Z a U R W ^ G S n a R S [ R G h ^ R G Sººººº n a R | X R g p S asite.iugaza.edu.ps/ssafi/files/2017/09/الإحصاء... · 2017. 11. 11. · Z U U W U W Y S U p c T Y l T i

.

2017 - 2018

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1

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............................................................................................................. 6 ........................................................................................................................ 8 .............................................................................................................. 9 ) ( ...................................................................................... 11 )( .............................................................................................................. 12

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...................................................................................................................... 18

........................................................................................................................ 18

....................................................................................................................... 18 ................................................................................................. 21

– KOLMOGOROV – SMIRNOV TEST...................................... 23

..................................................................................................................... 24

: (T) ONE SAMPLE T-TEST ................................................................... 24 : )T( INDEPENDENT SAMPLES T-TEST ................................ ................ 30

................................................................................................ ................ 39

: )T( ................................................................................................. 39 DEPENDENT (PAIRED) SAMPLES T-TEST ............................................................................. 39

: ) ( ONE-WAY ANOVA ............................................................. 46 : WITHOUT INTERACTION TWO-WAY ANOVA ................................. 57 : WITH INTERACTION TWO-WAY ANOVA ......................................... 60 : ANOVA WITHIN GROUPS ................................ ................. 65 : MIXED ANOVA ............................................... 67

................................................................................................ ................. 70

............................................................................................................... 70

: Sign Test ...................................................................... 72 : Wilcoxon Test ................................. 73 : - Mann-Whitney Test ............................................................. 75

: – Kruskal-WallisTest ....................................... 79 : FriedmanTest ....................................................... 81

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2

................................................................................................ ................. 84

RELATIONSHIPS........................................................................................................ 84

CORRELATION ....................................................................................................... 84 Correlation Coefficient ..................................................................................... 84

TEST CHI-SQUARE ........................................................................................... 89

................................................................................................ ................ 93

LINEAR REGRESSION ....................................................................................... 93

SIMPLE LINEAR REGRESSION ....................................................................... 93 MULTIPLE LINEAR REGRESSION .................................................................. 100

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3

.

Population

.

Comprehensive Survey

.

Samples

.

Raw Data .

.

.

.

1.

)

(

2. .

.

.

– .

4

3. .

4.

5.

.

6. Continuous

.

7. Discrete

1.

.

2. .

3. .

4. .

5. . 6. --

– .

5

7.

8.

.

– .

6

Probability Samples

.

)

... .

.

1.

2.

3.

Simple Random Sampling

Sampling units

N 1 N .

-Sampling with replacement .1n

n

-Sampling without replacement .1 1, ,

1n nn

( )

.

– .

7

1.

2. Outlier or Extreme Point) (

.

1.

.

3 :2

.

3 :2

2.

3.

– .

8

Systematic Sampling

”U”

1 U

”U”

100000

500 ”U” :

100000U 200

500= =

1 200 150

200

1503505507509501150500

1.

2. ) 5 (

1.

.

2.

U

.

"".

– .

9

Stratified Random Sampling

“Strata”

.

.

.

.

1.

2.

:

, 1, 2,i

iNn n iN

in iiNi n N

200 2000

2 380 120

200

– .

10

2000

300 200 400 950 150

250 .

1300 250 37.5 382000

n

1200 250 252000

n

1400 250 502000

n

1950 250 118.75 1192000

n

1150 250 18.75 192000

n

1. .

2.

3. .

4.

5.

6. .

– .

11

) (Multi-Stage Random Sampling) Cluster Sampling

“Cluster” “C”

“R”

.

1 2, , , Rn n n

1 2 Rn n n n .

.

“C” in

1 2 3 4, , ,n n n n

1 2 3 4n n n n n.

.

.

1. .

2.

3.

1. ( )

.

2. – –

.

– .

12

) Permanent (Fixed) Sampling

1. .

2. .

3. .

4. .

5. ( ) .

6.

” “”“.

– -.

.

– .

13

Non-Probability Samples

.

. .

.

Convenience Sampling

Purposive Sampling

Convenience Sampling

Unrestricted Samples

.

.

Accidental Sample

.

Purposive Sampling

– .

14

.

.

.

.

Judgmental Sampling

Quota Sampling.

Judgment Sampling

.

Quota Sampling

.

.

.

– .

15

.

.

. 60%40%

18 12

60% 40% 18 12 .

Snowball Sample

.

.

.

.

.

1. .

2. .

3. .

– .

16

1.

2.

1.

2. .

.

95% -99%

– .

17

0.95 0.96 0.97 0.98 0.99

10 10 10 10 10 10

20 20 20 20 20 20

30 28 29 29 29 29

40 37 37 37 38 38

50 45 45 46 46 47

60 53 53 54 55 56

70 60 61 62 63 64

80 67 68 69 70 72

90 74 75 76 78 80

100 80 81 83 85 88

200 132 136 141 147 154

300 169 176 184 194 207

400 197 206 217 231 250

500 218 230 243 261 286

600 235 248 265 285 316

700 249 264 282 306 341

800 260 277 297 324 363

900 270 288 310 339 383

1000 278 297 321 352 400

2000 323 349 382 427 499

3000 341 370 408 459 544

4000 351 382 422 477 570

5000 357 390 431 489 586

6000 362 395 437 497 598

7000 365 398 442 503 607

8000 367 401 445 507 613

9000 369 403 448 511 618

10000 370 405 450 514 623

100000 383 421 469 539 660

1000000 384 422 471 541 664

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18

Test of Hypotheses

.

.( )

Fundemental Definitions

The Statistical Hypothesis

.

.

The Null Hypothesis

( )

0H NH .

.

(Hypothesized value)0

0 0: 0 (Hypothezied Value) .

70

0 : 70 70

.

– .

19

The Alternative Hypothesis

Research hypothesis) ( 1H AH .

"

"

Statistically Significant .

.

.

1- ( )

1 0: 2- ( )

1 0: 3- ( )

1 0:

.( )

– .

20

Type-I and Type-II Errors

Type-I Error

.

(Level of Significance) " 1

(Confidence level).

1%-5%.

05.0

Type-II Error

.

" Baytuh "

" Beta"1 (Power of the test).

) 1.(

) 1 :(

) 1 (

The Statistical Test

ZT .

ZT *Z*T

– .

21

) (Probability Value) The Observed Significance level

" " (P-value)

( )

0H 1H .

. Sig. P-value .

1- 0H 1H.

2- ) .

3-

4- .

5- :value)-(Sig. or P :

0H value)-(Sig. or P

0H.

) P-value (0.05

0.050.10

.0.10

0H :

1H :

( )

.( ) .

.

– .

22

2

2mZn

Z=1.96 05.0Z=1.96 =0.05

38505.02

96.1 2

n

1nNnNncorrected

N=250

1521385250

250385correctedn

: http://www.surveysystem.com/sscalc.htm

12NNn

N 05.0 :

– .

23

– Kolmogorov – Smirnov Test

( )

.

.

– )Kolmogorov-Smirnov (

50-) Shapiro-Wilk (

50.

50 : 90 82 76 32 21 80 92 65 30 40 70 60 82 45 88 90 70 80 89 89 60 50 90 88 92 76 65 92 77 85 68 79 86 86 79 94 82 71 90 31 83 68 93 94 29 74 80 68 97 50

: –

0 05.. )Normal(. Analyze Descriptive Statistics Explore

SPSS

Tests of Normality

.160 50 .003 .866 50 .000Statistic df Sig. Statistic df Sig.

Kolmogorov-Smirnova Shapiro-Wilk

Lilliefors Significance Correctiona.

Sig.=.003

0 05..

– .

24

Parametric Tests

: (T) One Sample T-Test ) 1(

65, 72, 68, 82, 45, 92, 87, 85, 90, 60, 48, 60, 68, 72, 79, 68, 73, 69, 78, 84

: = 65 Analyze Compare Means One-Sample T Test

T SPSS

One-Sample Statistics

20 72.25 12.867 2.877scoresN Mean Std. Deviation

Std. ErrorMean

One-Sample Test

2.520 19 .021 7.250 1.23 13.27scorest df Sig. (2-tailed)

MeanDifference Lower Upper

95% ConfidenceInterval of the

Difference

Test Value = 65

t = 2.52Sig.(2-tailed)=0.0210.05 ( )

65

( ) 65.

65

(Sig.) 0 021 0 0105

2. . )T

2 (72 25x .

) 65 65

– .

25

/ =

=n

T T n

.

.

.

2.0

0.2 0.8 0.8

.

=7.25 =12.867

7 25 0 56312 867

. .

.

2 52 0 563

20. .

– .

26

) 2(

.100 .

.

( ) 100 .

100 .

SPSS


30 110.23 7.960 1.453N Mean Std. Deviation

Std. ErrorMean

One-Sample Test

7.042 29 .000 10.233 7.26 13.21t df Sig. (2-tailed)


95% Confidence Intervalof the Difference

Test Value = 100

t = 7.042Sig.(2-tailed)=0.0000.05 ( )

( )

100 ( ) 100.

100

(Sig.) 000.0 110 23x .

) 100(

100.

= 10.233 =7.960

10 233 1 2867 960

. ..

7 042 1 286

30. .

– .

27

) 1(

.:

75 . 74 83 94 68 76 60 90 70 80 90 80 68 82 79 76 65 50 70 60 92 82 68 93 71 86 92 90 80 82 65

One-Sample Statistics N Mean Std. Deviation Std. Error Mean

30 77.2000 11.30578 2.06414

One-Sample Test

Test Value = 75

t df Sig. (2-tailed) Mean Difference

95% Confidence Interval of the

Difference

Lower Upper

1.066 29 .295 2.20000 -2.0216 6.4216

– .

28

) 2(

10 .

.5

.

1 - .

2 - Sig


10 5.7000 2.35938 .74610xN Mean Std. Deviation

Std. ErrorMean

One-Sample Test

.938 9 .373 .70000 -.9878 2.3878xt df Sig. (2-tailed)



Difference

Test Value = 5

– .

29

)3(

70 .

20

.SPSS

.

N Mean Std. Deviation Std. Error Mean 20 76.35 6.938 1.551

Test Value = 70

t df Sig. (2-tailed) Mean Difference 4.093 19 0.001 6.350

– .

30

:) T (INDEPENDENT SAMPLES T-TEST

/ = 2

22

2

TT df

df 2 01 .

2 .

.( )

2 1

2 60.0 20 06 0 14. . 20 14 0 23. .

2 0 23.

– .

31

) 1(

.

.

( )

1 2

)

. Analyze Compare Means Independent Samples T Test

Group Statistics

21 85.90 8.496 1.85419 79.32 11.061 2.537

N Mean Std. DeviationStd. Error

Mean

Independent Samples Test

4.135 .049 2.125 38 .040 6.589 3.101 .311 12.867

2.097 33.704 .044 6.589 3.143 .200 12.978

Equal variances assumedEqual variances notassumed

F Sig.

Levene's Test forEquality of Variances

t df Sig. (2-tailed)Mean

DifferenceStd. ErrorDifference Lower Upper


t-test for Equality of Means

) Levene’s Test(Sig. = 0.049 .

t=2.097 Sig. = 0.044

5%.

(Sig.) 0 044 0 022

2. . )T

2 (1 2 6 589x x .

) (

.

– .

32

/ =

= 6.58 =9.795

6 58 0 6729 795

. ..

2

22

2 097 0 1152 097 33 704

. .. .

– .

33

) 1(

.

Group Statistics N Mean Std. Deviation Std. Error Mean

12 34.6667 5.39921 1.55862

13 28.0000 4.12311 1.14354


Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-

tailed)

95% Confidence

Interval of the

Difference

Lower Upper

Equal variances

assumed

1.137 .297 3.487 23 .002 2.71141 10.62192

Equal variances

not assumed 3.449 20.567 .002 2.64135 10.69199

– .

34

)2(

.7

6. SPSS

.

1-

2-

3- ) 1.(

4- 95 % .

5- ) 4) (3.(

6-

– .

35

7 41.4286 13.45185 5.084326 45.0000 22.58318 9.21954

N Mean Std. DeviationStd. Error

Mean

2.638 .133 -.353 11 .731 -25.83335 18.69049-.339 7.895 .743 -27.90654 20.76369

Equal variances assumedEqual variances not assumed

F Sig.


t df Sig. (2-tailed) Lower Upper


Difference


– .

36

) 3(

.16

.

:

42 38 41 37 43 44 45 36

34 35 35 36 39 37 38 34

Group Statistics N Mean Std. Deviation Std. Error Mean

8 40.7500 3.37004 1.19149

8 36.0000 1.85164 .65465


Levene's Test

for Equality of

Variances t-test for Equality of Means

F Sig. t df

Sig. (2-

tailed)

Mean

Difference

Std. Error

Difference

95% Confidence Interval

of the Difference

Lower Upper

Equal

variances

assumed

4.342 .056 3.494 14 .004 4.75000 1.35949 1.83418 7.66582

Equal

variances

not

assumed

3.494 10.83 .005 4.75000 1.35949 1.75353 7.74647

– .

37

) 4(

CPA

CPA .

.

1 - .

2 -

3 - ) 2(

4- ) 3 (Sig

– .

38

Tests of Normality

.208 5 .200 .914 5 .494

.182 7 .200 .944 7 .675

Statistic df Sig. Statistic df Sig.

Kolmogorov-Smirnov Shapiro-Wilk

Group Statistics

5 69.4000 14.46720 6.46993

7 61.2857 13.57343 5.13028

N Mean Std. Deviation

Std. Error

Mean


.031 .863 .994 10 .344 -10.06989 26.29847.983 8.398 .353 -10.77068 26.99925

Equal variances assumedEqual variances not assumed

F Sig.


t df Sig. (2-tailed) Lower Upper


Difference


Ranks

5 7.60

7 5.71

12Total

N Mean Rank

Test Statistics

12.000

40.000

-.896

.370

.432

Mann-Whitney U

Wilcoxon W

Z

Asymp. Sig. (2-tailed)

Exact Sig. [2*(1-tailed Sig.)]

– .

39

:) T ( DEPENDENT (PAIRED) SAMPLES T-TEST

.

.

.

iX

iY .

/ =

=n

T T n

2 2

22T

T df

1df n

– .

40

) 1(

0 05..

Before 96 110 90 94 107 93 89 120 103 92

After 90 96 85 87 104 85 76 103 95 84 Before 86 94 86 110 105 123 95 90 111 123

After 78 84 80 102 95 109 89 83 102 107

:

0 05. Analyze Compare Means Paired- Samples T Test

) T ( SPSS

Paired Samples Statistics

100.8500 20 12.11035 2.7079691.7000 20 10.13644 2.26658

x_beforey_after

Pair1

Mean N Std. DeviationStd. Error

Mean

Paired Samples Correlations

20 .957 .000x_before & y_afterPair 1N Correlation Sig.

Paired Samples Test

9.15000 3.78744 .84690 7.37742 10.92258 10.804 19 .000x_before - y_afterPair 1Mean Std. Deviation

Std. ErrorMean Lower Upper


Difference

Paired Differences

t df Sig. (2-tailed)

R = 0.957.

t = 10.804Sig. (2 tailed) = 0.000

– .

41

(Sig.) 0.000

)9.15 (

0 05..

= 9.15 = 3.787

9 15 0 2 4163 787

. . ..

0 0 2 41620

1 .8 4 .

2

22

10 804 0 86010 804 19

. ..

– .

42

) 2(

) (

( )-

.

.

) .

.(

.

( ) .

) (

) T ( SPSS


30.45 20 4.019 .89934.20 20 6.066 1.356

- -

Pair 1Mean N Std. Deviation

Std. ErrorMean

Paired Samples Correlations

20 .771 .000 - & -

Pair 1N Correlation Sig.

Paired Samples Test

-3.750 3.919 .876 -5.584 -1.916 -4.280 19 .000 - - -

Pair 1Mean Std. Deviation

Std. ErrorMean Lower Upper


Paired Differences

t df Sig. (2-tailed)

– .

43

R =

0.771.

t = -4.280Sig. (2 tailed) = 0.000

.

(Sig.) 0.000

)-3.750 (

0 05..

= -3.750 = 3.919

3 750 0 9573 919

. ..

4 28 0 95720. .

2

22

4 28 0 4914 28 19

. ..

– .

44

)1(

12

.

. (2,1), (3,2), (2,0), (1,3), (2,1), (6,3), (5,3), (4,1), (5,2), (3,2), (2,3), (4,2)


Mean N Std. Deviation Std. Error Mean

Pair 1 1.9167 12 .99620 .28758

3.2500 12 1.54479 .44594

Paired Samples Test

Paired Differences

t df

Sig. (2-

tailed) Mean

Std.

Deviation

95% Confidence Interval of

the Difference

Lower Upper

Pair

1

-

-1.33 1.55700 -2.32260 -.34406 -2.966 11 .013

– .

45

)2(

:

.

( ) .

( ) ( )

45 44 47 48 48 42 47 43 47 46

45 36 35 46 42 36 42 39 38 47

:

Paired Samples Statistics Mean N Std. Deviation Std. Error Mean

Pair 1 45.7000 10 2.11082 .66750

() 40.6000 10 4.42719 1.40000

Paired Samples Test

Paired Differences

t df

Sig. (2-

tailed) Mean

Std.

Deviation

95% Confidence Interval of

the Difference

Lower Upper

Pair

1

-

()

5.1 4.04008 2.20990 7.99010 3.992 9 .003

– .

46

:) ONE-WAY ANOVA ) 1(

:)ANOVA_1(

70 64 48 83 45 94 87 56 83 78 50 84 71 80

87

90

0 05.

Analyze Compare Means One-Way ANOVA

SPSS:

Levene's Test of Equality of Error Variancesa

Dependent Variable:

.322 2 13 .730F df1 df2 Sig.

Tests the null hypothesis that the error variance of thedependent variable is equal across groups.

Design: Intercept+a.

Tests of Between-Subjects Effects

Dependent Variable:

1849.093a 2 924.546 6.044 .014 .48279835.608 1 79835.608 521.891 .000 .9761849.093 2 924.546 6.044 .014 .4821988.657 13 152.974

89394.000 163837.750 15

SourceCorrected ModelIntercept

ErrorTotalCorrected Total

Type III Sumof Squares df Mean Square F Sig.

Partial EtaSquared

R Squared = .482 (Adjusted R Squared = .402)a.

– .

47

= 0.322Sig. = 0.73

F = 6.044Sig. = 0.014

0 05. .

= 0.482

. Post - Hoc One-Way ANOVA Scheffe .

Multiple Comparisons

Dependent Variable: Scheffe

22.30 8.297 .057 -.59 45.19-1.36 7.752 .985 -22.74 20.03

-22.30 8.297 .057 -45.19 .59-23.66* 7.242 .020 -43.64 -3.68

1.36 7.752 .985 -20.03 22.7423.66* 7.242 .020 3.68 43.64

(J) (I) Mean

Difference (I-J) Std. Error Sig. Lower Bound Upper Bound95% Confidence Interval

Based on observed means.The mean difference is significant at the .05 level.*.

Sig. =0.020

0 05..

) 23.66-.(

2 1849.093 0.482

3837.75between

total

SSSS

– .

48

)1(

:

: :

: .

..

1 - .

2 -

.

3 - )2(

4- ) 3 () 1.(

5-

– .

49

.401 11 .000 .650 11 .000

.307 11 .005 .765 11 .003

.195 11 .200 .968 11 .868



3575822 2 1787910.939 57.824 .000

927593.6 30 30919.788

4503416 32

Between Groups

Within Groups

Total

Sum of

Squares df Mean Square F Sig.

Dependent Variable:

Scheffe

45.45455 .833 -147.6302 238.5393

719.90909 .000 526.8243 912.9939

-45.45455 .833 -238.5393 147.6302

674.45455 .000 481.3698 867.5393

-719.90909 .000 -912.9939 -526.8243

-674.45455 .000 -867.5393 -481.3698

(J) (I)

Mean

Difference

(I-J) Sig.

Lower

Bound Upper Bound


Test Statistics a,b

21.961

2

.000

Chi-Square

df

Asymp. Sig.

Kruskal Wallis Testa.

Grouping Variable: b.

11 21.05

11 23.95

11 6.00

33Total

N Mean Rank

– .

50

)2(

: : :

. :

.

1 - .

2 - .

3 - ) 2(

4 -

– .

51

5- ) 3 (Sig

Tests of Normality

.175 3 . 1.000 3 1.000

.175 3 . 1.000 3 1.000

.221 5 .200 .953 5 .758



Test of Homogeneity of Variances

.857 2 8 .460

Levene

Statistic df1 df2 Sig.

ANOVA

4620.000 2 2310.000 7.605 .014

2430.000 8 303.750

7050.000 10

Between Groups

Within Groups

Total

Sum of Squares df Mean Square F Sig.

– .

52


Dependent Variable:

Scheffe

-55.00000 .015 -97.4957 -12.5043

-33.00000 .087 -71.0093 5.0093

22.00000 .281 -16.0093 60.0093

(J) (I) Mean Difference (I-J) Sig. Lower Bound Upper Bound


Ranks

3 2.17

3 9.00

5 6.50

11Total

N Mean Rank

Test Statisticsa

6.729

2

.035

Chi-Square

df

Asymp. Sig.


– .

53

)3(

) 24

8 .SPSS

.

.

– .

54

.

(Sheffe)

Levene's Test of Equality of Error Variances

F df1 df2 Sig. 0.946 2 21 0.404

F Sig. 1,898.583 2 949.292 13.121 0.000

1,519.375 21 72.351

3,417.958 23

Scheffe

Sig.

4.63 0.563

20.75 0.000

16.12 0.004

– .

55

)4(

.

) .(

"

( ) .

.

.

.

.

.

.

SPSS

Levene's Test of Equality of Error Variancesa

Dependent Variable:

2.804 2 27 .078F df1 df2 Sig.

Tests the null hypothesis that the error variance of thedependent variable is equal across groups.

Design: Intercept+a.


Dependent Variable:

244.867a 2 122.433 41.425 .000 .75410453.333 1 10453.333 3536.842 .000 .992

244.867 2 122.433 41.425 .000 .75479.800 27 2.956

10778.000 30324.667 29




Partial EtaSquared


– .

56

= 2.804Sig. = 0.078 .

F = 41.425Sig. = 0.000

.

0 05. = .0.754

Scheffe .



6.70* .769 .000 4.71 8.695.10* .769 .000 3.11 7.09

-6.70* .769 .000 -8.69 -4.71-1.60 .769 .134 -3.59 .39-5.10* .769 .000 -7.09 -3.111.60 .769 .134 -.39 3.59

(J) (I) Mean

Difference (I-J) Std. Error Sig. Lower Bound Upper Bound95% Confidence Interval


-

000.0 Sig. = 0 05..

)6.70.(

-

000.0 Sig. = 0 05..

)5.10.(

-

134Sig. =0. 0 05..

– .

57

:Without Interaction Two-Way ANOVA

) 1(

. 10 9 8 7 6 5 4 3 2 1

74 83 94 68 76 60 90 70 80 90 1 80 68 82 79 65 50 70 60 92 82 2 68 93 71 86 92 90 80 82 65 76 3

(

(05.0

:


Dependent Variable:

1052.733a 11 95.703 .649 .766178795.200 1 178795.200 1212.597 .000

746.133 9 82.904 .562 .810306.600 2 153.300 1.040 .374

2654.067 18 147.448182502.000 30

3706.800 29




R Squared = .284 (Adjusted R Squared = -.154)a.

:

:F = 0.562 )Sig. = 0.81 05.0 ( )

:

:F = 1.040 )Sig. = 0.374 05.0 ( )

2 2 2 *

**

, ,A B A BA B A B

Error A Error B Error A B

SS SS SSSS SS SS SS SS SS

– .

58

)1(

.SPSS

1 -

.

2 -

3 -

.

– .

59

Dependent Variable:

186.750 5 37.350 11.492 .005 .90546500.750 1 46500.750 14307.923 .000 1.000

118.500 2 59.250 18.231 .003 .85968.250 3 22.750 7.000 .022 .77819.500 6 3.250

46707.000 12206.250 11




Partial EtaSquared



-7.5000 1.27475 .003 -11.5885 -3.4115-2.2500 1.27475 .285 -6.3385 1.83855.2500 1.27475 .018 1.1615 9.3385

(J) (I)

MeanDifference

(I-J) Std. Error Sig. Lower Bound Upper Bound95% Confidence Interval



4.0000 1.47196 .160 -1.5607 9.56076.0000 1.47196 .037 .4393 11.56071.0000 1.47196 .923 -4.5607 6.56072.0000 1.47196 .630 -3.5607 7.5607

-3.0000 1.47196 .335 -8.5607 2.5607-5.0000 1.47196 .075 -10.5607 .5607

(J) (I)

MeanDifference

(I-J) Std. Error Sig. Lower Bound Upper Bound95% Confidence Interval

– .

60

: With Interaction Two-Way ANOVA ) 1(

( ) .

: .

.

.

. :

) 1 2 ) (1 :2 :3 ( :

1 -

2 -

3 - Analyze General Linear Model Univariate

:

Between-Subjects Factors

1515101010

12123

Value Label N


Dependent Variable:

3984.267a 5 796.853 13.344 .000 .73537878.533 1 37878.533 634.304 .000 .964

34.133 1 34.133 .572 .457 .0233678.867 2 1839.433 30.803 .000 .720

271.267 2 135.633 2.271 .125 .1591433.200 24 59.717

43296.000 305417.467 29


* ErrorTotalCorrected Total


Partial EtaSquared


– .

61

:Sig.=0.457

:Sig.=0.000

:Sig.=0.125


Dependent Variable: scoreTukey HSD

8.70* 3.456 .048 .07 17.3326.60* 3.456 .000 17.97 35.23-8.70* 3.456 .048 -17.33 -.0717.90* 3.456 .000 9.27 26.53

-26.60* 3.456 .000 -35.23 -17.97-17.90* 3.456 .000 -26.53 -9.27

(J) methodDicussListenNotesListenNotesDicuss

(I) methodNotes

Dicuss

Listen

MeanDifference (I-J) Std. Error Sig. Lower Bound Upper Bound



Notes DISCUSS .

Notes Listen .

. .

.

gender method

.

.

– .

62

Estim

ated

Mar

gina

l Mea

ns

50

40

30

20

10

Estimated Marginal Means of

– .

63

) 2(

( )

)Example11.(

3B 2B 1B

2.3, 1.6 1.8, 2.2 2, 1.5 1A

1.7, 2.1 2.3, 1.5 2.3, 2.6 2A

2.3, 1.7 2.1, 1.8 1.5, 2 3A

1.9, 1.5 1.5, 2.1 2.1, 1.8 4A

05.0:

(

(

(

:


Dependent Variable:

.835a 11 .076 .588 .80688.935 1 88.935 688.529 .000

.228 3 .076 .589 .634

.033 2 .016 .126 .883

.574 6 .096 .741 .6271.550 12 .129

91.320 242.385 23


* ErrorTotalCorrected Total


R Squared = .350 (Adjusted R Squared = -.246)a.

:

F = 0.126 Sig. = 0.883 05.0 ( )

:

F = 0.589 Sig. = 0.634 05.0 ( )

:

– .

64

F = 0.741 )0.627Sig. = 05.0 ( )

0H

Post Hoc… Bonferroni

– .

65

: ANOVA Within Groups (Repeated Measures ANOVA)

) 1(

. .

.

.

1. ) 15 .(

2. )

15 .(

3. ) 15 .(

4. ) 15

.(

5. ) 15

.(

( )

( ) .

.

) .(

Analyze General Linear Model Repeated Measures

: Mauchly's Test of Sphericityb

Measure: MEASURE_1

.094 41.250 9 .000 .442 .484 .250Within Subjects Effectfactor1

Mauchly's WApprox.

Chi-Square df Sig.Greenhouse-

Geisser Huynh-Feldt Lower-bound

Epsilona

Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to anidentity matrix.

May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in theTests of Within-Subjects Effects table.

a.

Design: Intercept Within Subjects Design: factor1

b.

– .

66

"Mauchly's Test of Sphericity" " Sphericity

Condition" F .Sig.=0.000 .

F " Epsilon".

Tests of Within-Subjects Effects

Measure: MEASURE_1

1547.660 4 386.915 207.754 .0001547.660 1.769 874.709 207.754 .0001547.660 1.938 798.734 207.754 .0001547.660 1.000 1547.660 207.754 .000

141.540 76 1.862141.540 33.617 4.210141.540 36.815 3.845141.540 19.000 7.449

Sphericity AssumedGreenhouse-GeisserHuynh-FeldtLower-boundSphericity AssumedGreenhouse-GeisserHuynh-FeldtLower-bound

Sourcefactor1

Error(factor1)


- Sphericity Assumed :

- Greenhouse-Geisser :

Greenhouse-Geisser Sig.

=0.000

Pairwise Comparisons

Measure: MEASURE_1

11.150* .634 .000 9.139 13.1616.250* .403 .000 4.971 7.529

10.250* .652 .000 8.179 12.3217.200* .408 .000 5.906 8.494

-11.150* .634 .000 -13.161 -9.139-4.900* .390 .000 -6.138 -3.662

-.900* .270 .035 -1.758 -.042-3.950* .407 .000 -5.242 -2.658-6.250* .403 .000 -7.529 -4.9714.900* .390 .000 3.662 6.1384.000* .363 .000 2.849 5.151

.950* .185 .001 .364 1.536-10.250* .652 .000 -12.321 -8.179

.900* .270 .035 .042 1.758-4.000* .363 .000 -5.151 -2.849-3.050* .387 .000 -4.279 -1.821-7.200* .408 .000 -8.494 -5.9063.950* .407 .000 2.658 5.242-.950* .185 .001 -1.536 -.364

3.050* .387 .000 1.821 4.279

(J) factor123451345124512351234

(I) factor11

2

3

4

5

MeanDifference (I-J) Std. Error Sig.a Lower Bound Upper Bound

95% Confidence Interval forDifferencea

Based on estimated marginal meansThe mean difference is significant at the .05 level.*.

Adjustment for multiple comparisons: Bonferroni.a.

– .

67

: Mixed ANOVA ) 1(

.

( )

.

..

Analyze General Linear Model Repeated Measures

:

Multivariate Testsb

.881 62.926a 2.000 17.000 .000 .881

.119 62.926a 2.000 17.000 .000 .8817.403 62.926a 2.000 17.000 .000 .8817.403 62.926a 2.000 17.000 .000 .881

.959 197.963a 2.000 17.000 .000 .959

.041 197.963a 2.000 17.000 .000 .95923.290 197.963a 2.000 17.000 .000 .95923.290 197.963a 2.000 17.000 .000 .959

Pillai's TraceWilks' LambdaHotelling's TraceRoy's Largest RootPillai's TraceWilks' LambdaHotelling's TraceRoy's Largest Root

Effect

*

Value F Hypothesis df Error df Sig.Partial EtaSquared

Exact statistica.

Design: Intercept+ Within Subjects Design:

b.

* Sig.=0.000.

Mauchly's Test of Sphericityb

Measure: MEASURE_1

.920 1.426 2 .490 .926 1.000 .500Within Subjects Effect Mauchly's W

Approx.Chi-Square df Sig.

Greenhouse-Geisser Huynh-Feldt Lower-bound

Epsilona

Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to anidentity matrix.

May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in theTests of Within-Subjects Effects table.

a.

Design: Intercept+ Within Subjects Design:

b.

(Sig.=0.490) Sphericity Assumed

– .

68

Tests of Within-Subjects Effects

Measure: MEASURE_1

880.533 2 440.267 68.554 .000 .792880.533 1.851 475.702 68.554 .000 .792880.533 2.000 440.267 68.554 .000 .792880.533 1.000 880.533 68.554 .000 .792

2254.933 2 1127.467 175.557 .000 .9072254.933 1.851 1218.213 175.557 .000 .9072254.933 2.000 1127.467 175.557 .000 .9072254.933 1.000 2254.933 175.557 .000 .907231.200 36 6.422231.200 33.318 6.939231.200 36.000 6.422231.200 18.000 12.844

Sphericity AssumedGreenhouse-GeisserHuynh-FeldtLower-boundSphericity AssumedGreenhouse-GeisserHuynh-FeldtLower-boundSphericity AssumedGreenhouse-GeisserHuynh-FeldtLower-bound

Source

*

Error( )


Partial EtaSquared

Sig. =0.000

)Sig. =0.000(.

Sig. =0.000

.(Partial Eta Squared) 0.923


Measure: MEASURE_1Transformed Variable: Average

11454.017 1 11454.017 1322.465 .000 .9871870.417 1 1870.417 215.956 .000 .923

155.900 18 8.661

SourceIntercept

Error


Partial EtaSquared

) (

( )

– .

69

321

Estim

ated

Mar

gina

l Mea

ns

35

30

25

20

15

10

5

Estimated Marginal Means of MEASURE_1

– .

70

Non-Parametric Tests

SPSS

"Sign Test"

"Wilcoxon Test"

– .

71

– "Mann Whitney Test"

– "Kruskal-Wallis Test"

.( )

"Friedman Test"

(Repeated Measures) .

– .

72

:Sign Test t

SPSS

) 1(

15

60

. 25 84 95 30 90 85 60 87 86 64 88 89 92 94 88

60

05..

60.

: Analyze Non-Parametric Tests Binomial Test

SPSS

Descriptive Statistics

14 78.36 22.775 25 95N Mean Std. Deviation Minimum Maximum

Binomial Test

<= 60 2 .14 .50 .013> 60 12 .86

14 1.00

Group 1Group 2Total

Category NObserved

Prop. Test Prop.Exact Sig.(2-tailed)

Sig.=0.013

60

05.60 .

) 60( 12 86% 60

– .

73

: Wilcoxon Test 10

)10 (1 )6 5

) - .(

.

SPSS

) 1(

12

(2,1), (3,2), (2,0), (1,3), (2,1), (6,3), (5,3), (4,1), (5,2), (3,2), (2,3), (4,2).

0 05.. Analyze Non-Parametric Tests 2 Related Samples…

SPSS

Ranks

2a 5.25 10.5010b 6.75 67.50

0c

12

Negative RanksPositive RanksTiesTotal

- N Mean Rank Sum of Ranks

> a.

< b.

= c.

Test Statisticsb

-2.266a

.023ZAsymp. Sig. (2-tailed)

-

Based on negative ranks.a.

Wilcoxon Signed Ranks Testb.

23Sig.=.0

0 05. 0 05.

( ) 6.75

( ) 5.25

.

– .

74

14 1

1prbTr

n n

:

1T :n :

prbr :0.4 :0.4 0.70.7 0.9

:0.9. 14 1

14 67 5 1

12 12 10 73

prbTr

n n.

.

– .

75

: - Mann-Whitney Test –

.

– ( ) t ( )

SPSS

) 1(

( ) ) .

. ( ) :

14 3

11 6

12 4

9 20

6 6

4 5

3 8

7 2 2

1

Analyze Non-Parametric Tests 2-Independent Samples…

– SPSS

Ranks

10 9.85 98.508 9.06 72.50

18Total

N Mean Rank Sum of Ranks

– .

76

Test Statisticsb

36.50072.500

-.312.755

.762a

Mann-Whitney UWilcoxon WZAsymp. Sig. (2-tailed)Exact Sig.[2*(1-tailed Sig.)]

Not corrected for ties.a.


Sig=0.762

0 05. .

0 05.

1 2

1 2

2rb

MR MRr

n n

:

1MR :2MR :

1n :2n :

rbr

:0.4 :0.4 0.70.7 0.9

:0.9.

1 2

1 2

2

2 9 85 9 0610 8

0 088

rb

MR MRr

n n

. .

.

– .

77

) 2(

.

)Mann-Whitney_2(

40 29 44 27 33 32 26 25 31 27 29 28 34 31 31 23 38 37 33 28 42 22 35 31 24

0 05.

– SPSS Ranks

12 17.54 210.5013 8.81 114.5025Total

N Mean Rank Sum of Ranks

Test Statisticsb

23.500114.500

-2.972.003

.002a

Mann-Whitney UWilcoxon WZAsymp. Sig. (2-tailed)Exact Sig.[2*(1-tailed Sig.)]

Not corrected for ties.a.


:Sig.=.002

0 05..

17.54 8.81

.

– .

78

1 2

1 2

2

2 17 54 8 8112 13

0 698

rb

MR MRr

n n

. .

.

– .

79

:– Kruskal-WallisTest - –

SPSS

) 1(

86 82 75 81 66 78 84 69 61 71 72 69 81 67 75 88 30 79 77 77

0 05. )Wallis-Kruskal(

Analyze Non-Parametric Tests k Independent Samples…

– .

80

- SPSS

Ranks

8 15.067 7.145 7.90

20Total

N Mean Rank

Test Statisticsa,b

8.0022

.018

Chi-SquaredfAsymp. Sig.



8.002Sig.=.018

3

0 05.. .

15.06

)7.147.90 (.

2 1H

H kn k

:

H : -2(K :n :

2H ) :2( :0.0620 06 0 14. . :20 14 0 23. .2 0 23.

2 1

8 002 3 120 3

0 35

HH k

n k.

.

– .

81

: FriedmanTest

)

.

.

SPSS

) 1(

10 . .

8 7 9 8 8 8 8 5 9 8 7 8

0 05. Analyze Non-Parametric Tests k Related Samples…

SPSS

Ranks

3.172.172.672.00

Mean Rank

– .

82

Test Statisticsa

31.875

3.599

NChi-SquaredfAsymp. Sig.

Friedman Testa.

1.875Sig.=0.599

0 05.

.

2

1FF

n k

F :-2(K :n :

2Friedman ) :2(

:0.0620 06 0 14. . :20 14 0 23. .2 0 23.

2

11 875

12 4 10 05

FF

n k.

.

– .

83

) 2(

) (

10 7 11 13

8 13 6 10 7 15 11 9

11 11 9 14 9 12 8 11 7 8 7 12 8 14 5 10

11 10 10 13

0 05.

SPSS

Ranks

1.563.191.883.38

Mean Rank

Test Statisticsa

812.346

3.006

NChi-SquaredfAsymp. Sig.

Friedman Testa.

12.346Sig.=.006

0 05.. .

1.56

) 3.191.88 3.88 (

2 12 346 0 129

1 32 4 1FF . .

n k

– .

84

Relationships

CORRELATION

.

)

.

Dependent (Response) Variable :

Y.

Independent (Explanatory) Variable :

X .

X Y XY.

.

X, Y Scatter plot

X, Y

Correlation Coefficient Y, X r

1 1r 11

– .

85

1

r = 0 (

.

r 1 1 .

.X, Y

120 r.

31

2 4r.

34 1r

12 0r

21

43 r

431 r

:

1r

.8r

.6r

.4r

.2r

0r

.1r

.3r

.5r

– .

86

.7r .9r 1r

– .

87

) 1(

.

. 30

.

)correlation1(

1.

2. .( )

3. )

.(

4. )

.(

5.

.

Analyze – Correlate – Bivariate

Exercise IQ 0.614 Sig. =0.000

30 . 0 05..

SPSS Correlations

1 .897** .691** -.614** .614**.000 .000 .000 .000

30 30 30 30 30.897** 1 .696** -.562** .511**.000 .000 .001 .004

30 30 30 30 30.691** .696** 1 -.243 .421*.000 .000 .196 .021

30 30 30 30 30-.614** -.562** -.243 1 -.225.000 .001 .196 .231

30 30 30 30 30.614** .511** .421* -.225 1.000 .004 .021 .231

30 30 30 30 30

Pearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)N

exercise

esteem

satisfy

stress

iq

exercise esteem satisfy stress iq

Correlation is significant at the 0.01 level (2-tailed).**.

Correlation is significant at the 0.05 level (2-tailed).*.

– .

88

) 2(

)correlation2(

:

SPSS

Correlations

1.000 .718*. .019

10 10.718* 1.000.019 .

10 10

Correlation CoefficientSig. (2-tailed)NCorrelation CoefficientSig. (2-tailed)N

Spearman's rho

Correlation is significant at the 0.05 level (2-tailed).*.

=0.718

. Sig.=.019

– .

89

Test Chi-Square

) 1(

.

.

39 : .

– – .( )

: .– –

.

.

)chi_square1(.

5 80%

Analyze – Descriptive Statistics – Crosstabs

* Crosstabulation

9 3 1 133.7 4.7 4.7 13.0

69.2% 23.1% 7.7% 100.0%1 10 2 13

3.7 4.7 4.7 13.07.7% 76.9% 15.4% 100.0%

1 1 11 133.7 4.7 4.7 13.0

7.7% 7.7% 84.6% 100.0%11 14 14 39

11.0 14.0 14.0 39.028.2% 35.9% 35.9% 100.0%

CountExpected Count% within CountExpected Count% within CountExpected Count% within CountExpected Count% within

Total

Total

– .

90

Chi-Square Tests

34.208a 4 .00032.871 4 .000

19.118 1 .000

39

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

9 cells (100.0%) have expected count less than 5. Theminimum expected count is 3.67.

a.

Sig. =0.000

df :) (

( )

2 1df 0.10 0.30 0.50

3 2df 0.07 0.21 0.35

4 3df 0.06 0.17 0.29

2 34 208 0 439 0 662

39 2c c.V . .

n df

– .

91

)1(

.

1 - .

2 -

3 - ) 2 (

4 - ) 1 . (

– .

92

20 20 40 80

32.0 32.0 16.0 80.0

25.0% 25.0% 50.0% 100.0%

20 20 0 40

16.0 16.0 8.0 40.0

50.0% 50.0% .0% 100.0%

40 40 0 80

32.0 32.0 16.0 80.0

50.0% 50.0% .0% 100.0%

80 80 40 200

80.0 80.0 40.0 200.0

40.0% 40.0% 20.0% 100.0%

10

20

40

Total

75.000 4 .00089.257 4 .000

34.068 1 .000

200

Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases

Value dfAsymp. Sig.

(2-sided)

– .

93

Linear Regression

Simple Linear Regression

Independent variable x

Dependent variable y.

) y () x.(

) Scatter

Plot(

) Scatter

Plot(

yx, y

y

y x xy 10

x

y

0 y

1 y x.

– .

94

( )

( )

(Dummy Variables) " 0" "1 "

) 1(

300 350 500 600 900 1000 900 1200 1050 250

280 340 500 550 800 750 850 1050 1000 250

:

Income(J.D)

a . Enter

Model1

VariablesEntered

VariablesRemoved Method

Variables Entered/Removedb

All requested variables entered.a.

Dependent Variable: Consumption (J.D)b.

.982a .965 .960 58.6090Model1

R R SquareAdjustedR Square

Std. Errorof the

Estimate

Model Summary

Predictors: (Constant), Income (J.D)a.

751329.9 1 751329.9 218.727 .000a

27480.111 8 3435.014778810.0 9

RegressionResidualTotal

Model1

Sum ofSquares df

MeanSquare F Sig.

ANOVAb

Predictors: (Constant), Income (J.D)a.

Dependent Variable: Consumption (J.D)b.

48.229 43.913 1.098 .304

.835 .056 .982 14.789 .000

(Constant)Income(J.D)

Model1

B Std. Error

UnstandardizedCoefficients

Beta

Standardized

Coefficients

t Sig.

Coefficientsa

Dependent Variable: Consumption (J.D)a.

– .

95

:

Consump. = 48.229 + 0.835 * Income

= 0.982

). 0.000 0.05Sig(

965.02R =0.96 = 58.6190.

96.5% ( )

3.5%

F= 218.727000.0.Sig

098.1t0bSig.=0.304

789.14t1bSig.=0.000

– .

96

) 2(

.

25 .

.

.

.

1 - " X "

"Y."

2-

3 - )

.( Analyze Regression Linear

:

Model Summary

.826a .683 .669 47.332Model1

R R SquareAdjusted R

SquareStd. Error ofthe Estimate

Predictors: (Constant), a.

R=0.826 :

R Square=0.683 :( )68.3%

ANOVAb

110987.2 1 110987.191 49.541 .000a

51526.81 23 2240.296162514.0 24


Model1

Sum ofSquares df Mean Square F Sig.

Predictors: (Constant), a.

Dependent Variable: b.

– .

97

Coefficientsa

221.126 15.964 13.852 .00015.929 2.263 .826 7.039 .000

(Constant)Model1

B Std. Error


Beta

StandardizedCoefficients

t Sig.

Dependent Variable: a.

= 221.126 +15.929 *

Sig. =0.000

– .

98

)1(

) Y ( )1X (

)2X ( 1990 -2012 .

1. .

2. .

3. " " .

4.

5. ( ) " " ) 4 (

Model Summary

.995a .990 .989 2.15754Model1


Std. Error ofthe Estimate

Predictors: (Constant), x2, x1a.

– .

99

ANOVAb

9040.379 2 4520.189 971.045 .000a

93.099 20 4.6559133.478 22


Model1


Predictors: (Constant), x2, x1a.

Dependent Variable: yb.

Coefficientsa

52.029 24.038 2.164 .043-.395 .152 -.472 -2.601 .017.035 .012 .525 2.893 .009

(Constant)x1x2

Model1

B Std. Error


Beta


t Sig.

Dependent Variable: ya.

– .

100

Multiple Linear Regression

) y (1x 2x

n

y 12 , xx

22110 xxy

22110ˆ xbxbby

Y

1 2 kX ,X , , X.

– .

101

) 1(

salary salbegin

educ minority )1 =0 ( =474

- salary salbegin, educ, minority .

-

Model Summary

.891a .794 .792 $7,783.85Model1


Square

Std. Errorof the

Estimate

Predictors: (Constant), Minority Classification,Educational Level (years), Beginning Salary

a.

ANOVAb

1.09E+11 3 3.65E+10 602.097 .000a

2.85E+10 470 605882611.38E+11 473


Model1

Sum ofSquares df

MeanSquare F Sig.

Predictors: (Constant), Minority Classification, Educational Level (years),Beginning Salary

a.

Dependent Variable: Current Salaryb.

Coefficientsa

-7200.395 1792.199 -4.018 .0001.664 .059 .767 28.186 .000

1009.327 160.440 .171 6.291 .000-1394.343 875.659 -.034 -1.592 .112

(Constant)Beginning SalaryEducational Level (years)Minority Classification

Model1

B Std. Error


Beta

Standardized

Coefficients

t Sig.

Dependent Variable: Current Salarya.

salary salbegin, educ, minority :

Salary = -7200.395 + 1.664 * Salbegin + 1009.327 * Educ – 1394.343 * Minority

2 .Salary salbegin, educ, minority .891

.

3 .794.0R 2 =.792 = 7783.85

– .

102

79.4% ( )

20.6%

F=602.097. 0.000Sig

018.4t0bSig.=0.000

186.28t1bSig.=0.000

291.6t2bSig.=0.000

592.1t2bSig.=0.112

– .

103

)1(

.

.

.

30 .

)

) .(

.(

.( )

)

(

.( )

)

) .(

developmental ability (.

1 -

2 - .

Analyze Regression Linear

:

Model Summary

.930a .865 .849 5.664Model1



Predictors: (Constant), homeenv, temper, supporta.

– .

104

ANOVAb

5326.979 3 1775.660 55.342 .000a

834.221 26 32.0856161.200 29


Model1


Predictors: (Constant), homeenv, temper, supporta.

Dependent Variable: developb.

Coefficientsa

-8.307 5.344 -1.555 .132.447 .071 .663 6.284 .000.291 .148 .165 1.967 .060.563 .271 .221 2.080 .048

(Constant)supporttemperhomeenv

Model1

B Std. Error


Beta


t Sig.

Dependent Variable: developa.

Predicted DEVELOP = -8.307 + 0.447 *(SUPPORT) + 0.291 *(TEMPER) + 0.563 *(HOMEENV)

Stepwise Model Summary

.899a .809 .802 6.487 .809 118.416 1 28 .000

.919b .844 .833 5.958 .036 6.193 1 27 .019

Model12



R SquareChange F Change df1 df2 Sig. F Change

Change Statistics

Predictors: (Constant), supporta.

Predictors: (Constant), support, homeenvb.

ANOVAc

4982.957 1 4982.957 118.416 .000a

1178.243 28 42.0806161.200 295202.779 2 2601.390 73.285 .000b

958.421 27 35.4976161.200 29

RegressionResidualTotalRegressionResidualTotal

Model1

2


Predictors: (Constant), supporta.

Predictors: (Constant), support, homeenvb.

Dependent Variable: developc. Coefficientsa

6.509 3.246 2.005 .055.606 .056 .899 10.882 .000

-3.299 4.942 -.667 .510.476 .073 .705 6.487 .000.689 .277 .271 2.489 .019

(Constant)support(Constant)supporthomeenv

Model1

2

B Std. Error


Beta


t Sig.

Dependent Variable: developa. Predicted DEVELOP = -3.299 + 0.476 *(SUPPORT) + 0.689 *(HOMEENV)

– .

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150.190 4 37.547 86.354 .00054.786 126 .435

204.976 130


Model1


.173 .508 .341 .734

.257 .103 .208 2.494 .014

.142 .106 .140 1.343 .182

.226 .108 .241 2.088 .039

.367 .090 .341 4.100 .000

(Constant)Model1

B Std. Error


Beta


t Sig.

– .

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.913 .834 .800 5.50148Model1



3654.606 5 730.921 24.150 .000726.391 24 30.266

4380.998 29


Model1


Coefficientsa

-.250 7.740 -.032 .974

-.095 .364 -.027 -.260 .797

-.010 .014 -.107 -.710 .484

.048 .014 1.729 3.498 .002

-.073 .019 -2.304 -3.771 .001

.138 .019 1.584 7.236 .000

(Constant)

Model

1

B Std. Error

Unstandardized

Coefficients

Beta

Standardized

Coefficients

t Sig.

Dependent Variable: a.

Z a U R W ^ G S n a R S [ R G h ^ R G Sººººº n a R | X R g p S asite.iugaza.edu.ps/ssafi/files/2017/09/الإحصاء... · 2017. 11. 11. · Z U U W U W Y S U p c T Y l T i

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