. . .

2006

. : . : .

DataSets : http://research.edu.uoi.gr/aemvalot

SPSS SPSS Inc [www.spss.com, www.spss.gr]

1. E 7 1.1 8 1.2 11 1.3 - 13 1.4

() 17

2. 19 2.1 Pearson r 21 2.2 26 2.3 28 2.4

Pearson r 30

2.5

34

2.6 - 35 3. 37 3.1

SPSS 42

3.2 47 4. 49 4.1 50 4.2 51 4.2.1 52 4.2.1.1 52 4.2.1.2 52 4.2.1.3 54 4.3

56

4.4

56

4.5 61 4.5.1 61 4.5.1.1 62

4.5.2 :

67

4.6

69

5. 71 5.1 72 5.2 ANOVA 73 5.2.1 ANOVA 73 5.2.2 Post hoc 74 5.3 ANOVA 75 5.4 ANOVA 75 6. x2 79 6.1 x2 80 6.2

SPSS 87

7. 89 7.1 90 7.2 92 7.2.1 92 7.2.2

. 93

7.2.3 94 8 97

& ( ) . . , & . : () , () () . () . . , . () , , . , "-", . .

-7-

1

-8-

1. 1.1.

, - . (variables). . . , . ( ) . , (, ).

, . (qualitative) (quantitative) .

(qualitative variables) , , , , , ... . , ( ) . , - / - .

(quantitative variables) , , , ( ), ... , . ( Celsius, Kelvin Fahrenheit), .

(continuous) (discrete).

() , (real numbers). ,

-9-

. 67.2 (Kgr), 67.3 (Kgr), 67.4 (Kgr), ...

() , . , . , 3 , 4 , 5 , .., 2.5 .

(independent) (dependent). .

. () (predictor variable), () .

. () (outcome/response variable).

(control), (extraneous) , (suppressor) (intervening) .

, , .

() , .

() .

.

-10-

1

-11-

1.2.

Stevens (1946). , . & . (quantitative) , (qualitative) . (nominal) (ordinal) , (interval) (ratio).

2

. () . . 1.

1 .

-12-

. , . . , () 2 , 30 (!) , (, , , .). , .

, , . . 10C 20C (10C) , 80C 90C (10C). . y=a+bx ( x , y b a ) (, .. 1999:1-28)2.

. ( ), ( ) . y=bx (, . 1999: 1-28). (1 = 340,750 )

2 .

-13-

1.3.

- ( ), () () . :

() , , () , () , ( ) .

(histogram), (frequency polygon), (frequency curve), (bar chart), (pie chart) (boxplot), (stem and leaf diagram) (dot diagram).

- (histogram) . () . 3 4 (. http://www.shodor.org /interactivate/activities /histogram/).

0

0,05

0,1

0,15

0,2

0,25

0,3

160 166 172 178 184 190 196 1:

3 . 4 (scale) .

-14-

- (frequency polygon)

. x, .

0

0,05

0,1

0,15

0,2

0,25

0,3

160 166 172 178 184 190 196

2: () - (frequency curve)

5 . ( ) (rectangular distribution), (normal distribution), student F . ( Gauss) . , .

3 & 4: 5 (, , student, 2, ..) (, , , , .).

-15-

- (bar chart)

. (x) . (Norusis 2002:570-573). Pareto (Paretos chart), (. http://nces.ed.gov /nceskids/Graphing/bar_pie_data.asp?ChartType=bar).

- (pie chart)

( ) 360 (360 ). , 3.6 ( 1% ), . () 34 34 x 3.6 = 122.4 . () ( 100% ), () 6 () 7. (.http://nces.ed.gov/nceskids/Graphing/bar_pie_data.asp?ChartType=pie,http://www.shodor.org/interactivate/activities/piechart/index.html ).

6 () . 7 () .

-16-

5: - (boxplot)

. (, , 1-2 & 3 ) , . () (. 6) (8), 9. .

8 boxplot . 9 (outlier) (extreme)

-17-

6: 1.4 ()10

1. 11 . ( ) .

2. . , .

3. : a. b. ( ) c. ( ).

10 . , . (1997). : , . : Gutenberg. , . (1998). : . : Gutenberg. 11

-18-

-19-

2

-20-

2. 12 ( , ) , ; . , .

. 5 7. ; , . 10 20; ; 50; , (random) - - . . , , , 5% . , 5 100 , , . - ( ), . 4 100 (), 5 100 ; . () 10%, 5%, 1% 1.

, , , 5% ( 12 .

-21-

). 5% , () - . . (0), (1, , ). . 2.1. Pearson r

Pearson r () (.., ). . , - , . Pearson r :

() & () . ,

. , . . , ( ), . . , ( ) ( ), () ( ).

-22-

: ( ): 0: : 10 , :

1: 1 2 3 4 5 6 7 8 9 10

2 4 6 8 1 0 3 5 7 9

12 15 16 20 9 6 13 16 18 19 () (scatterplot) SPSS : Graphs SPSS Scatter/Dot. Define, Simple Scatter.

7: . .

-23-

(Study) (Grades) 13. .

8: . 9 & 9 SPSS . 9 & 9, /, ( ). , , ( 10). , ( 11), ( ) ( 12).

13 o .

-24-

9: .

9: .

0 6

(outlier) ( )

-25-

10: 2 .

11: 2 .

-26-

12: 2 . 2.2. H

, . , . , 9, , . () . . (.., Yerkes & Dowdson, 1908) , ( ), ( - ). , . , ( 13).

-27-

13: . 13, ( ) . , , . 14, . , . , . ( ) ( ), Pearson .

. . , SPSS , , . Regression-Curve Estimation. , (fit functions).

-28-

14: . 2.3.

(. ) . .

, . , 14 , 100 15:

14 .

-29-

15: . 15 (. ) ( 90-100) . , ( ) () . - () , . , 15 120 130 ( .., IQ ), . (.., 70-80). () Kolmogorov-Smirnov. SPSS . , .

-30-

2.4. Pearson Pearson r; , . r -1 +1. ( ), ( ) . . 0.6 -0.6, . , 1.0 / ( ). 2 (-1 +1), . :

0.00-0.20 0.21-0.40 0.41-0.60 0.61-0.80 > 0.81

0.80

, : 0.80 /; , .

. . Pearson r :

X Y

, y .

-31-

. . . , , , . , . , . , , . SPSS Analyze Correlate Bivariate. (. 16 & 17), , Pearson r 15 . - Spearman Kendall.

15 . : ( . ). , . , . , .

-32-

16 & 17: Pearson r SPSS.

18: Pearson r SPSS. 10 0.964

Correlations

1 .964**.000

10 10.964** 1.000

10 10

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

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

-33-

: p = .000. , 1. = 5% ( ), .

, . ( 10 ) ( 500 ), . ( ) ( ) . , , .

-34-

2.5. Pearson / Pearson r:

1. . () .

2. , , . .

3. - . () .

4. , , . , ( 16).

5. . point-biserial , .

6. , . 17 , .

7. . , . .

16 , . , ( ). 17 - . () .

-35-

.

2.6. - (Spearman) (. , ), . Spearman, (. : , , , .). , ... . , , .

Spearman :

D ( ). SPSS, Spearman Spearman CorrelateBivariate. Kendall . Spearman :

-36-

19: Spearman. 19, r = .985 (p < .001). 2 , . Spearman Pearson, 18.

18 - . .

-37-

3

-38-

3. , ; ; / . 19.

(regression analysis), . :

() ()

.

. , 30 - . 19 20:

0: :

19 :

19 , , . 20 . , ( ) .

-39-

2: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 11 9 9 9 8 8 8 6 6 5 5 5 5 5 4 4 4 3 3 26 21 24 21 19 13 19 11 23 15 4 18 12 3 11 15 6 13 4 , , , , . Pearson, .

12108642

25

20

15

10

5

20: . () 21 ( ). 21 , - - , .

-40-

() (). 15 . . , Kolmogorov-Smirnov test, ( ) . K-S 0.941 0.457 ( 0.34 0.99, ). 5%, ( ) () . .

. :

Y abX += Y , (b) (). b . , , ( ), ( ). ( ) ( ).

-41-

21: .

21 , . , () ( 22). (residuals), () . , . / 5 ( ), 12 ( ). 22 . , Pearson r 0.739. , ( ) .

R Sq Linear = 0.546

-42-

/ . ( ) (). (simple linear regression). (multiple linear regression). . 3.1. SPSS

: Analyze Regression Linear.

22 & 22

() Dependent ( ) Independent(s). . .

-43-

23: .

24, .

Model Summary

.739a .546 .519 4.882Model1

R R SquareAdjustedR Square

Std. Error ofthe Estimate

Predictors: (Constant), a.

24: (1 ).

,

Pearson r, 0.739, () . (), (R Square) . 0.546, . ~55%. / 55% 23. , 23 55% , .

-44-

, (), /. , : () (causal relationships) , () 55% , . . , , - . , (., ) (.., 55% 45%), 10% .

ANOVAb

487.252 1 487.252 20.444 .000a

405.169 17 23.833892.421 18

RegressionResidualTotal

Model1

Sum ofSquares df Mean Square F Sig.

Predictors: (Constant), a.

Dependent Variable: b.

25: : (2 ). 19 ( 18) () . . (ANOVA) r R2 . 19, F24 20.444,

24 (F) . .

-45-

1 17 25 ( , ), 1). , / .

Coefficientsa

.938 3.229 .290 .7752.224 .492 .739 4.522 .000

(Constant)

Model1

B Std. Error

UnstandardizedCoefficients

Beta

StandardizedCoefficients

t Sig.

Dependent Variable: a.

26: : (3 output SPSS).

20 . ( ). 20 t-test26. ( ). (constant, ), . :

25 , , (). . 26 t-test, F-test .

-46-

0: :

0.938

. , 77.5%, ( 5%), . ; , ( ) . , b . B 20 (2,224). :

0: b : b

t 4.522 5%, . () . ( , F-test ), . b; b ( ) ( ). b 2.224 , 2 .

-47-

3.2. , , . .., / 5 . x = 5, :

Y = x+ => Y = .938x + 2.224 => Y = .938(5) + 2.224 => Y = 6.914, ~ 7

, 7 5 . , 7 . / 0 . = 0, 2 . 2 7 . . , () .

-48-

-49-

4

-50-

4. 4.1.

, , . ( ). , , . . , ( ) . 1: 2000 ( ). . 2000 . 2: & . , & ( , , ) . , ( & ). 3: . 12 .

-51-

. 12 . , ( ), . . 27.

(.. , ). (. 1=, 2=) 28. 29, , 30. 4.2.

:

.

27 () : . 12 ; . () . . . . Stanley Milgram's Experiment (http://www.cba.uri.edu/ Faculty/dellabitta/mr415s98/EthicEtcLinks/Milgram.htm ) 28 (nominal data). 29 (ordinal data). 1= , 2= , 3= . 30 . 1.2 . . http://www.cmh.edu/stats/definitions.asp

-52-

. ( ). t (t-test). ( ) , t-test .

4.2.1 4.2.1.1

, . ( ) .

( , , ) . , . , (). . .

4.2.1.2

. . . , 5 50 , 500

-53-

. , . 500 . , . , / . :

= ( ) /

, , . , t ( Student), t (t-test). p (p-value), (statistical significance level) .

. . . , , . , , . t () . Wilcoxon signed rank .

-54-

4.2.1.3

. , . . (: . ( ) . ). . . : () . . (null hypothesis, 0) . , . , (statistically significant difference) . .

t p (p-value). p (statistical significance level) . () . 5% ( 0.05) 1% ( 0.01) 10% ( 0.10) . . , p .

-55-

t:

1. (

t). 2. ()

. .

3. . 4. t. 5. p. 6. p :

6() p , , 6() p> , .

-56-

4.3. ()

. SPSS p , , .

. , . , p .

(two-sided test), (one-sided test).

, . . 2. , .

4.4. . . 1: 12 8 ( , , .). . . 10 12 17 9,5 7,5 6,5 9,5 11 14 8,5 9,5

-57-

. 1: SPSS . (Graphs Histogram Variables) ( 27). Analyze Nonparametric tests-1 Sample K-S. ( 28). Test Variable List Test Distribution Normal. ( 28 29).

4

3

2

1

0

Freq

uenc

y

Mean =10,5Std. Dev. =3,1447

N =10 27: HOURS

28 & 29:

-58-

. .

One-Sample Kolmogorov-Smirnov Test

1010,5003,1447

,225,225

-,102,711,693

NMeanStd. Deviation

Normal Parametersa,b

AbsolutePositiveNegative

Most ExtremeDifferences

Kolmogorov-Smirnov ZAsymp. Sig. (2-tailed)

Hours

Test distribution is Normal.a.

Calculated from data.b.

30: .

: Asymp. Sig. (2-tailed): p . . p ( 5%), . 0,693> 0,05, t (t-test). 2: (0) . (1).

0: 8 .

1: 8 . 3:

5% ( 0,05). 4: t

: Analyze Compare Means One Sample T Test

-59-

Test Variable(s) (hours SPSS). ( 8) Test Value . ( 31 & 32): One-Sample Statistics

N Mean Std. Deviation Std. Error

Mean Hours 10 10,500 3,1447 ,9944

31 One-Sample Test

Test Value = 8 95% Confidence Interval

of the Difference

t df Sig. (2-tailed) Mean

Difference Lower Upper Hours 2,514 9 ,033 2,5000 ,250 4,750

32 5: p

Hours 10.50, 8. Std. Error Mean . : t=(10,5-8)/0,944=2,514 . Sig. (2-tailed) p 0,033. 6: p 0,033

-60-

, , . . , 8. :

0: 8 . ( )

1: 8 . SPSS 5% p. :

1. p (0,033) 2. (t=2,514). 2. , p p . 2. , p :

1- p .

2. , p p . 2. , p :

1- p .

2 p

0.016. 8

-61-

5%. , 1%.

8, p 2 1-0,016=0,84>0,05. 8 5% ( ).

4.5.

. , 2 ( ) 3 ( ). , , . . 4.5.1.

t . . :

= ( ) /

. . () .

-62-

, t Mann-Whitney, ( ). Mann-Whitney . , SPSS.

4.5.1.1 ( 0-100) (1-, 2-). .

83 1 73 2 75 1 81 2 67 1 49 2 44 1 36 2 28 1 65 2 56 1 56 2 91 1 73 2 39 1 51 2 71 1 44 2 54 1 65 2 38 1 51 2 57 2

(Grades Sex) . . , . Data Select Cases

-63-

33

If condition is satisfied Sex=1.

34

,

.

-64-

(Sex=2). 31, All cases, . : 0: 1: t : Analyze Compare means Independent Samples T Test

35 Grades Test Variable(s) Sex Grouping Variable. Define Groups (1 2 Group 1 Group 2 ).

31 .

-65-

36 Continue OK .

Group Statistics

11 58.73 20.308 6.12312 58.42 13.276 3.833

12

N Mean Std. Deviation

Std. ErrorMean

37

Independent Samples Test

3.068 .094 .044 21 .965 .311 7.093 -14.440 15.061

.043 16.999 .966 .311 7.224 -14.930 15.551

Equal variancesassumedEqual variancesnot assumed

F Sig.

Levene's Test forEquality of Variances

t df Sig. (2-tailed)Mean

DifferenceStd. ErrorDifference Lower Upper

95% ConfidenceInterval of the

Difference

t-test for Equality of Means

38

-66-

Group Statistics (58.73 58.42 ). . 5% . t Sig (2-tailed) 2 p. p . (.965 .966);

. Levene . p Sig . p (.094) 5%, p (.966). .094>.05, .995 .

, . p ( ):

1. p (.996). 2. (t=.005). 2. , (Group 1=) (Group 2=), p , () p . 2. , (Group 1=) (Group 2=,) p :

1 - () p . 2. , (Group 1=) (Group 2=), p () p .

-67-

2. , (Group 1=) (Group 2=), p :

1- () p .

( : ) . 2 p .47. , 5%.

4.5.2. :

. ( ) 0 . : = /

t

(paired samples t-test). . . Wilcoxon signed rank.

: - . . - ( 0-100). :

-68-

-

-

(-)

12 23 -11 34 45 -11 67 73 -6 43 54 -11 81 76 5 54 56 -2 56 66 -10 76 78 -2 65 79 -14 56 63 -7

2 (before

after) SPSS (Diff=before-after) : Transform-Compute. Target variable Numeric expression . . diff 0. : 0: - 1: , - T-Test

Paired Samples Statistics

54,40 10 20,533 6,49361,30 10 17,588 5,562

BeforAfter

Pair1

Mean N Std. DeviationStd. Error

Mean

Paired Samples Correlations

10 ,966 ,000Befor & AfterPair 1N Correlation Sig.

-69-

Paired Samples Test

-6,900 5,782 1,828 -11,036 -2,764 -3,774 9 ,004Befor - AfterPair 1Mean Std. Deviation

Std. ErrorMean Lower Upper

95% ConfidenceInterval of the

Difference

Paired Differences

t df Sig. (2-tailed)

39 , : Analyze Compare Means Paired samples T Test

, Paired variables . ( ).

- (54,4 61,3 ). . Paired Sample Test. Sig (2-tailed) p . p diff. , - diff < 0 ( 2). p 0,002 5% -. 4.6.

. t. , . (non-parametric tests). t, (parametric tests). . 2 Mann Whitney: Analyze Non-Parametric Tests 2 Independent Samples

-70-

Grades test variable list, sex group variable Mann Whitney U test type Wilcoxon signed rank: Analyze Non-Parametric Tests 2 related Samples before after test pair list Wilcoxon test type. SPSS . Wilcoxon signed rank . , , (Hours ) ( ew ) 0 . Wilcoxon signed rank hours new test pair list Wilcoxon test type. new : Transform-Compute new Target Variable 0 Numeric Expression. :

() () () .

. , . , // . (alternative hypothesis-research hypothesis). , .

-71-

5

-72-

5. 5.1.

(Analysis of Variance ANOVA)

. , t. . t-test , , . . t :

:

(3) . , , ( ), (, ) .

t

. t-test (2) . (3) . t (3) . , ( (8) 28 t) : t .

. t , (.. ) . 6 ( 3 ). t 6 .

-73-

( ) (dependent variable), ( ) (independent variables). ( ) (one-way analysis of variance, one-way ANOVA). , . one-way ANOVA 2 t. ANOVA ( t) . . t-test. - ( Kruskal-Wallis). .

, one-way ANOVA, . . 5.2. NOVA

ANOVA, ( ) .

5.2.1 ANOVA ANOVA .

, . ( ) : () , () , ( ) .

-74-

, ( ). , ANOVA ,

= ( ) /

, . F t . p .

5.2.2 Post hoc , . , . post hoc ( a posteriori ) post hoc . post hoc . , :

- LSD (Least Squares Differences). t, . , . - Bonferroni. . - Tukey HSD (Honestly Significant Difference). . ,

-75-

. - Scheffe. . . Tukey .

5.3. ANOVA

ANOVA . , , SPSS ( & ). , , . . post hoc ( ) . . t, , . 5.4. ANOVA

15 PISA (Program for the International Student Assessment32).

32 . http://www.pisa.oecd.org

-76-

33:

1: 469, 474, 478, 465, 459, 489, 478 2: 462, 465, 447, 431, 453, 467, 466 3: 467, 453, 472, 451, 457, 443, 456

SPSS.

34, . one-way ANOV 5% . Analyze General Linear Model Univariate.

40 Dependent Variable scores Fixed Factor(s) school. (: two-way ANOVA, ). Post hoc school Post hoc tests for Scheffe, Tukey. Continue OK .

33 ( ) 34 . 1

-77-

Univariate Analysis of Variance Between-Subjects Factors

777

123

N

41

Tests of Between-Subjects Effects

Dependent Variable:

1308,286a 2 654,143 5,329 ,0154482324,000 1 4482324,000 36512,337 ,000

1308,286 2 654,143 5,329 ,0152209,714 18 122,762

4485842,000 213518,000 20

SourceCorrected ModelInterceptSchoolErrorTotalCorrected Total

Type III Sumof Squares df Mean Square F Sig.

R Squared = ,372 (Adjusted R Squared = ,302)a.

42

Multiple Comparisons

Dependent Variable:

17,29* 5,922 ,024 2,17 32,4016,14* 5,922 ,035 1,03 31,26

-17,29* 5,922 ,024 -32,40 -2,17-1,14 5,922 ,980 -16,26 13,97

-16,14* 5,922 ,035 -31,26 -1,031,14 5,922 ,980 -13,97 16,26

17,29* 5,922 ,031 1,49 33,0816,14* 5,922 ,045 ,35 31,93

-17,29* 5,922 ,031 -33,08 -1,49-1,14 5,922 ,982 -16,93 14,65

-16,14* 5,922 ,045 -31,93 -,351,14 5,922 ,982 -14,65 16,93

(J) 231312231312

(I) 1

2

3

1

2

3

Tukey HSD

Scheffe

MeanDifference

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

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

43

F p F Sig. 5,329 0,015 . 5% ( 1%) . 3

-78-

( 1=473, 2=455,9 3=457) ( 10). post hoc , Tukey Scheffe, Multiple Comparisons. , (I) 2 (J). Tukey o 1 2 p 0,024. 1 2 ( ), t p 0,012. 1 2 PISA 5% ( 1%). 1 3, 2 3. 2 .

- Kruskal Wallis : Analyze Non-Parametric Tests-K Independent Samples pisa test variable list school group variable.

3:

- t-test

Wicoxon signed rank

( )

t-test

Mann-Whitney

( )

Paired t-test

Wicoxon signed rank

( )

ANOVA

Kruskal-Wallis ( one-way)

-79-

2

6

-80-

6. 2 2 (chi square test of independence) (contingency tables). ( ) ( ) . . X2 . : ( ). ( ). . 2 . 2 :

n > 2535 ( 25%) (n > 250), 36 X2.

6.1. 2 ( )37.

35 n250 ( SPSS random sample) Monte Carlo. 37 : / ;[ =1, =2, =3, =4, =5, =6]

-81-

, (chi square test of independence). :

0 : 1 :

2, ( ) ( ). . SPSS : 4:

5:

37 18.5 18.8 18.840 20.0 20.3 39.131 15.5 15.7 54.869 34.5 35.0 89.811 5.5 5.6 95.49 4.5 4.6 100.0

197 98.5 100.03 1.5

200 100.0

Total

Valid

MissingMissingTotal

Frequency Percent Valid PercentCumulative

Percent

, . SPSS Crosstabs : - Menu Analyse Descriptive Statistics Crosstabs.

83 41.5 41.5 41.5 117 58.5 58.5 100.0 200 100.0 100.0

Total

Valid Frequency Percent Valid Percent

Cumulative Percent

-82-

44: SPSS X2 (rows) (columns).

45: SPSS 2

46:

-83-

. . . SPSS . (Analyse - Descriptive Statistics - Crosstabs), Statistics (. ) ( Chi-square)38 .

47 & 48: SPSS 2

:

38 . .

-84-

7:

-85-

* Crosstabulation

24 19 17 17 2 2 8115.2 16.4 12.7 28.4 4.5 3.7 81.08.8 2.6 4.3 -11.4 -2.5 -1.713 21 14 52 9 7 116

21.8 23.6 18.3 40.6 6.5 5.3 116.0-8.8 -2.6 -4.3 11.4 2.5 1.7

37 40 31 69 11 9 19737.0 40.0 31.0 69.0 11.0 9.0 197.0

CountExpected CountResidualCountExpected CountResidualCountExpected Count

Total

Total

49: . , , . . ( ). ( ), . ( 50):

50: SPSS

-86-

2 . 2. . ( 25%). (recode) .

39. ; Pearson Chi-Square . , . 1 () . X2 (Pearson Chi-Square) 564.786, p-value (Significance level) 0.000 5% ( ) , (. http://home.clara.net/sisa/two2hlp.htm, http://www.graphpad.com/ quickcalcs/contingency1.cfm).

39 .

-87-

6.2. SPSS , SPSS . . - . Count ( ) = . Exp.count ( ) = . Residual ( ) = . Row Total ( ) = . Column Total ( ) = . Chi Square Pearson & Likelihood Ratio (2 ). Degrees of Freedom ( ) = -1 -1, (-1)(-1) Significance () = . (>) 0.05 . Linear by Linear association ( ) = () . Minimum Expected Count ( ). Cells (.x%) have expected count less than 5 = 25% X2 -.

-88-

Phi () = . Phi 2, . , . Cramers V = Cramers V () () . >1, Cramers V 0 1. APA Style : 2(5, =200)= 23.159, p

-89-

7

-90-

7.1 ( ). ( ) . .

0: :

. (grades) SPSS : Statistics NonParametric tests 1-Sample K-S.

1: SPSS Kolmogorov-Smirnov

(Normal) , , 97%. .

-91-

2: SPSS Kolmogorov-Smirnov

. / . . : Statistics Descriptive Statistics Frequencies Variables / () statistics.

3: SPSS

-92-

Skewness/Kurtosis, continue OK. :

4: SPSS +/- 2 . ,

ErrorSkewSkew=

-.690/.687 = -1.004, -.185/1.334 = -.1386. +/-2 . - Explore. 7.2 7.2.1 . Test X2 . : () >30, () > 1 () 80% > 5 . Test Mc Nemar. To test . : () (dichotomous) (b) (value labels)

-93-

. Test Mann & Whitney To test . . Test (Sign test) test Wilcoxon. Sign test ( ), to Wilcoxon test . Sign test test Wilcoxon. . T test o: () . . Mann Whitney test. t-test. F (F-test). . T test o: () . . test Wilcoxon. 7.2.2 . . . n ( n = ) k ( k = ). . 2 test . 2 . o: () >1 80% >5.

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. . n ( n = ) k ( k = ). : () (dichotomous) Test Cohran (Q test). . Kruskal & Wallis test ( test). . . Friedman test. . . ANOVA. : () , () . . . . 7.2.3 . Pearson. : . . Spearman. .

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eta. : - test. . Spearman. . Spearman. . 2 test. . 2 test. . 2 test. . 2 test.

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8

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. : http://bcs.whfreeman.com/ips4e/cat_010/applets/CorrelationRegression.html

http://www.stat.vt.edu/~sundar/java/applets/Correlation.html

http://bcs.whfreeman.com/bps3e/content/cat_010/applets/twovarcalcbps.html

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http://davidmlane.com/hyperstat/index.html

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