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sÛbrÛa@Ý—ÐÛa

48

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49

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sÛbrÛa@Ý—ÐÛa

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sÛbrÛa@Ý—ÐÛa

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− üaÞýÔnÛaïma‰ïÓaìjÜÛ:

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אאאא )T(،)F(א،)R2(א א א ، א

א .א

− Šbjn‚gãb¤ïÓaìjÛa)Šbjn‚apbjqåíbjnÛa(Homoscedasticity:

אא אאאאאא אא א ،

א.א אbiased،אאא .)2(א

òÔibÛa@Âë‹“Ûa@Õîjm@òîÐî×@òîÜàÈÛa@òÜrßþbi@|šìäë:

Þbrß:

1 Palta, Mari, (2003)," Quantitative Methods in population health: Extensions of ordinary regression", Wiley – IEEE, p 6.

2 Berk, Richard A., (2003)," Regression analysis: a constructive critique", Sage publications Inc., p 144.



ÉibÛa@Ý—ÐÛa

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160 130

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157 125

130 115

150 119

152 121

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א . אאא Income(x)אIndependent(s).

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113

א א א :א. Normal probability plotא א א

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ÉibÛa@Ý—ÐÛa

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( R:א)א א א א ).א

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ÉibÛa@Ý—ÐÛa

116

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117

، Data Viewא −א Standardized(א

Residuals(אres_1،א،pre_1א)y(א

:א

א − א א א אאא .אאאא



ÉibÛa@Ý—ÐÛa

118

، א א אא א א א א א א).א(א

א א א א א א אא .א

paì©aZ@ @

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Simple،Defineא )2

א א א :א




119

א א א :אא ) א א Standardא

Residual [zre_1]א א .Y Axisא

א ) א א)א(אUnstandardized Predicted Value [pre_1]

א א .X Axisא

אokא )3 א א :א



ÉibÛa@Ý—ÐÛa

120

@ @

אא ،אאא א אאא א :אא

ë@wöbnäÛa@óÜÇ@ÕîÜÈnÛa@xˆì¹@òîyý–@óÜÇ@áØ¨aŠa‡®üa@ð‰Ûa@@éÔîÏìmZ@ @

@üëc :Š‡Ô¾a@Ša‡®üa@xˆì¹Z@ @

Y = 8.149 + 0.735 X




121

א א א :،אא ◘ .0β:()8.149(א (א ◘ ).1β:()0.735(א

@ @

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א א ،אאא :א

אאא .).א(א . )אא(א

א א א א א ،.

א :אא

Consumption = 8.149 + 0.735 Income

אאא אא אא א .א

@òÃìzÜßòßbç:



ÉibÛa@Ý—ÐÛa

122

אא אא אא א،אאא

א אא.אא אא ،א א

א .א

2( ñŠ‡ÔÛaòíÐnÛaxˆìàäÜÛ:

אאאא אא)R-Sq(א א،]R-Sq (adj)[א.א

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א77.1٪אא א א )א(،א77.1٪ א ،)א(אאא

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brÛbq:Zòîšbí‹Ûa@Âë‹“Ûa@:

1( òíìäÈ¾aòîÜØÛaxˆìàäÜÛ:




123

◘ ë‹ÐÛaòîöb—ya:א):0H(אא .א

א א):1H(א .א

◘ ë‹ÐÛaÝØ“i‹‚e:א):0H(אא א

.א( (א א):1H(א אא א

).א(

◘ Íí‹ÐmwöbnäÛaÕîÜÈnÛaëbèîÜÇ:

ANOVAא

א א

אSource א

DF א

SS א

MS א

F cal

P. Value

א 0.0000 54.814 2244.036 2244.036 1א

* * 40.939 614.082 15 א

* * * 2858.118 16 א

ÕîÜÈnÛa:



ÉibÛa@Ý—ÐÛa

124

،P.Valueא:אאאא،5٪א

א אא،א אא .אא

2( òíìäÈ¾aòîö§axˆìàäÜÛ:

◘ âìèÐ¾a:א אאא אא אא.אאאא، .א

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◘ Íí‹ÐmwöbnäÛaÕîÜÈnÛaëbèîÜÇ:א א




125

א

א א P. Value )(א

B0 8.149 0.569 0.578

B1 0.735 7.404 0.000

◘ ÕîÜÈnÛa:)B0(א ،P.Value0.578

אאא،5٪א א אאא .א

)B1(،אP.value0.000

אאא،5٪אא א)B1(א .א

3( Âë‹’pbÈi‹¾aô‹Ì—Ûaòí†bÈÛa.

Þëþa@Â‹“Ûa:òîÛa‡nÇa@ÉíŒìnÛa@ïÛbànyüa@ïÓaìjÜÛNormality Test

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א א:)H1(א .אאא



ÉibÛa@Ý—ÐÛa

126

אא אא א :א

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א א א א א، א א א א אא א

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127

@ @òîãbrÛa@òÔí‹Ûa@Z@Šbjn‚a@åß@Ý×@Šbjn‚a@âa‡ƒnbi@bîibyI@Òë‹uìßìÜ×–Òë‹ä@H@L

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ÉibÛa@Ý—ÐÛa

128

:ع احلواري الذي أمامكيف املرب )2

املربع الذي إىل Standardized Residualقم بنقل املتغري )أ .Dependent Listبعنوان

.Plots اختر Displayومن االختيارات )ب الذي احلواري نفس املربع يف ..Plots االختيار فوق أنقرمث )ج

:يلي جديد، كما حواريأمامك، سيظهر لنا مربع

:قم مبا يلي: ييف هذا املربع احلوار )3




129

من خالل Normality Plots with testsنشط االختيار )أ الضغط مرة واحدة باملاوس يف املربع األبيض الذي أمام هذا

.االختيار مث قم بتعطيل .Noneر اخت Boxplotsمث من االختيارات )ب

هو، اهلدف من هذه اخلطوة Stem – and – Leafاالختيار .إليها حاجة املخرجات اليت لسنا يفتقليل

. للعودة للمربع احلواري السابقContinueمث اضغط )ج

نافـذة املخرجـات سنحصل على النتـائج التاليـة يف ، OKمث اضغط )4Output:

◘ ÕîÜÈnÛaë@wöbnäÛa@Íí‹Ðm: אא אאאא

א א

P. value

0.20 17 0.129–א

0.780 17 0.970–א



ÉibÛa@Ý—ÐÛa

130

◘ ÕîÜÈnÛa@òÔí‹ :א אP.Valueא

אאאא،א0.05 א،א אא א אא.א א[א ]אאאא

א א א .אא

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◘ òîöb—ya@ë‹ÐÛa:אא:)H0(אא אא(א

א ).אא אא:)H1(א אא(א

א ).א

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Durbin – Watson Test

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131

א אDurbin-Watsonאא א א אא،א

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א א ،Durbin – Watson

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ÉibÛa@Ý—ÐÛa

132

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ÉibÛa@Ý—ÐÛa

134

אא ،אGoldfield – Quandtא.

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135

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ÉibÛa@Ý—ÐÛa

136

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137

א א א :א

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א א א א:אא א א Continueא.א

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ÉibÛa@Ý—ÐÛa

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אא (x)(y)א

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139

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ÉibÛa@Ý—ÐÛa

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142

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145

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146

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148

א א א :א

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149

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150

א )3 א א Saveא:א

א א א :א

א א א :א. Unstandardizedא א א

Predicted Values

. standardizedא א אResiduals





151

א )4 א א Plotsא:א

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Standardized Residual Plots.


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Y = 4.421 + 0.345 X1 – 1.367 X2 + 0.209 X3




152

א א א :،אא ◘ .0β:()4.421(א (א ◘ א א

o )1β()0.345.(

o )2β()-1.367.(

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א א א א א אא א א ، א א

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153

1H @xˆìàäÜÛ@òîÜØÛa@òíìäÈ¾aZ

א ◘ :אא א):0H(א .אא א):1H(א .א

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).א(

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:אאא א א:א

P.Valueא ،5٪،א ، א א א א א

אא א .א




154

ANOVAא

א אא

אSource א

DF א

SS

אMS

אF cal

P. Value

א 0.000 12.874 2.292 6.877 3א

* * 0.178 2.849 16 א

* * * 9.726 19 א

2( xˆìàäÜÛ@òîö§a@òíìäÈ¾a:

א ◘ :א− )B0:(

0:

0:

01

00

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− )B1:(

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− )B2:(

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20

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155

− )B3:(

0:

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31

30

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=

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א ◘ :א

אא אא

א

א א P. Value )(א

B0 4.421 11.895 0.000

B1 0.345 0.931 0.365

B2 -1.367 -5.545 0.000

B3 0.209 3.854 0.001

:א)B0:(אP.Value،א5٪א א א א، א

א א .א




156

)B1:(אP.Value0.365

א5٪א א א ،)B1(א א .א

)B2:(אP.Value،א5٪א א א ،

)B2(א א .א

)B3(،אP.Value0.001،א5٪א א א ،

)B3(א א .א

3( Âë‹’pbÈi‹¾aô‹Ì—Ûaòí†bÈÛa.

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א ◘ :אא א):H0(א א א .אא א):H1(א א א .א

א א א א א :א

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157

אא א א אא א א א .א

א:א א אא א ، א(א ).א

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paì©a@ @




158

Descriptive א א ، Analyze א )1

Statistics א Explore ، א א :א א

: يف املربع احلواري الذي أمامك )2

إىل املربع Standardized Residualاملتغري قم بنقل -أ .Dependent Listالذي بعنوان

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:أمامك، سيظهر لنا مربع حواري جديد، كما يلي




159

:قم مبا يلي: يف هذا املربع احلواري )3

من Normality Plots with testsنشط االختيار -أ خالل الضغط مرة واحدة باملاوس يف املربع الذي أمام هذا

.االختيارمث قم بتعطيل . None اختر Boxplotsمث من االختيارات -ب

، اهلدف من هذه اخلطوة Stem – and – Leafاالختيار .املخرجات اليت لسنا يف حاجة إليهاتقليل وه

. للعودة للمربع احلواري السابقContinueمث اضغط -ج

، سنحصل على النتـائج التاليـة يف نافـذة املخرجـات OKمث اضغط )4Output:




160

א ◘ :אא א א א א א

א

אP. value

0.149 20 0.166 –א

0.189 20 0.929 –א

:א ◘א אP.Valueא

א0.05 א א א א ، אא א ، א אא

א.א א[א א א א ]אא א א א .אא

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א ◘ :אא א:)H0(א א אא(א

א ).אא א):H1(א א א(א א

א ).א




161

א ◘ :אא א א א א א

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א ◘ :א):DW(א:א א

א אא ،א−אא)DW()1.488.(

א:א א א(א אDurbin – Watson:(

א :k=3،n=16א

73.186.0

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א ))11 :אא ).( dL<DW<4-4א:אא ).DW<dL>0(א:א




162

א ))22 :א

א ).DW<4-du>2(א:אא ).du<DW<2 (א:א

33(( ، א א אא :א

א (א :4-du<DW<4-dL.(א ).dL<DW<du(:א

:dL<DW<du،)0.86<DW<1.73(.−א−)א–א( א א א

אאא.א א .א

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א א א א א א .א

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אאScatterאGraphsא )1 א:א




163

א א א ،Simpleא:אDefineא א א :א

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residual [zre_1]א א .Y Axisא




164

א − א )א(א Unstandardized Predicted Valueא

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189

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190

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191

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192

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193

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ÉbnÛa@Ý—ÐÛa@

194

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195

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196

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197

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ÉbnÛa@Ý—ÐÛa@

198

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199

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א א אאא א"אא"א א :אא

Field, Andy P., (2005). Discovering statistics using spss (2nd edition), London, Sage. (Chapter 15).