theinteracti$e "indo"s

* #se a sec#red telnet e1g1 ssh! to remotely login gl#e1#md1ed# "ith yo#rdirectory 3 and pass"ord

* type ,tap sas- to tell the system that yo# "ant to access SAS* #se any tet editor say pico! to edit yo#r sas program say myprog1sas!1 o#

can also create the tet/only 1sas file in yo#r 56 and sec#rely! ftp it intogl#e1

* n gl#e+ type ,sas myprog1sas 7- "ill send the sas program to r#n in the

bac%gro#nd1* )he comp#ter "ill a#tomatically generate myprog1log to tell yo# ho" each

command r#ns in sas1 f yo#r program prod#ces any o#tp#t+ the o#tp#t "illbe a#tomatically sa$ed in myprog1lst1 All in the same directory as yo#r 1sasfile1


4/88

'oadmap

)hin%ing in ,SAS-

8asic r#les

'ead in data 3ata cleaning commands

S#mmary statistics

6ombine t"o or more datasets ypothesis testing

'egression


5/88

)hin%ing in ,SAS-

What is a program?* Algorithm+ recipe+ set of instr#ctions

o" is programming done in SAS?

* SAS is li%e programming in any lang#age: Step by step instr#ctions 6an create yo#r o"n ro#tines to process data (ost instr#ctions are set #p in a logical manner

* SAS is N.) li%e other lang#ages:

Some synta is pec#liar to SAS Written specifically for statistics so it isn;t all/p#rpose 6anned processes that yo# cannot edit nor can yo# see the

code


6/88

)hin%ing in ,SAS-

6reating a program

* What is yo#r problem? ta%e pro


7/88

8asic r#les >! * organie files

1sas * program file

1log * notes+ errors+ "arnings

1lst * o#tp#t

1sas@bdat * data file library * a cabinet to p#t data in* 3efa#lt: Wor% library

temporary+ erased after yo# close the session

* 5ermanent library

libname mylib ,m:-B mylib1mydata

C a sas data file named ,mydata- in library ,mylib-

r#n and recall 1sas


8/88

8asic r#les 2! // program

e$ery command ends "ith B

format does not matter

if C> then yC>B else yC2Bis the same as

if C> then yC>B

else yC2B

case insensiti$e

commentD this is commentBD this is comment DB


9/88

8asic r#le =! * $ariable

)ype* n#meric defa#lt+ digit+ 1 stands for missing $al#e!

* character G+ defa#lt digit+ blan% stands for missing!

Hariable names* IC=2 characters if SAS 910 or abo$e

* IC characters if SAS or belo"

* case insensiti$e

(#st start "ith letter or ,J- Jname+ myJname+ ipK+ #JandJme

/name+ my/name+ Kip+ perL+ #7me+ myM"+ myGsign


10/88

8asic r#les 4! * data step

3ata step3A)A ne"dataB

set pro

obs2

obs n

define

,frac#nins#red-

define

,percent#nins#red-

o#tp#t data,ne"data-

obs>

obs n

create a ne" data set called ,ne"data- in

the temporary library

#se the data set called ,pro


11/88

8asic r#les K! * proc step

5'.6 step

5'.6 5'N) dataCne"dataB

$ar frac#nins#red percent#nins#redB

title ,print o#t ne" data-Br#nB

Action

3ataso#rce

Signal the end of 5'.6 step+

co#ld be ignored if this is

follo"ed by a 3ata or 5roc step


12/88

'ead in data >! * table editor

)ools * table editor

choose an eisting library or define a ne"

library rename $ariable

sa$e as


13/88

'ead in data 2! * by program

3ata format

*3atalines enter the data in the program!

*Eisting data tet+ comma or tab delimited*Eisting data tet+ fied "idth

*From an eisting ecel file


14/88

)he follo"ing se$eral slides "on;t be

co$ered in class1 8#t yo# are "elcome to

#se them by yo#rsel$es1


15/88

'ead in data 2! // datalines

data testdata>B

infile datalinesB

inp#t id height "eight gender G ageB

datalinesB

> O >44 ( 2=2 @ 1 ( =4

= O2 99 F =@

B

D yo# only need one semicolon at the end of all data lines+ b#t the

semicolon m#st stand alone in one line D

proc contents dataCtestdata>B r#nB

proc print dataCtestdata>B r#nB

No B #ntil yo# finish all

the data lines


16/88

'ead in data =! * more datalines

D read in data in fied col#mns D

data testdata>B

infile datalinesB

inp#t id > height 2/= "eight 4/O gender G@ age /9B

datalinesB

>O>44(2=

2@ (=4

=O299 F=@

B


17/88

'ead in data 4! * more datalines

data testdata>B

infile datalinesB

inp#t id : >1 height : 21 "eight : =1 gender : G>1 age : 21B

datalinesB

> O >44 ( 2=

2 @ 1 ( =4

= O2 99 F =@

B


18/88

'ead in data 4! * more datalines

Dalternati$elyB

datatestdata>B

infile datalinesB

informat id 1.height 2."eight 3.gender G>1 age 2.B

inp#t id height "eight gender ageB

datalinesB

> O >44 ( 2=

2 @ 1 ( =4

= O2 99 F =@

B


19/88

'ead in data K! * 1cs$

data testdata>B

infile datalines dlmCP+; dsd misso$erB

D "hat if yo# do not ha$e dsd andor misso$er D

inp#t id height "eight gender G age BdatalinesB

>+ O+ >44+ (+ 2=

2+ @+ + (+ =4

=+ O2+ 99+ F+ =@B D "hat if yo# forget to type 2= D

r#nB


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'ead in data O! * 1cs$ file

D sa$e the pro


21/88

2>

'ead in data @! * from ecel

filename myecel ,(:pro


22/88

22

'ead in data @! * from ecel

8e caref#l

SAS "ill read the first line as $ariable names+ and ass#methe ra" data start from the second ro"1

SAS assigns n#meric and character type a#tomatically1Sometime it does ma%e mista%e1


23/88

3ata cleaning >! * if then

Format:

F condition )EN actionB

ETSE F condition )EN actionB

ETSE actionB

Note:

>! the if/then/else can be nested as many as yo#

"ant2! if yo# need m#ltiple actions instead of one

action+ #se ,3.B action>B action2B EN3B -


24/88


C or EU means eV#als

C or NE means not eV#al

X or &) means greater than

I or T) means less than XC or &E means greater than or eV#al

IC or TE means less than or eV#al

in means s#bset

* if gender in P(;+ PF;! then 11B (#ltiple conditions: AN37!+ .'Y!


25/88


Dreading in program of proK )EN 11B

2!missing $al#e is al"ays co#nted as the smallest negati$e+ sofrac#nins#redC1 "ill satisfy the condition frac#ins#redI01>K1 f yo# "antto ignore the missing obs set the condition as 0ICfrac#nins#redI01>K1


26/88


* (#ltiple actions in each branchB

data proK AN3 #nins#redX>000000 )EN 3.B

#nins#redgrpC0B #nins#redpopCPo$er > millionRB

EN3B

ETSE 3.B

#nins#redgrpC1B #nins#redpopCPless than > millionRB

EN3B

r#nB

proc print dataCpro


27/88


DZse if commands to choose a s#bsampleB

data pro


28/88

3ata cleaning >! * eercise

still #se pro if frac#nins#red I01> lo"!

2 if 01>ICfrac#nins#redI01>K mid/lo"!

= if 01>KICfrac#nins#redI012 mid/high!

4 if frac#nins#redXC012 high!1


29/88

3ata cleaning >! * eercise ans"er

data pro then ne"grpC>B

else if frac#nins#redI01>K then ne"grpC2Belse if frac#nins#redI012 then ne"grpC=B

else ne"grpC4B

r#nB

proc contents dataCpro


30/88

Sa$e data

D Sa$e in sas formatB

libname mylib ,(:-B

data mylib+pro


31/88

5ages =>/=4 are optional material fordata cleaning1

)hey are not reV#ired+ b#t yo# may

find them #sef#l in the f#t#re1

We s%ip them in the reg#lar class1


32/88

3ata cleaning 2!

* con$ert $ariable typeN#meric to character:

age>Cp#tage+ G21!B

age and age> ha$e the same contents b#t different formats

6haracter to n#meric:

age2Cinp#tage>+ >1!B

no" age and age2 are both n#meric+ b#t age2 is chopped at the firstdigit

)a%e a s#b string of a character

age=Cs#bstrage>+2+>!B

no" age= is a s#b string of age>+ starting from the second digit ofage> the meaning of ,2-! and ha$ing one digit in total the meaningof ,>-!1


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3ata cleaning 2! / eample

* we want to convert studid 012345678 to 012-345-678;

data testdata2;

infile datalines;

input studid : 9 studna!e : "1;

datalines;

012345678 #

135792468 $

009876543 %

;

proc print; run;

data testdata2;

set testdata2;

if studid &' 1()7 ten studid1+ ,00..co!press/put/studid "9;

else if 1()7 &( studid &' 1()8 ten studid1+,0,..co!press/put/studid

"9;

else studid1+ put/studid "9;

studid2+sustr/studid113..,-,..sustr/studid143..,-,..

sustr/studid173;

proc print; run;


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3ata cleaning 2! / eercise

ou ave te followin data variales in seuence are

score1 score2 score3 score4 score5:

123-45-6789 100 98 96 95 92

344-56-7234 69 79 82 65 88

898-23-1234 80 80 82 86 92

%alculate te averae and standard deviation of te five

scores for eac individual se if-ten co!!and to find

out wo as te iest averae score and report is

witout dases


35/88

3ata s#mmary roadmap

5roc contents * $ariable definitions

5roc print * ra" data

5roc format * ma%e yo#r print loo% nicer

5roc sort * sort the data

5roc means * basic s#mmary statistics

5roc #ni$ariate * detailed s#mmary stat

5roc freV * freV#ency co#nt 5roc chart * histogram

proc plot * scatter plot


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proc format >!

D6ontin#e the data cleaning eercise on page 29B

data prothen ne"grpC>B

else if frac#nins#redI01>K then ne"grpC2B

else if frac#nins#redI012 then ne"grpC=B

else ne"grpC4B

r#nB

3efining ,gro#p- as a

n#meric $ariable "ill

sa$e space


37/88

proc format 2!

proc formatB

$al#e ne"gro#p >CPlo";

2CPmid/lo";

=CPmid/high;

4CPhigh;B r#nB

proc print dataCpro


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proc sort

proc sort dataCpro


39/88

proc means and proc #ni$ariate

proc means dataCpro


40/88

Notes on proc means and proc #ni$ariate

Dif yo# do not #se classorbycommand+ thestatistics are based on the f#ll sample1 f yo# #seclassorby$ar + the statistics are based on the

s#bsample defined by each $al#e of $ar 1Do# can #se classorbyinproc means+ b#t onlyby

inproc #ni$ariateB

D"hene$er yo# #se ,by$ar -+ the data set sho#ld

be sorted by $ar beforehandB


41/88

proc means and proc #ni$ariate

allo" m#ltiple gro#psdata pro


42/88

proc freV

D 'emember "e already generate a $ariable called ne"grp toindicate categories of fraction #nins#red and a $ariable called

popgrp to indicate categories of pop#lation sieB

proc freV dataCpro


43/88

proc chart * histogram for

categorical $ariables

proc chart dataCpro


44/88

proc chart * histogram for

contin#o#s $ariable

proc chart dataCpro


45/88

proc plot * scatter plot

proc plot dataCpro


46/88

scatter plot is less informati$e for

categorical $ariables

proc plot dataCpro


47/88

fancy proc means

proc means dataCpro

mean C a$g#nins#red a$gfrac#nins#redB

r#nB

proc print dataCs#mmary>Br#nB


48/88

)he follo"ing page may be#sef#l in practice+ b#t am not

going to co$er it in class1


49/88

some s#mmary stat1 in proc print

D Ass#me "e ha$e already defined ne"grp andpopgrp in proB

by popgrpB

s#m totalpopB $ar totalpop ins#red #nins#red frac#nins#redB

r#nB


50/88

o" to handle m#ltiple data sets?

Add more observationsto an eisting dataand the ne" obser$ations follo" the samedata str#ct#re as the old oneappend

Add more variablesto an eisting data andthe ne" $ariables refer to the sames#b


51/88

merge and append

pro high

s#mmary>: ne"grp popgrp a$g#nins#red a$gfrac#nins#red

> high @K00000 010@=

merged:

year state totalpop .fracuninsured newgrp popgrp avguninsure avgfracuninsured

2009 (A O42094@ 010K4 > high @K00000 010@=

appended:year state totalpop .fracuninsured newgrp popgrp avguninsure avgfracuninsured

2009 (A O42094@ 010K4 > high 1 1

1 1 1 > high @K00000 010@=


52/88

merge t"o datasets

proc sort dataCproB

by ne"grp popgrpB

r#nB

data mergedB

merge proB

r#nB What if this line is

,if oneC> .' t"oC>B-?


53/88

[eep trac% of matched and

#nmatched records

data allrecordsB

merge proB

r#nB

proc freV dataCallrecordsBtables myoneDmyt"oB

r#nB

SAS "ill drop $ariables,one- and ,t"o-

a#tomatically at the end of

the 3A)A step1 f yo# "ant

to %eep them+ yo# can copythem into ne" $ariables

,myone- and ,myt"o-


54/88

be caref#l abo#t merge

al"ays p#t the merged data into a ne"data set

m#st sort by the %ey $ariables before merge

o% for one/to/one+ m#lti/to/one+ one/to/m#lti+ b#t

no good for m#lti/to/m#lti be caref#l of "hat records yo# "ant to %eep+ and

"hat records yo# "ant to delete

"hat if $ariable appears in both datasets+ b#t is

not in the ,by- statement?* after the merge ta%es the $al#e defined in the last

dataset of the ,merge- statement


55/88

append

data appendedB

set pro


56/88

6lass eample of merge and

append: reshape and s#mmarie

So#rce format of 5ro= 010K=O

>2K@O22 010@ 1 >2O@409 010@K 11


57/88

(ain data iss#es

From long to "ide+ $ariable names are

different ecept for the %ey $ariable state!

We can generate a$erage frac#nins#red perstate either before or after the reshape+ b#t

the merge code "ill be different depending

on "hen "e comp#te the a$erage

frac#nins#red


58/88

Step > to reshape:

generate a s#b/sample for each year+

so that "e ha$e:

s#bsample2009

s#bsample200

1

s#bsample200=


59/88

foc#s on 2009

data s#bsample2009B

set pro


60/88

Same for 200

data s#bsample200B

set pro


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Step 2 to reshape: merge each year;s

s#bsample by state

proc sort dataCs#bsample2009B by stateB r#nB

proc sort dataCs#bsample200=B by stateB r#nB

data reshapedB

merge s#bsample2009 s#bsample200 s#bsample200@

s#bsample200O s#bsample200K s#bsample2004

s#bsample200=Bby stateB

r#nB

proc print dataCreshapedB r#nB

& f i d


62/88

&enerate a$erage frac#nins#red

by state

proc means dataCpro


63/88

(erge the data file ,a$gperstate-

bac% to reshapedproc sort dataCreshapedB

by stateB

r#nB

proc sort dataCa$gperstateB

by stateB

r#nBdata reshapedJ"itha$gB

merge reshaped inCone! a$gperstate inCt"o!B

by stateB

myoneConeB

myt"oCt"oB

if oneC> Y t"oC>Br#nB

proc print dataCreshapedJ"itha$gB r#nB

6h % b i i


64/88

6hec% obser$ations in

reshapedJ"itha$g

proc freV dataCreshapedJ"itha$gB

tables myoneDmyt"oB

r#nB


65/88

mean comparison: t"o gro#ps

Eample: does the a$erage frac#nins#red differ bet"een 200 and 2009?

0: mean of frac#nins#red200 C mean of frac#nins#red20091

>: mean of frac#nins#red200 not eV#al to mean of frac#nins#red20091

)his is a t"o/tail mean/comparison test bet"een the 200 sample and the2009 sample1

)he test res#lt "ill be different if

>! "e treat 200 and 2009 as t"o independent samplesB or2! We treat 200 and 2009 as matched pairs matched by state!1


66/88

mean comparison: t"o gro#ps

SAS performs mean comparison in a regression frame"or%1

0: mean of frac#nins#red200 C mean of frac#nins#red20091

>: mean of frac#nins#red200 not eV#al to mean of frac#nins#red20091

Step >: foc#s on the s#bsample that has 200 and 2009 data only1

Step 2: create a binary $ariable d#mmy2009C> if yearC2009+ 0 if yearC2001Step =: depend on "hether 200 and 2009 are independent samples or matched pairs1

f independent samples+ regress frac#nins#red as:

frac#nins#red C a \ bD d#mmy2009 \ error

f matched pairs+ regress frac#nins#red as:

frac#nins#red C a \ b D d#mmy2009

\ c>D d#mmyJAT \ c2D d#mmyJA[

\ \cK>Dd#mmyJW \ error

i t


67/88

mean comparison: t"o gro#ps as

t"o independent samplesD Foc#s on 200 and 2009 data onlyB

3ata s#bsample009B

Set pro


68/88

mean comparison: t"o gro#ps as

matched pairs matched by state!

D Foc#s on 200 and 2009 data onlyB

data s#bsample009B

set pro


69/88

mean comparison: more than t"o gro#ps

Eample: does the a$erage frac#nins#red differ bet"een any t"o yearsin o#r data? here year C 200=+ 2004+ 2009!

)he test res#lt "ill be different if

>! "e treat year t and year t; as t"o independent samplesB or2! We treat year t and year t; as matched pairs matched by state!1

i


70/88

mean comparison: e$ery year as an

independent sampleD )reat e$ery year as an independent sampleB

D No" "e need to #se the "hole data of pro


71/88

mean comparison: e$ery year as

matched pairs matched by state!D )reat e$ery year as matched by stateB

D First define d#mmies for each yearB

data proB else d#mmy2004C0B

if yearC200K then d#mmy200KC>B else d#mmy200KC0B

if yearC2009 then d#mmy2009C>B else d#mmy2009C0B

r#nB

proc glm dataCpro


72/88

notes on mean comparison

>1 )he logic of mean comparison is the same as in Ecel

21 8e caref#l abo#t one/tail and t"o/tail tests1

)he standard SAS o#tp#t of coefficient t/stat and p/$al#e are based on a t"o/tail test of 0: coeffC0+b#t co#ld be #sed for a one/tail test if "e compare >/alpha $s1 p/$al#e2 instead of p/$al#e1

=1 6omparison across more than t"o gro#ps as independent samples!

0: all gro#ps ha$e the same mean

F/test of "hole regression.'

0: gro#p and gro#p y has the same mean

"aller or lsd statistics

41 6omparison across more than t"o gro#ps as matched pairs! reV#ires specific test on regressioncoefficients1

0: 200= C 2004test the coefficient of d#mmy2004C0 beca#se 200= is set as the benchmar%

0: 2004C200Ktest the coefficient of d#mmy2004 C coefficient of d#mmy200K1

E li it h th i t t


73/88

Eplicit hypothesis tests

in proc reg and proc glmD )reating each year as independent samplesB

5roc reg dataCpro 0 0 0 /> 0B6ontrast Ptest 200 $s1 2009;

year 0 0 0 0 > />B

'#nB)est frac#nins#red200=Cfrac#nins#red200B

)est frac#nins#red200Cfrac#nins#red2009B

)est frac#nins#red200=Cfrac#nins#red200B

)est frac#nins#red200Cfrac#nins#red2009B

n class e ercise


74/88

n class eercise

for mean comparison(ain V#estion:

compare frac#nins#red in "est+ midatlantic and e$ery"here else+ "here

"est C 6A+ WA+ .'

midatlantic C 3E+ 36+ (3+ HA

step 0: define "est+ midatlantic and e$ery"hereelse

eercise >: compare "est and midatlantic

>a!1 as t"o independent samples

>b!1 consider the match by year

eercise 2: compare "est+ midatlantic+ and e$ery"here else2a!1 as three independent samplesB

2b!1 consider the match by yearB


75/88

regression in SAS

U#estion: ho" do frac#nins#red $ary by total pop#lation of a state?

D model: frac#nins#redCa\bDtotalpop\errorB

proc reg dataCpro


76/88

A comprehensi$e eample

A re$ie" of

>1 readin data

21 s#mmary statistics=1 mean comparison

41 regression

reg/cityreg/simple1sas in N:share


77/88

A 6ase St#dy of Tos Angeles 'esta#rants

Nov. 16-18, 1997 CBS 2 News Behind the Kitchen Door

Jn!r" 16, 1998, #$ co!nt" ins%ectors strt iss!in& h"&iene

&rde crds

$ &rde i' score o' 9( to 1((

B &rde i' score o' 8( to 89

C &rde i' score o' 7( to 79

score )e*ow 7( ct!* score shown

+rde crds re %roinent*" dis%*"ed

in rest!rnt windows

Score not shown on &rde crds


78/88


79/88

)a%e the idea to data

betternformation

betterV#ality

reg#lationby co#nty

by city

hygienescores

'esearch U#estion:

3oes better information lead to better hygiene V#ality?

3 t li ti


80/88

3ata complicationsbl#e font indicates o#r final choices!

Znit of analysis:

indi$id#al resta#rant? city? ipcode? cens#s tract?

Znit of time:

each inspection?per month? per V#arter? per year?

3efine information:

co#nty reg#lation? city reg#lation? the date of passing the reg#lation?

days since passing the reg#lation? L of days #nder reg#lation?

3efine V#ality:

a$erage hygiene score? the n#mber of A resta#rants? L of A

resta#rants?


81/88

o" to test the idea?

'egression:

V#ality C ]\^Dinformation\error

\something else?

Something else co#ld be:

year trend+ seasonality+ city specific effects+ 1


82/88

real test

reg/cityreg/simple1sas in N:share


83/88

U#estions

o" many obser$ations in the sample?

* log of the first data step+ or o#tp#t from proc contents

o" many $ariables in the sample? o" many

are n#merical+ ho" many are characters?* .#tp#t from proc contents

o" many percentage of resta#rants ha$e A

V#ality in a typical city/month?* .#tp#t from proc means+ on perJA


84/88

U#estions

What is the difference bet"een cityreg and ctyreg? We %no" co#ntyreg#lation came earlier than city reg#lation+ is that reflected in o#rdata?* es+ cityregICctyreg in e$ery obser$ation* We can chec% this in proc means for cityreg and ctyreg+ or add a proc

print to eyeball each obs

What is the difference bet"een cityreg and citymper? What is themean of cityreg? What is the mean of citymper? Are they consistent"ith their definitions?* )he #nit of cityreg is _ of days+ so it sho#ld be a non/negati$e integer

* )he #nit of citymper is L of days+ so it sho#ld be a real n#mber bet"een0 and >* )o chec% this+ "e can add a proc means for cityreg and citymper


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U#estions

Economic theories s#ggest V#ality be higher after

the reg#lation if reg#lation gi$es cons#mers better

information1 s that tr#e?

*)he s#mmary statistics reported in proc meansclass citymJg or ctymJg! sho" the a$erage

percentage of A resta#rants in different

reg#lation en$ironments1

*'igoro#s mean comparison tests are done in

proc glm "ith "aller or lsd options1


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U#estions

S#mmary statistics often reflect many economic factors+ notonly the one in o#r mind1 )hat is "hy "e need regressions1

3oes more reg#lation lead to higher V#ality?

* is the coefficient of city reg#lation positi$e andsignificantly different from ero? proc reg!

* is the coefficient of co#nty reg#lation positi$e andsignificantly different from ero? proc reg!

* 3o "e omit other sensible eplanations for V#alitychanges? What are they? proc glm+ year+ V#arter+ city!


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6o#nt d#plicates not reV#ired!

http:s#pport1sas1comctsamplesinde1


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co#rse e$al#ation

Zni$ersity "ide:

* """16o#rseE$alZ(1#md1ed#

))class in partic#lar: pass"ord plstt!* """1s#r$eyshare1coms#r$eyta%e?sidC>0@
http://www.courseevalum.umd.edu/http://www.surveyshare.com/survey/take/?sid=81087http://www.surveyshare.com/survey/take/?sid=81087http://www.courseevalum.umd.edu/

Documents

Notes for SAS Programming Fall2009