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Chapter 8. Data Transformations
Data Transformations
Inanideal situation, yourraw dataare perfectly suitablefor the type ofanalysisyouwant to perform,
and any relationshipsbetweenvariablesare either conveniently linear or neatlyorthogonal.
Unfortunately, thisisrarely the case. Preliminary analysismayreveal inconvenient coding schemesor
coding errors, or datatransformations may be required in order to expose the true relationshipbetween
variables.
Youcanperform datatransformationsranging fromsimpletasks, such ascollapsing categoriesfor
analysis, to more advancedtasks, such ascreating new variablesbased oncomplex equations and
conditionalstatements.
Computing Variables
Use theCompute dialog box to compute valuesfor avariable basedon numerictransformationsofother
variables.
v You cancomputevaluesfornumeric or string (alphanumeric) variables.
v You cancreatenew variablesor replace the valuesof existing variables. For newvariables, youcan
also specify the variable typeandlabel.
v You cancomputevaluesselectively forsubsetsof databased onlogicalconditions.
v You canuse alarge varietyof built-infunctions, including arithmetic functions,statisticalfunctions,
distributionfunctions, and string functions.
ToCompute Variables
1. Fromthe menus choose:
Transform> ComputeVariable...
2. Type the name of asingletarget variable. Itcanbeanexisting variable or anewvariabletobe added
to the active dataset.
3. Tobuildanexpression, either pastecomponentsintotheExpressionfieldortype directly inthe
Expressionfield.
v You canpaste functionsor commonlyused system variablesbyselectingagroup fromtheFunction
grouplistanddouble-clicking the functionor variable inthe Functionsand SpecialVariableslist (or
select the functionor variable and click the arrow adjacent to the Function group list). Fillinany
parametersindicatedby question marks(only appliesto functions). The functiongrouplabeled All
providesa listing of all available functionsandsystemvariables.Abrief descriptionof the currently
selected functionorvariable isdisplayed inareserved areainthe dialog box.
v String constantsmust be enclosed inquotationmarks orapostrophes.
v If valuescontaindecimals, aperiod(.) must be used asthedecimalindicator.
v For newstring variables, you must also select Type& Label to specify the datatype.
Compute Variable: If Cases
TheIf Casesdialog box allowsyouto apply datatransformationstoselected subsetsof cases,using
conditionalexpressions. Aconditional expressionreturnsavalue of true, false, or missingfor eachcase.
v If theresult of aconditionalexpression is true,thecaseisincluded inthe selectedsubset.
v If theresult of aconditionalexpression is false or missing,thecaseisnot included in theselected
subset.
©CopyrightIBMCorporation1989,2014
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v Mostconditional expressionsuse one or moreof thesixrelationaloperators(<, >, <=, >=, =,and~=)
on the calculator pad.
v Conditionalexpressionscaninclude variable names, constants, arithmeticoperators, numeric(and
other) functions, logicalvariables, and relationaloperators.
Compute Variable: Type and Label
By default,new computedvariablesare numeric. To compute anewstring variable,youmust specify the
datatype and width.
Label. Optional, descriptive variable label upto255byteslong. Youcanenter alabelor use thefirst110
charactersof the compute expressionasthe label.
Type.Computedvariablescan be numericor string (alphanumeric). String variablescannot be used in
calculations.
Functions
Many typesof functionsare supported, including:
v Arithmeticfunctions
v Statisticalfunctions
v String functions
v Dateandtime functions
v Distribution functions
v Randomvariable functions
v Missingvalue functions
v Scoring functions
For more information and adetailed description of eachfunction, typefunctionsonthe Indextab of the
Help system.
Missing Values in Functions
Functionsandsimple arithmetic expressionstreat missing valuesindifferentways. In theexpression:
(var1+var2+var3)/3
the resultismissing ifacasehasamissingvalue for any of the three variables.
Intheexpression:
MEAN(var1, var2, var3)
the resultismissing onlyif the case hasmissing valuesfor all three variables.
For statistical functions,you canspecify the minimumnumberofargumentsthatmusthave nonmissing
values. Todo so, type aperiod and the minimumnumber after the functionname, asin:
MEAN.2(var1, var2, var3)
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IBMSPSSStatistics23CoreSystemUser'sGuide
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Random Number Generators
TheRandomNumber Generatorsdialog box allowsyou to selecttherandom number generator and set
the startingsequence value so youcanreproduce asequence of randomnumbers.
ActiveGenerator. Two differentrandom number generatorsare available:
v Version 12Compatible.The randomnumber generatorused inversion12and previousreleases.If you
needtoreproduce randomized resultsgeneratedinpreviousreleasesbased onaspecifiedseed value,
use thisrandomnumber generator.
v MersenneTwister. Anewer randomnumber generatorthat ismore reliablefor simulationpurposes. If
reproducingrandomized resultsfromversion12or earlier isnotanissue, use thisrandomnumber
generator.
ActiveGeneratorInitialization. Therandom number seed changeseach time arandom numberis
generated foruse intransformations(suchasrandomdistributionfunctions),random sampling,orcase
weighting.To replicate asequence of random numbers,set the initializationstarting pointvaluepriorto
eachanalysisthatusesthe random numbers.The value must beapositive integer.
Some procedures, suchas Linear Models, haveinternal randomnumber generators.
Toselectthe randomnumbergeneratorand/or set the initializationvalue:
1. Fromthe menus choose:
Transform> Random NumberGenerators
Count Occurrences of Values within Cases
Thisdialog boxcreatesavariable thatcountsthe occurrences of the samevalue(s) inalist of variablesfor
eachcase. For example, asurvey mightcontainalist of magazineswithyes/nocheck boxesto indicate
which magazineseachrespondent reads.You couldcount the number of yesresponsesfor each
respondent to create anew variable that containsthe total numberof magazinesread.
ToCount Occurrencesof ValueswithinCases
1. Fromthe menus choose:
Transform> Count Values within Cases...
2. Enter atarget variable name.
3. Select twoormore variablesof the same type (numeric or string).
4. Click DefineValuesandspecifywhichvalue or values should be counted.
Optionally, you candefine asubset of casesfor which to countoccurrencesof values.
Count Values within Cases: Values to Count
Thevalueofthetarget variable (onthe maindialog box) isincremented by 1eachtime one of the
selectedvariablesmatchesaspecificationinthe ValuestoCount list here. Ifacasematchesseveral
specificationsfor any variable, the target variable isincremented severaltimes for thatvariable.
Value specificationscaninclude individual values,missing or system-missing values, andranges.Ranges
include their endpointsand any user-missing valuesthat fallwithinthe range.
Count Occurrences: If Cases
TheIf Casesdialog box allowsyouto count occurrencesof valuesfor aselected subsetofcases,using
conditionalexpressions. Aconditional expressionreturnsavalue of true, false, or missingfor eachcase.
Chapter8.DataTransformations
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Shift Values
Shift Valuescreatesnewvariablesthatcontainthevaluesof existingvariablesfrompreceding or
subsequent cases.
Name. Name forthenew variable.Thismustbea namethat doesnot already exist in the active dataset.
Getvaluefromearlier case(lag).Get the valuefromapreviouscase in theactive dataset.For example,
withthe defaultnumberofcasesvalue of 1, each case for the new variable hasthe value of the original
variable fromthe case that immediately precedesit.
Getvaluefromfollowingcase(lead).Get the valuefromasubsequent case inthe active dataset. For
example,withthe default number of casesvalue of 1, eachcase for the newvariable hasthevalueofthe
originalvariable fromthe next case.
Numberofcases to shift. Get the value fromthe nth preceding or subsequent case,wheren isthe value
specified. The value must be anon-negative integer.
v If split file processing ison, the scope of the shift is limitedtoeachsplitgroup.Ashift value cannot be
obtainedfromacaseinapreceding or subsequent split group.
v Filter statusisignored.
v The value of the resultvariableisset tosystem-missing for thefirstorlast n casesinthe dataset or
splitgroup, where n isthe valuespecifiedfor Numberofcases to shift. For example, using the Lag
methodwithavalue of 1would settheresult variable to system-missing forthe first case inthe
dataset (or first case ineachsplitgroup).
v User-missingvaluesarepreserved.
v Dictionary informationfromthe originalvariable,including defined value labelsand user-missing
value assignments, is applied to the newvariable. (Note: Customvariable attributesare not included.)
v Avariable labelisautomatically generated forthe new variable that describesthe shift operationthat
createdthevariable.
ToCreate aNewVariable withShifted Values
1. Fromthe menus, choose:
Transform> ShiftValues
2. Select the variable to use asthe source of valuesfor the newvariable.
3. Enter aname for thenewvariable.
4. Select the shift method (lag orlead) andthe number of casesto shift.
5. Click Change.
6. Repeat foreachnewvariable youwanttocreate.
Recoding Values
Youcanmodify datavaluesby recoding them. Thisisparticularlyusefulfor collapsing orcombining
categories.You can recode the valueswithinexisting variables, or youcancreate newvariablesbased on
the recodedvaluesof existingvariables.
Recode into Same Variables
The Recode into Same Variablesdialog box allows you to reassignthevaluesof existing variablesor
collapse rangesofexisting valuesinto new values. For example, you couldcollapsesalariesintosalary
range categories.
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IBMSPSSStatistics23CoreSystemUser'sGuide
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Youcanrecodenumeric and stringvariables.If you select multiple variables, theymust allbe thesame
type.You cannot recodenumeric and string variablestogether.
ToRecode Valuesof aVariable
1. Fromthe menus choose:
Transform> Recodeinto SameVariables...
2. Select the variablesyou want to recode. If youselect multiple variables, they must bethe same type
(numeric or string).
3. Click Old andNewValues andspecify howto recode values.
Optionally, you candefine asubset of casestorecode. The If Casesdialog boxfordoing thisisthe same
as theone described for CountOccurrences.
Recode into Same Variables: Old and New Values
Youcandefine valuesto recode inthisdialog box. Allvalue specificationsmust bethe same datatype
(numeric or string) asthe variablesselectedinthe main dialog box.
Old Value.The value(s)tobe recoded.You canrecode single values, ranges of values, andmissing
values. System-missing valuesandrangescannot be selectedfor string variablesbecause neither concept
appliesto string variables.Rangesinclude their endpointsandanyuser-missing valuesthatfall within
the range.
v Value. Individualold valuetobe recodedinto anew value. The valuemust be the samedatatype
(numericor string) asthe variable(s) being recoded.
v System-missing. Values assignedby theprogramwhen valuesinyour dataare undefinedaccording to
the format type you have specified, whenanumeric field isblank, orwhenavalue resulting froma
transformationcommandisundefined. Numeric system-missing valuesaredisplayed asperiods. String
variablescannot have system-missingvalues,since any character islegal in astringvariable.
v System- oruser-missing.Observationswithvaluesthateither have beendefinedasuser-missing values
or are unknownand have beenassigned the system-missing value, which isindicated witha period (.).
v Range.Inclusive range of values. Not availablefor stringvariables.Any user-missing valueswithinthe
range are included.
v Allother values.Any remaining valuesnot included in oneof thespecificationsonthe Old-New list.
ThisappearsasELSE onthe Old-New list.
NewValue. The single valueinto whicheachold value orrangeofvaluesisrecoded. Youcanentera
value or assignthe system-missing value.
v Value. Value into whichone or more old valueswillberecoded.The value must be the same datatype
(numericor string) asthe oldvalue.
v System-missing. Recodesspecifiedold valuesinto the system-missing value. The system-missing value
isnot usedin calculations, and caseswiththe system-missing value are excludedfrommany
procedures. Not available forstring variables.
Old–>New. The listofspecificationsthat willbe used to recodethe variable(s). Youcanadd, change, and
remove specificationsfromthe list. Thelist isautomatically sorted,based onthe old value specification,
using the following order: single values, missing values, ranges, and all other values. If youchange a
recode specification onthe list,the procedure automatically re-sortsthe list, if necessary, to maintain this
order.
Chapter8.DataTransformations
87
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Recode into Different Variables
The Recode into Different Variablesdialog box allowsyou to reassignthe valuesof existingvariablesor
collapse rangesofexisting valuesinto new valuesfor anewvariable. For example, you couldcollapse
salariesinto anew variable containing salary-range categories.
v You canrecode numericandstring variables.
v You canrecode numericvariablesintostring variablesand vice versa.
v If you select multiple variables, theymust allbe thesame type. Youcannotrecode numericandstring
variablestogether.
ToRecode Valuesof aVariable into aNew Variable
1. Fromthe menuschoose:
Transform> Recodeinto Different Variables...
2. Select the variablesyou want to recode. If youselectmultiple variables, they must bethe same type
(numeric or string).
3. Enter anoutput(new) variable name foreachnew variable and click Change.
4. Click Old andNewValues andspecify howto recode values.
Optionally, you candefine asubset of casestorecode.The If Casesdialog boxfordoing thisisthe same
as theone described for CountOccurrences.
Recode into Different Variables: Old and New Values
Youcandefine valuesto recodeinthisdialog box.
Old Value.The value(s)tobe recoded.You canrecode single values, rangesof values, and missing
values. System-missing valuesandrangescannot be selected for string variablesbecause neither concept
appliesto stringvariables.Oldvaluesmust be the same datatype(numericorstring) asthe original
variable. Rangesinclude their endpointsandany user-missing valuesthat fallwithintherange.
v Value. Individualold valueto be recodedinto anew value. The valuemust be the samedatatype
(numericor string) asthe variable(s) being recoded.
v System-missing. Values assignedby theprogramwhen valuesinyour dataare undefinedaccording to
the format type you have specified, whenanumeric field isblank, or whenavalue resulting froma
transformationcommandisundefined. Numeric system-missing valuesare displayed asperiods. String
variablescannot have system-missing values,sinceany character islegal in astringvariable.
v System- oruser-missing.Observationswithvaluesthateither have beendefinedasuser-missing values
or are unknownand have beenassigned the system-missing value, which isindicated with aperiod (.).
v Range.Inclusive range of values. Not availablefor stringvariables.Any user-missing valueswithinthe
range are included.
v Allother values.Any remaining valuesnot included inone of the specificationsonthe Old-New list.
ThisappearsasELSE onthe Old-New list.
NewValue. The single valueinto whicheachold value or rangeofvaluesisrecoded. New valuescanbe
numericor string.
v Value. Value into whichone or more old valueswillberecoded.The value must bethe same datatype
(numericor string) asthe oldvalue.
v System-missing. Recodesspecifiedold valuesinto the system-missing value. The system-missing value
isnot used in calculations, and caseswiththe system-missing value are excludedfrommany
procedures. Not available forstring variables.
v Copyoldvalues. Retains theoldvalue.If some valuesdon'trequire recoding,use thisto include the old
values. Anyoldvaluesthat are notspecifiedare not includedinthe new variable, and caseswiththose
valueswillbe assigned the system-missing value for the newvariable.
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IBMSPSSStatistics23CoreSystemUser'sGuide
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Output variables arestrings. Definesthe new, recodedvariable asastring (alphanumeric) variable. The old
variable canbe numericor string.
Convert numeric strings to numbers.Convertsstring values containingnumbersto numericvalues.Strings
containing anything otherthannumbersand anoptionalsign(+or -)are assigned the system-missing
value.
Old–>New.The listofspecificationsthat willbe used to recodethe variable(s). Youcanadd, change, and
remove specificationsfromthe list. Thelist isautomatically sorted, based onthe old value specification,
using the following order: single values, missing values, ranges, and all other values. If youchange a
recode specification onthe list,the procedure automatically re-sortsthe list, if necessary, to maintain this
order.
Automatic Recode
TheAutomaticRecode dialog boxallowsyou to convert string andnumeric valuesinto consecutive
integers. Whencategory codesarenot sequential, the resulting empty cellsreduceperformance and
increase memory requirementsfor many procedures. Additionally, some procedurescannot use string
variables, and some require consecutive integer valuesfor factor levels.
v The new variable(s) createdbyAutomatic Recode retain any definedvariable andvalue labelsfromthe
old variable. For any valueswithoutadefined value label, the originalvalue isusedasthe labelfor
the recoded value.Atabledisplaysthe old and newvaluesand value labels.
v String valuesare recoded inalphabetical order,withuppercase letterspreceding their lowercase
counterparts.
v Missingvaluesarerecoded into missing valueshigherthananynonmissingvalues,withtheir order
preserved. For example, if the original variable has10nonmissing values, the lowest missing value
would be recoded to 11, andthe value 11would be amissing value forthenew variable.
Usethesamerecoding schemefor all variables. This optionallowsyoutoapply asingle autorecoding
scheme to allthe selectedvariables, yielding aconsistent coding scheme for all the newvariables.
If youselect thisoption,thefollowing rulesand limitationsapply:
v All variablesmust be of the same type (numeric or string).
v All observed values for all selectedvariablesare used to create asorted order of valuesto recode into
sequentialintegers.
v User-missingvaluesforthe new variablesare basedonthe first variable inthe list withdefined
user-missing values.Allothervaluesfrom other originalvariables,except for system-missing,are
treated as valid.
Treat blankstring valuesasuser-missing. For string variables, blank or nullvalues are not treatedas
system-missing. Thisoptionwillautorecode blank strings into auser-missingvalue higher thanthe highest
nonmissing value.
Templates
Youcansave theautorecoding scheme inatemplate file andthenapply it to othervariablesand other
datafiles.
For example, you may have alarge number of alphanumericproduct codesthatyouautorecode into
integersevery month, butsome monthsnewproductcodesare addedthat change the original
autorecoding scheme. If yousave the originalscheme inatemplateandthenapplyit to the new data
thatcontainthe new set of codes, any new codesencountered inthe dataare autorecoded into values
higher than thelastvalue inthe template, preserving the originalautorecode schemeof theoriginal
product codes.
Chapter8.DataTransformations
89
Savetemplateas. Savesthe autorecode schemefor the selectedvariablesinanexternal template file.
v The template containsinformationthat mapsthe originalnonmissing valuesto the recoded values.
v Only informationfor nonmissing valuesissavedinthetemplate. User-missing value informationisnot
retained.
v If you haveselected multiplevariablesforrecodingbut you havenot selected to use the same
autorecoding scheme forallvariablesor you are not applying anexisting template as part of the
autorecoding, the template willbe based onthe first variable inthe list.
v If you haveselected multiplevariablesforrecodingandyou have also selected Usethe samerecoding
schemefor all variables and/oryouhave selectedApplytemplate,thenthe template willcontainthe
combined autorecodingscheme for allvariables.
Apply templatefrom. Appliesapreviously savedautorecode template tovariablesselectedfor recoding,
appending anyadditionalvaluesfound inthe variablestotheend of the scheme andpreserving the
relationship betweenthe originaland autorecoded valuesstoredin thesavedscheme.
v All variablesselected for recoding mustbe the sametype (numeric or string), and that type must
matchthe typedefined inthe template.
v Templatesdonot containanyinformationonuser-missing values. User-missing valuesfor the target
variablesarebased onthe first variable inthe originalvariablelist withdefined user-missingvalues.
All other valuesfrom other originalvariables, except for system-missing, are treatedasvalid.
v Value mappingsfromthe templateare appliedfirst.Allremaining valuesare recoded into values
higher thanthe last value in the template, withuser-missing values(based onthe first variable inthe
listwithdefineduser-missing values) recoded intovalueshigher than thelastvalid value.
v If you haveselected multiplevariablesforautorecoding, the template isappliedfirst, followedby a
common, combinedautorecoding foralladditionalvalues found in theselected variables, resulting in a
single, commonautorecodingscheme for all selectedvariables.
ToRecode String or NumericValuesintoConsecutiveIntegers
1. Fromthe menuschoose:
Transform> Automatic Recode...
2. Select one or more variablestorecode.
3. Foreachselected variable, enter aname for the new variable andclick NewName.
Rank Cases
The Rank Casesdialogboxallowsyoutocreatenewvariablescontaining ranks, normaland Savage
scores,andpercentile valuesfor numericvariables.
New variable namesanddescriptive variable labelsare automatically generated, based onthe original
variable name and the selected measure(s). Asummary table liststhe original variables, thenew
variables, and the variable labels. (Note:The automatically generatednew variable namesare limitedtoa
maximumlengthof 8bytes.)
Optionally, you can:
v Rankcasesinascending or descending order.
v Organize rankingsinto subgroupsby selecting oneormore grouping variablesforthe By list. Ranks
are computed withineachgroup. Groupsare defined by the combinationofvaluesof the grouping
variables. For example, if youselect gender and minorityasgrouping variables, ranksare computed for
eachcombination of genderandminority.
ToRank Cases
1. Fromthe menuschoose:
Transform> Rank Cases...
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2. Select one or more variablestorank. Youcanrank only numeric variables.
Optionally, you canrank casesin ascendingordescending order and organize ranksinto subgroups.
Rank Cases: Types
Youcanselect multipleranking methods.Aseparate ranking variable iscreated for eachmethod.
Ranking methodsinclude simple ranks,Savage scores, fractionalranks, and percentiles. Youcanalso
create rankingsbased onproportionestimatesand normal scores.
Rank. Simple rank. Thevalue ofthe new variable equalsitsrank.
Savage score.The new variable containsSavage scoresbased onanexponentialdistribution.
Fractionalrank.The value of the new variableequalsrankdivided by the sumof the weightsof the
nonmissing cases.
Fractionalrankaspercent.Eachrank isdividedbythe number of caseswithvalid valuesandmultiplied
by 100.
Sumofcase weights. Thevalue of the new variable equalsthe sumof case weights.The new variable isa
constant forallcasesinthe samegroup.
Ntiles. Ranksare based onpercentile groups, witheachgroupcontainingapproximately the same number
of cases. Forexample, 4Ntiles wouldassignarank of1to casesbelow the25thpercentile, 2to cases
betweenthe 25th and 50thpercentile, 3to casesbetweenthe 50thand75thpercentile, and 4to cases
abovethe 75thpercentile.
Proportionestimates. Estimatesof the cumulative proportionof the distributioncorresponding to a
particular rank.
Normal scores. The zscorescorresponding tothe estimated cumulative proportion.
Proportion EstimationFormula. Forproportionestimatesandnormalscores, you can selectthe
proportionestimationformula:Blom, Tukey, Rankit, or Vander Waerden.
v Blom.Createsnewranking variable basedonproportionestimatesthat usesthe formula(r-3/8) /
(w+1/4),wherew isthe sum of the case weightsandr isthe rank.
v Tukey. Usestheformula(r-1/3) / (w+1/3), where r is therank and wisthe sumof the case weights.
v Rankit. Usesthe formula (r-1/2) /w, where wisthe number of observationsand risthe rank, ranging
from1to w.
v Van derWaerden. VanderWaerden's transformation,defined by the formular/(w+1),wherew isthe
sumof the case weightsand r is therank, ranging from 1to w.
Rank Cases: Ties
Thisdialog boxcontrolsthe method for assigning rankingstocaseswith thesamevalue on the original
variable.
Thefollowing table shows howthe different methods assignranksto tiedvalues:
Table7.Rankingmethodsandresults
Value
Mean
Low
High
Sequential
10
1
1
1
1
15
3
2
4
2
15
3
2
4
2
Chapter8.DataTransformations
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Table7.Rankingmethodsandresults (continued)
Value
Mean
Low
High
Sequential
15
3
2
4
2
16
5
5
5
3
20
6
6
6
4
Date and Time Wizard
The Date and TimeWizard simplifiesa numberof commontasksassociated withdate andtime variables.
ToUse the Date andTime Wizard
1. Fromthe menuschoose:
Transform> DateandTimeWizard...
2. Select the task you want to accomplishand followthe stepstodefine the task.
v Learn how datesandtimesarerepresented.Thischoice leadsto ascreenthat providesabrief
overview of date/timevariablesinIBMSPSSStatistics.Byclicking onthe Help button, it also provides
alink to moredetailed information.
v Createadate/timevariablefromastring containing adateor time. Use thisoptionto create a
date/time variable fromastring variable.For example,you have astring variable representing datesin
the formmm/dd/yyyy andwanttocreatea date/time variable fromthis.
v Createadate/timevariablefromvariables holding partsof datesortimes. Thischoiceallowsyouto
construct adate/timevariablefromaset of existing variables. For example, you havea variable that
representsthe month(asaninteger), asecondthat representsthe day ofthemonth, and athirdthat
representsthe year.You cancombine these three variablesintoa single date/time variable.
v Calculatewithdates and times. Use thisoptionto addor subtract values fromdate/time variables.
For example, youcancalculate the duration of aprocessby subtracting avariablerepresenting the
start time of the processfromanother variable representing the endtime of the process.
v Extracta part ofadateor time variable. Thisoption allowsyoutoextract partofa date/time
variable, suchasthe dayof themonthfrom adate/time variable,whichhastheform mm/dd/yyyy.
v Assignperiodicity toadataset. Thischoicetakesyoutothe Define Dates dialog box,used to create
date/time variablesthat consistof asetof sequentialdates. Thisfeature istypicallyused to associate
dateswithtime seriesdata.
Note:Tasksare disabledwhenthedataset lacksthe typesof variablesrequiredtoaccomplishthe task. For
instance, if thedataset containsno string variables, thenthe task to create adate/time variable froma
string doesnot applyandisdisabled.
Dates and Times in IBM SPSS Statistics
Variablesthat represent datesand timesinIBMSPSSStatisticshave avariable typeof numeric, with
display formats that correspondto the specificdate/time formats. These variablesare generally referred
to asdate/time variables. Date/timevariablesthatactually represent datesare distinguishedfromthose
thatrepresent atimedurationthat isindependent of any date,suchas20hours,10minutes, and 15
seconds.The latterare referredto asduration variablesandthe former asdateordate/time variables.
For acomplete list of display formats, see "Date and Time"in the"Universals" sectionof the Command
SyntaxReference.
Dateanddate/timevariables. Date variableshave aformat representing adate,suchasmm/dd/yyyy.
Date/timevariableshave aformat representing adate andtime, suchasdd-mmm-yyyy hh:mm:ss.
Internally, date and date/time variablesare storedasthe number of secondsfromOctober14,1582. Date
and date/time variablesare sometimesreferred to asdate-format variables.
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