is to do with multicollinearity, which is investigated by considering the correlation among the independent variables. Tables 4.46 to 4.48 indicate the great majority of the correlations among the independent (i.e. predictor) variables of the study are not above .7, which demonstrates that the multicollinearity assumption is met.

Tables 4.46 to 4.48 also show that only the correlation coefficient between General autonomy and Expert teaching style is close to .3, and the rest of the predictor variables have an insignificant correlation with all autonomy scores. It is therefore, predicted that in the final results of regression, these insignificantly correlated predictor variables are not going to have significant contribution in terms of predicting autonomy. Nevertheless, the regression analysis was continued to observe which of these predictor variables would indeed have any prediction power in terms of different autonomy scores.

Table 4.46

General Autonomy Correlations

General autonomy

Expert

Formal authority

Personal model

Facilitator

Delegator

NLP

Pearson Correlation

General autonomy

1.000

.308

.156

.191

.292

.178

.088

Expert

.308

1.000

.716

.807

.718

.604

.281

Formal authority

.156

.716

1.000

.821

.689

.722

.392

Personal model

.191

.807

.821

1.000

.773

.667

.480

Facilitator

.292

.718

.689

.773

1.000

.769

.454

Delegator

.178

.604

.722

.667

.769

1.000

.452

NLP

.088

.281

.392

.480

.454

.452

1.000

Sig. (1-tailed)

General autonomy

.

.000

.038

.015

.000

.022

.160

Expert

.000

.

.000

.000

.000

.000

.001

Formal authority

.038

.000

.

.000

.000

.000

.000

Personal model

.015

.000

.000

.

.000

.000

.000

Facilitator

.000

.000

.000

.000

.

.000

.000

Delegator

.022

.000

.000

.000

.000

.

.000

NLP

.160

.001

.000

.000

.000

.000

.

N

General autonomy

129

129

129

129

129

129

129

Expert

129

129

129

129

129

129

129

Formal authority

129

129

129

129

129

129

129

Personal model

129

129

129

129

129

129

129

Facilitator

129

129

129

129

129

129

129

Delegator

129

129

129

129

129

129

129

NLP

129

129

129

129

129

129

129

Table 4.47

Curriculum Autonomy Correlations

Curriculum autonomy

Expert

Formal authority

Personal model

Facilitator

Delegator

NLP

Pearson Correlation

Curriculum autonomy

1.000

-.257

-.266

-.259

-.142

-.004

-.018

Expert

-.257

1.000

.716

.807

.718

.604

.287

Formal authority

-.266

.716

1.000

.821

.689

.722

.416

Personal model

-.259

.807

.821

1.000

.773

.667

.511

Facilitator

-.142

.718

.689

.773

1.000

.769

.464

Delegator

-.004

.604

.722

.667

.769

1.000

.439

NLP

-.018

.287

.416

.511

.464

.439

1.000

Sig. (1-tailed)

Curriculum autonomy

.

.002

.001

.002

.054

.480

.419

Expert

.002

.

.000

.000

.000

.000

.000

Formal authority

.001

.000

.

.000

.000

.000

.000

Personal model

.002

.000

.000

.

.000

.000

.000

Facilitator

.054

.000

.000

.000

.

.000

.000

Delegator

.480

.000

.000

.000

.000

.

.000

NLP

.419

.000

.000

.000

.000

.000

.

N

Curriculum autonomy

129

129

129

129

129

129

129

Expert

129

129

129

129

129

129

129

Formal authority

129

129

129

129

129

129

129

Personal model

129

129

129

129

129

129

129

Facilitator

129

129

129

129

129

129

129

Delegator

129

129

129

129

129

129

129

NLP

129

129

129

129

129

129

129

Table 4.48

Total Autonomy Correlations

Total

Autonomy

Expert

Formal authority

Personal model

Facilitator

Delegator

NLP

Pearson Correlation

Total

Autonomy

1.000

.191

.005

.051

.249

.207

.086

Expert

.191

1.000

.716

.807

.718

.604

.287

Formal authority

.005

.716

1.000

.821

.689

.722

.416

Personal model

.051

.807

.821

1.000

.773

.667

.511

Facilitator

.249

.718

.689

.773

1.000

.769

.464

Delegator

.207

.604

.722

.667

.769

1.000

.439

NLP

.086

.287

.416

.511

.464

.439

1.000

Sig. (1-tailed)

Autonomy

.

.015

.476

.281

.002

.009

.165

Expert

.015

.

.000

.000

.000

.000

.000

Formal authority

.476

.000

.

.000

.000

.000

.000

Personal model

.281

.000

.000

.

.000

.000

.000

Facilitator

.002

.000

.000

.000

.

.000

.000

Delegator

.009

.000

.000

.000

.000

.

.000

NLP

.165

.000

.000

.000

.000

.000

.

N

Autonomy

129

129

129

129

129

129

129

Expert

129

129

129

129

129

129

129

Formal authority

129

129

129

129

129

129

129

Personal model

129

129

129

129

129

129

129

Facilitator

129

129

129

129

129

129

129

Delegator

129

129

129

129

129

129

129

NLP

129

129

129

129

129

129

129

4.2.4.2. Assumption of Normality

Another assumption of multiple regression is the normality of the regression standardized residuals, which was checked via checking the Normal Probability Plot of the regression standardized residuals (Figures 4.4, 4.5 & 4.6). As shown in the figures, it can be said that the points have lain in an almost straight diagonal line from bottom left to top right without many deviations; therefore, it is assumed the assumption of normality of the regression standardized residuals is met for all the data.

Figure 4.4. The Normal Probability Plot of the Regression Standardized Residuals Dependent Variable: General Autonomy

Figure 4.5. The Normal Probability Plot of the Regression Standardized Residuals – Dependent Variable: Curriculum Autonomy

Figur

e 4.6. The Normal Probability Plot of the Regression Standardized Residuals Dependent Variable: Total Autonomy

4.2.4.3. Assumption of Homoscedasticity

Figures 4.7 to 4.9 also present scatter plots of the standardized residuals which indicate that there are only a few negligible outliers which have lain outside the rectangular cluster of the data in the center with regard to the large sample size in this study. Moreover, since there is a clear or systematic pattern to the residuals (e.g. curvilinear or higher on one side than the other) with very few deviations from a centralized rectangle, it is assumed that there is no violation of homoscedasticity in all the data for all the autonomy scores and the independent variables.

Figure 4.7. Scatterplot of the Standardized Residuals – Dependent Variable: General Autonomy

Figure 4.8. Scatterplot of the Standardized Residuals – Dependent Variable: Total Autonomy

Figure 4.9. Scatter Plot of the Standardized Residuals-Dependent Variable: Curriculum Autonomy

Tables 4.49 to 4.51 present the descriptive statistics for all the variables, and Tables 4.52 to 4.54 demonstrate what variables are going to be entered into the regression analysis. Since the literature suggested no order for entering the variables in the regression model and there was almost no logic for this issue, the method of regression was chosen to be simultaneous multiple regression analysis for all autonomy scores.

Table 4.49

Descriptive Statistics of General Autonomy, Styles and NLP

Mean

Std. Deviation

N

General autonomy

39.2248

5.24142

129

Expert

3.8117

.53063

129

Formal authority

3.6609

.57158

129

Personal model

3.8556

.64337

129

Facilitator

3.9002

.58887

129

Delegator

3.5530

.53970

129

NLP

143.5504

11.64847

129

Table 4.50

Descriptive Statistics of Curriculum Autonomy, Styles and NLP

Mean

Std. Deviation

N

Curriculum autonomy

16.8915

2.98758

129

Expert

3.8117

.53063

129

Formal authority

3.6609

.57158

129

Personal model

3.8556

.64337

129

Facilitator

3.9002

.58887

129

Delegator

3.5530

.53970

129

NLP

143.5504

11.64847

129

Table 4.51

Descriptive Statistics of Total Autonomy, Styles and NLP

Mean

Std. Deviation

N

Autonomy

56.1163

4.43112

129

Expert

3.8117

.53063

129

Formal authority

3.6609

.57158

129

Personal model

3.8556

.64337

129

Facilitator

3.9002

.58887

129

Delegator

3.5530

.53970

129

NLP

143.5504

11.64847

129

Table 4.52

Variables Entered/Removeda

Model

Variables Entered

Variables Removed

Method

1

NLP, Expert, Delegator, Formal authority, Facilitator, Personal modelb

.

Enter

a. Dependent Variable: General autonomy

b. All requested variables entered.

Table 4.53

Variables Entered/Removeda

Model

Variables Entered

Variables Removed

Method

1

NLP, Expert, Delegator, Formal authority, Facilitator, Personal modelb

.

Enter

a. Dependent Variable: Autonomy

b. All requested variables entered.

Table 4.54

Variables Entered/Removeda

Model

Variables Entered

Variables Removed

Method

1

NLP, Expert, Delegator, Formal authority, Facilitator, Personal modelb

.

Enter

a. Dependent Variable: Curriculum autonomy

b. All requested variables entered.

In Tables 4.55 to 4.57, the value given under the heading R Square indicates how much of the variance in the dependent variable (i.e. General, Curriculum and Total autonomy) is explained by the model (which includes the entered variables). In the case of General autonomy, the value is .139 which, expressed as a percentage, explains 13 percent of the variance in General autonomy. In the case of Total autonomy, the value is .184 which, expressed as a percentage, explains 18 percent of the variance in Total autonomy. Finally, In the case of Curriculum autonomy, the value is .175 which, expressed as a percentage, explains 17 percent of the variance in Curriculum autonomy.

Table 4.55

Model Summaryb (General Autonomy)

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.373a

.139

.097

4.98209

a. Predictors: (Constant), NLP, Expert, Delegator, Formal authority, Facilitator, Personal model

b. Dependent Variable: General autonomy

Table 4.56

Model Summaryb (Total Autonomy)

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.429a

.184

.144

4.10078

a. Predictors: (Constant), NLP, Expert, Delegator, Formal authority, Facilitator, Personal model

b. Dependent Variable: Autonomy

Table 4.57

Model Summaryb (Curriculum Autonomy)

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.418a

.175

.134

2.78016

a. Predictors: (Constant), NLP, Expert, Delegator, Formal authority, Facilitator, Personal model

b. Dependent Variable: Curriculum autonomy

To assess the statistical significance of the above results, it is necessary to look in Tables 4.58 to 4.60. The ANOVA tests the null hypothesis that multiple R in the population equals 0. As the results indicate, the model reaches statistical significance in all autonomy scores; therefore, all the predictor variables together make significant predictive contribution to the models.