THESIS REPORT.pptx

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    DATA PROCESSINGand STATISTICAL

    TREATMENT

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    TREATMENT

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    Forms Of DataProcessing

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    Exampe!

    • “How efective is the teaching o ProessorSnape in Mathematics to ElectricalEngineering students?

      x x

      20 x ! "0 #! x$   %0 x % ! &0

    #!2'0$(00

      0 x 2 ! "0 #! 2)' or%

      (0 x ( ! (0 *muchefective+

     ,otal- (00 2'0

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    DATA PROCESSING

    • .onverting inormation eithermanuall/ or / machine into1uantitative and 1ualitative orms)

    Categorization

    Coding

    Tabulation ofData

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    #ni$ariate Matrix

    • 3nvolves onl/ one variale)

    Scale :

    9- Like extremely 6- Like sligtly

    !- Like "ery muc #- $eiter like nor dislike%- Like moderately &- Dislike sligty

    %&ait'Attri(&tes

    Mi)*s+ L&nc+eon Meat

    Mean Descripti$eInterpretation

    Color %'%# Like "ey muc

    (dor !')# Like "ey muc

    *la"or !'+, Like "ey muc

    Texture !',, Like "ey muc

    eneral .cce/tability !'0, Like "ey muc

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    ,i$ariate Matrix• 3nvolves two variales)

    SC.L1 :

    #- 2ery "ery serious /roblem +- Serious /roblem )- not a /roblem at all

    &3 2ery serious /roblem 0- less serious /roblem

     -O,.RELATEDPRO,LEM

    S

    STAFF N#RSESPRI/ATE 0OSPITALS GO/ERNMENT

    0OSPITALS

    Mean Interpretation Mean Interpretation

    ( 2)( Less serious /roblem 2) less serious /roblem

    2 %)2 Serious /roblem %)% Serious /roblem

    % %)0 Serious /roblem ) 2ery serious /roblem

    %) Serious /roblem %)& 2ery serious /roblem4 )2 2ery serious /roblem 2)0 less serious /roblem

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    M&ti$ariate Matrix• Has three or more variales in the

    tale)

    Scale:

    9- Like extremely 6- Like sligtly!- Like "ery muc #- $eiter like nor dislike

    %&ait'Attri(&tes

    L&nc+eon Meat

    Mil56sh7falMean

    oat6sh7falMean

    Siganid7falMean

    Sardines7falMean

    .olor 8)8 8)& 8)4 8)(

    7dor ")0 ")0 8)% 8)2

    9lavor ") ")2 8)& 8)'

     ,exture ")( ")0 8)" 8)8

    eneral:cceptailit/ ")% ")0 8)8 8)4

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    D#MM1 TA,LES

    • ;sed in planning< summari=ing<

    organi=ing and anal/=ing the data onhow the diferent variales difer witheach other)

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     -o(Performance

    0ospitas

    Pri$ate Go$ernment Tota

    Fre2&enc'

    Percent Fre2&enc'

    Percent Fre2&enc'

    Percent

    O&tstanding

    /er'Satisfactor'

    #nsatisfactor'

    Tota (84 (00 (24 (00 %00 (00

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    STATISTICAL TREATMENT

    • ;sing :rithmetic mean in scaling)

    > ver/ much efective

      % > much efective  2 > efective

      ( > not efective at all

    INCORRECT STATISTICAL

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    INCORRECT STATISTICALTOOL

    • Percentage in scale options * % 2 (+is incorrect or inappropriatestatistical tool to scale options)

      8)4 @ ver/ much efective  4)0 @ much efective

      28)4 @ efective

      20)0 @ not efective at all