MELJUN CORTES RESEARCH Lectures Evaluating Data Statistical Treatment

8/17/2019 MELJUN CORTES RESEARCH Lectures Evaluating Data Statistical Treatment

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Evaluating data forEvaluating data for

statistical treatmentstatistical treatment

ESSENTIALITIESESSENTIALITIES

AND COMPLEXITIESAND COMPLEXITIES

IN THESIS !ITIN"IN THESIS !ITIN"


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Se#uence ofSe#uence of

PresentationPresentation1. How important statistics is in research2. Dangers of (mis)using statistics

3. Why data should be statistically treated4. urposes of !tatistics (in "esearch Writing)#. $he Data %nalysis rocess&. What to measure and how

'. eels of *easurement+. *atri, for !tatistical $reatment of Data-. ommon !tatistical /perations10. !tatistical $ests


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Ho$ im%ortantHo$ im%ortant

statistics is instatistics is inresearc&researc&n theory they are ery important. Without

statistics it is almost impossible to come to an

informed conclusion in any piece of research.$he use of statistics is wide ranging in the fieldof research and without the use of statistics it is

irtually impossible to interpret a true meaningof what the research shows. ot to e,aggeratestatistics is the %5/6 /7 % "6!6%"H.


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Dangers of 'mis(usingDangers of 'mis(using

statisticsstatistics1. !tatistics no matter how carefully collected

can always be flawed e.g. without a sample

of thousands of people (ensuring they arerepresentatie of the whole population) youcannot be certain that the results can be

wholly generali8ed.2. !tatistical information can be easily

manipulated to show ery different results.


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&) data s&ould *e&) data s&ould *e

statisticall) treatedstatisticall) treated+, Data come in di-erent volumeand form,

., Data are su*/ect to di-erentinter%retations,

0, 1ords 'data( di-erentl)

arranged &ave di-erentmeanings2 meaningsdi-erentl) arranged &ave

di-erent im%acts,3+1 att. to Charles Babbage, Father of

Modern Computer


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Pur%oses of StatisticsPur%oses of Statistics

'in !esearc& riting('in !esearc& riting(Essentiall)4 statistics+,&el%s organi5e t&e data, 'Ta*les and

gra%&s are t&e essential non6letter cuesfor inter%retation(.,ma7es inferring guided4 $&ic& )ields tomore meaningful inter%retations, Itma7es use of descri%tive statistics forcollection of data and inferentialstatistics for dra$ing inferences from

t&is set of data,0, rovides latform for researc&


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&at to Measure and&at to Measure and

Ho$Ho$Identify the observable characteristicsof the concepts being investigated record and order observations of those

behavioral characteristics.

1.Quantitative measurements

employ meaningful numericalindicators to ascertain the relativeamount of something.2.Qualitative measurement employ

symbols to indicate the meaning


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Levels of MeasurementLevels of Measurement

1.1. ((NN))ominal ariables are differentiated on the basis ofominal ariables are differentiated on the basis oftype or category.type or category.

2.2. ((OO)rdinal measurement scales not only classify a)rdinal measurement scales not only classify aariable into nominal categories but also ran9 orderariable into nominal categories but also ran9 orderthose categories along some dimension. ($he numberthose categories along some dimension. ($he number

does not e,press the si8e of the difference.)does not e,press the si8e of the difference.)3.3. ((II)nteral measurement scales not only categori8e a)nteral measurement scales not only categori8e a

ariable and ran9 order it along some dimension but alsoariable and ran9 order it along some dimension but alsoestablish e:ual distances between each of the ad;acentestablish e:ual distances between each of the ad;acentpoints along the measurement scale.points along the measurement scale.

4.4. ((RR)atio measurement scales not only categori8e and)atio measurement scales not only categori8e andran9 order a ariable along a scale with e:ual interalsran9 order a ariable along a scale with e:ual interalsbetween ad;acent points but also establish an absolutebetween ad;acent points but also establish an absoluteor true 8ero point where the ariable being measuredor true 8ero point where the ariable being measured

ceases to e,ist.ceases to e,ist.


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Matrix forMatrix for

Statistical Treatment of DataStatistical Treatment of Data


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Treatment of !egularl)Treatment of !egularl)

"at&ered Data"at&ered Data9aria*les9aria*les TreatmentsTreatments

GenderGender f, %f, %

Age, Height,Age, Height,

Weight,Weight,

Mo. IncomeMo. Income

f, %, mean, sdf, %, mean, sd

Educl. AttainmentEducl. Attainment f, %f, %

erceptionserceptions WM, Ave. WM, Grand WMWM, Ave. WM, Grand WM

!hoice!hoice f, %, ran"f, %, ran"

!orrelations!orrelations earson, #pearmanearson, #pearman

$est of #ignicance $est of #ignicance t&test '(&test)t&test '(&test)

!hi&s*uare!hi&s*uare

+an"+an" endall-s $au and !oecient ofendall-s $au and !oecient of

!oncordance!oncordance


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Common StatisticalCommon StatisticalO%erationsO%erations

1.1. Measures of Central Tendency indicate what isMeasures of Central Tendency indicate what istypical of the average su!ect. ".g. Mean#typical of the average su!ect. ".g. Mean#Median# ModeMedian# Mode

$.$. Measures of %ariance indicate the distriution ofMeasures of %ariance indicate the distriution ofthe data around the center. ".g. standardthe data around the center. ".g. standarddeviation and variancedeviation and variance

&.&. Correlation and regression analysis deals withCorrelation and regression analysis deals withthe degree (e'tent) to which two variales ovethe degree (e'tent) to which two variales ovein sync with one another. ".g. pearson productin sync with one another. ".g. pearson productoent of correlation and spearan ran*.oent of correlation and spearan ran*.

+.+. Test of significant difference,Test of significant difference,

relationships.relationships.


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-tatistical Tests -tatistical Tests

Twosided vs. onesided testTwosided vs. onesided test

$hese tests for comparison for instance between methods$hese tests for comparison for instance between methods A A andand B,B, are based on the assumption that there is noare based on the assumption that there is nosignificant difference (the test@ 1. are1. are A A andand BB differentAdifferentA (two-sided (two-sided test)test)

2. is2. is A A higher (or lower) thanhigher (or lower) than B? (one-sided B? (one-sided test).test).


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-tatistical Tests -tatistical Tests

/test (/isher0s Test)/test (/isher0s Test)

TheThe F F test (ortest (or Fisher's test Fisher's test ) is a coparison of the) is a coparison of thespread of two sets of data to test if the sets elong tospread of two sets of data to test if the sets elong to

the sae population# in other words if the precisionsthe sae population# in other words if the precisions

are siilar or dissiilar.are siilar or dissiilar.

The test a*es use of the ratio of the two variancesThe test a*es use of the ratio of the two variances

IfIf F F cal cal 22 F F tabtab one can conclude with 345 confidenceone can conclude with 345 confidence

that there is no significant difference in precision (thethat there is no significant difference in precision (the6null hypothesis6 that6null hypothesis6 that s1,s1, 77 s,s, is accepted). Thus#is accepted). Thus#

there is still a 45 chance that we draw the wrongthere is still a 45 chance that we draw the wrong

conclusion. In certain cases ore confidence ay econclusion. In certain cases ore confidence ay e

needed# then a 335 confidence tale can e used.needed# then a 335 confidence tale can e used.


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!eferences!eferences

!etrieved from : Aug to +; Aug .;+.

+,&tt%???;>,&tml

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MELJUN CORTES RESEARCH Lectures Evaluating Data Statistical Treatment

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