Demographic Information of the Research Participants

This analysis is provide the information of 150 participants regarding their gender, age, educational background, occupation and family system.

Gender

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

male

75

50.0

50.0

50.0

female

75

50.0

50.0

100.0

Total

150

100.0

100.0

Age_group

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

11-20

15

10.0

10.0

10.0

21-30

58

38.7

38.7

48.7

31-40

59

39.3

39.3

88.0

41-50

18

12.0

12.0

100.0

Total

150

100.0

100.0

Educational_background

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

below metric

2

1.3

1.3

1.3

metric

13

8.7

8.7

10.0

intermediate

12

8.0

8.0

18.0

bachelor

68

45.3

45.3

63.3

master

50

33.3

33.3

96.7

master above

5

3.3

3.3

100.0

Total

150

100.0

100.0

Occupation

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

unemployed

80

53.3

53.3

53.3

teacher

24

16.0

16.0

69.3

engineer

2

1.3

1.3

70.7

doctor

5

3.3

3.3

74.0

other

39

26.0

26.0

100.0

Total

150

100.0

100.0

Family_system

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

nuclear

77

51.3

51.3

51.3

joint

73

48.7

48.7

100.0

Total

150

100.0

100.0

Bar charts of Demographic Data

Mean and Standard Deviation

Statistics

Gender

Age_group

Educational_background

Occupation

Family_system

N

Valid

150

150

150

150

150

Missing

0

0

0

0

0

Mean

1.50

2.53

4.11

2.33

1.49

Std. Deviation

.502

.833

1.004

1.713

.501

Analysis of Relationship between Dependent and Independent variation

Correlations

resilience

Narcissism_

authority

self-sufficiency

superiority

Exhibitionism

exploitativeness

vanity

entitlement

Resilience

Pearson Correlation

1

-.044

-.073

.037

-.014

-.119

.014

.039

.073

Sig. (2-tailed)

.589

.374

.651

.865

.147

.868

.632

.377

N

150

150

150

150

150

150

150

150

150

Narcissism_

Pearson Correlation

-.044

1

.459

.354

.464

.493

.381

.231

.428

Sig. (2-tailed)

.589

.000

.000

.000

.000

.000

.004

.000

N

150

150

150

150

150

150

150

150

150

Authority

Pearson Correlation

-.073

.459

1

-.102

.188

-.044

.045

.102

.024

Sig. (2-tailed)

.374

.000

.213

.021

.597

.581

.214

.767

N

150

150

150

150

150

150

150

150

150

self_sufficiency

Pearson Correlation

.037

.354

-.102

1

.091

.015

.014

-.004

.069

Sig. (2-tailed)

.651

.000

.213

.271

.859

.862

.963

.400

N

150

150

150

150

150

150

150

150

150

Superiority

Pearson Correlation

-.014

.464

.188

.091

1

.006

.076

.072

.040

Sig. (2-tailed)

.865

.000

.021

.271

.946

.352

.383

.627

N

150

150

150

150

150

150

150

150

150

Exhibitionism

Pearson Correlation

-.119

.493

-.044

.015

.006

1

-.009

-.036

.066

Sig. (2-tailed)

.147

.000

.597

.859

.946

.912

.659

.423

N

150

150

150

150

150

150

150

150

150

Exploitativeness

Pearson Correlation

.014

.381

.045

.014

.076

-.009

1

-.037

.092

Sig. (2-tailed)

.868

.000

.581

.862

.352

.912

.653

.263

N

150

150

150

150

150

150

150

150

150

Vanity

Pearson Correlation

.039

.231

.102

-.004

.072

-.036

-.037

1

-.031

Sig. (2-tailed)

.632

.004

.214

.963

.383

.659

.653

.708

N

150

150

150

150

150

150

150

150

150

Entitlement

Pearson Correlation

.073

.428

.024

.069

.040

.066

.092

-.031

1

Sig. (2-tailed)

.377

.000

.767

.400

.627

.423

.263

.708

N

150

150

150

150

150

150

150

150

150

age_groups

Pearson Correlation

.264

-.108

-.079

.042

-.175

-.128

.004

.024

.063

Sig. (2-tailed)

.001

.190

.336

.611

.032

.118

.963

.768

.444

N

150

150

150

150

150

150

150

150

150

Interpretation of Correlation Analysis of all Independent and Dependent Variables

According to the correlation test the relationship between independent variable i.e, age groups and all dependent variables are interpreted as follows:

• The independent variable (age groups) has a positive and mild relationship with resilience (r=.264).

• The independent variable (age groups) has a mild negative relationship with narcissism (r=-.108).

• The independent variable (age groups) has a mild negative relationship with authority (r=-.079).

• The independent variable (age groups) has a low positive relationship with self-sufficiency (r=.042).

• The independent variable (age groups) has a mild negative relationship with superiority (r=-.175).

• The independent variable (age groups) has a mild negative relationship with exhibitionism (r=–.128).

• The independent variable (age groups) has almost no relationship with exploitativeness (r=.004).

• The independent variable (age groups) has a very low positive relationship with vanity (r=.024).

• The independent variable (age groups) has a low positive relationship with entitlement (r=.063).

3.2 Analysis of variance of the impact of Independent variable on Dependent variable (Regression Model)

Regression analysis is carried out for estimating the relationship between dependent variable and predictor or predictors. It helps us to understand how the value of dependent variable changes when the independent variables are varied, while the other independent variables are held fixed. This model is most commonly used for forecasting and prediction about the relation between dependent and independent variable and on the basis of t value we accept or reject hypothesis.

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

R Square Change

F Change

df1

df2

Sig. F Change

1

.264a

.069

.063

14.26570

.069

11.053

1

148

.001

a. Predictors: (Constant), age_groups

ANOVAa

Model

Sum of Squares

Df

Mean Square

F

Sig.

1

Regression

2249.299

1

2249.299

11.053

.001b

Residual

30119.521

148

203.510

Total

32368.820

149

a. Dependent Variable: resilience

b. Predictors: (Constant), age_groups

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

95.0% Confidence Interval for B

B

Std. Error

Beta

Lower Bound

Upper Bound

1

(Constant)

75.715

2.565

29.522

.000

70.647

80.783

age_groups

1.393

.419

.264

3.325

.001

.565

2.221

a. Dependent Variable: resilience

The conclusion from the above regression analysis shows that there is a positive and mild relationship (R=.264) between predictor age group and dependent variable resilience, R square value shows that 6.90% variability or change in resilience is explained by independent variable age group, the value of adjusted R squared (.063) shows that there is inconsiderable variation which in succession tells us that the results can be generalized beyond the sample to the population. In Analysis of variance (ANOVA) table, the F value (11.053) and the value of P i.e, .001 which is less than 95% (.05) level of significance reveals that the overall fitness of the model is logically good. In Coefficient table (Beta=.264, t=3.325, p=0.001) which reveals that pragmatic effect of predictor on outcome (dependent variable) that’s why this hypothesis is accepted.

Analysis of Variance between Age groups and Narcissism

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

R Square Change

F Change

df1

df2

Sig. F Change

1

.108a

.012

.005

.09660

.012

1.732

1

148

.190

a. Predictors: (Constant), age_groups

ANOVAa

Model

Sum of Squares

Df

Mean Square

F

Sig.

1

Regression

.016

1

.016

1.732

.190b

Residual

1.381

148

.009

Total

1.397

149

a. Dependent Variable: Narcissism_

b. Predictors: (Constant), age_groups

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

T

Sig.

95.0% Confidence Interval for B

B

Std. Error

Beta

Lower Bound

Upper Bound

1

(Constant)

1.525

.017

87.825

.000

1.491

1.560

age_groups

-.004

.003

-.108

-1.316

.190

-.009

.002

a. Dependent Variable: Narcissism_

The conclusion we derive from the above Regression analysis table that there is a mild positive relationship (R=.108) between independent variable age group and dependent variable narcissism, R square value (.012) shows that 1.20% change in narcissism is explained by independent variable age group, the Adjusted R square value (.005) shows that there is almost no variation. In Analysis of variance (ANOVA) table, the F value (1.732) and the value of P i.e, .190 which is greater than 95% (.05) level of significance reveals that the overall fitness of the model is logically not good. In Coefficient table the Beta value (-.108) which is less than 0 indicates that for every 1-unit increase in the independent variable the dependent variable or outcome will be decreased, the value of t (-1.316) and p (.190) is greater than level of significance so we accept our null hypothesis.

Analysis of Variance between age groups and authority

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

R Square Change

F Change

df1

df2

Sig. F Change

1

.079a

.006

.000

.20065

.006

.931

1

148

.336

a. Predictors: (Constant), age_groups

ANOVAa

Model

Sum of Squares

Df

Mean Square

F

Sig.

1

Regression

.037

1

.037

.931

.336b

Residual

5.959

148

.040

Total

5.996

149

a. Dependent Variable: authority

b. Predictors: (Constant), age_groups

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

95.0% Confidence Interval for B

B

Std. Error

Beta

Lower Bound

Upper Bound

1

(Constant)

1.536

.036

42.579

.000

1.465

1.607

age_groups

-.006

.006

-.079

-.965

.336

-.017

.006

a. Dependent Variable: authority

The conclusion we derive from the above Regression analysis table that there is a low positive relationship (R=.079) between independent variable age group and dependent variable authority, R square value (.006) shows that .06% change in authority is explained by independent variable age group, the Adjusted R square value (.000) shows that there is no variation. In Analysis of variance (ANOVA) table, the F value (.931) and the value of P i.e, .336 which is greater than 95% (.05) level of significance reveals that the overall fitness of the model is logically not good. In Coefficient table the Beta value (-.079) which is less than 0 indicates that for every 1-unit increase in the independent variable the dependent variable or outcome will be decreased, the value of t (-.965) and p (.336) is greater than significant value so the null hypothesis become accepted.

Analysis of Variance between age groups and Self-sufficiency

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

R Square Change

F Change

df1

df2

Sig. F Change

1

.042a

.002

-.005

.21729

.002

.259

1

148

.611

a. Predictors: (Constant), age_groups

ANOVAa

Model

Sum of Squares

Df

Mean Square

F

Sig.

1

Regression

.012

1

.012

.259

.611b

Residual

6.988

148

.047

Total

7.000

149

a. Dependent Variable: self_sufficiency

b. Predictors: (Constant), age_groups

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

95.0% Confidence Interval for B

B

Std. Error

Beta

Lower Bound

Upper Bound

1

(Constant)

1.449

.039

37.091

.000

1.372

1.526

age_groups

.003

.006

.042

.509

.611

-.009

.016

a. Dependent Variable: self_sufficiency

The conclusion we derive from the above Regression analysis table that there is a low positive relationship (R=.042) between independent variable age group and dependent variable self-sufficiency, R square value (.002) shows that .02% change in authority is explained by independent variable age group, the Adjusted R square value (-.005) shows that there is no variation. In Analysis of variance (ANOVA) table, the F value (.259) and the value of P i.e, .611 which is greater than 95% (.05) level of significance reveals that the overall fitness of the model is logically not good. In Coefficient table the Beta value (.042) which is close to 0 indicates that for every 1-unit increase in the independent variable the dependent variable or outcome will be decreased, the value of t (.509) and p (.661) is greater than the significance value so the null hypothesis become accepted.

Analysis of Variance between age groups and Superiority

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

R Square Change

F Change

df1

df2

Sig. F Change

1

.175a

.031

.024

.22980

.031

4.689

1

148

.032

a. Predictors: (Constant), age_groups

ANOVAa

Model

Sum of Squares

Df

Mean Square

F

Sig.

1

Regression

.248

1

.248

4.689

.032b

Residual

7.815

148

.053

Total

8.063

149

a. Dependent Variable: superiority

b. Predictors: (Constant), age_groups

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

T

Sig.

95.0% Confidence Interval for B

B

Std. Error

Beta

Lower Bound

Upper Bound

1

(Constant)

1.602

.041

38.786

.000

1.521

1.684

age_groups

-.015

.007

-.175

-2.165

.032

-.028

-.001

a. Dependent Variable: superiority

The conclusion we derive from the above Regression analysis table that there is a mild positive relationship (R=.175) between independent variable age group and dependent variable superiority, R square value (.031) shows that 3.10% change in superiority is explained by independent variable age group, the Adjusted R square value (.024) shows that there is almost no variation. In Analysis of variance (ANOVA) table, the F value (4.689) and the value of P i.e, .032 which is less than 95% (.05) level of significance reveals that the overall fitness of the model is logically good. In Coefficient table the Beta value (-.175) which is less than 0 indicates that for every 1-unit increase in the independent variable the dependent variable or outcome will be decreased, the value of t (-2.165) and p (.032) indicates that this hypothesis become accepted.

Analysis of Variance between age groups and Exhibitionism

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

R Square Change

F Change

df1

df2

Sig. F Change

1

.128a

.016

.010

.27149

.016

2.468

1

148

.118

a. Predictors: (Constant), age_groups

ANOVAa

Model

Sum of Squares

Df

Mean Square

F

Sig.

1

Regression

.182

1

.182

2.468

.118b

Residual

10.909

148

.074

Total

11.091

149

a. Dependent Variable: exhibitionism

b. Predictors: (Constant), age_groups

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

T

Sig.

95.0% Confidence Interval for B

B

Std. Error

Beta

Lower Bound

Upper Bound

1

(Constant)

1.565

.049

32.073

.000

1.469

1.662

age_groups

-.013

.008

-.128

-1.571

.118

-.028

.003

a. Dependent Variable: exhibitionism

The conclusion we derive from the above Regression analysis table that there is a mild positive relation (R=.128) between independent variable age group and dependent variable exhibitionism, R square value (.016) shows that 1.60% change in authority is explained by independent variable age exhibitionism, the Adjusted R square value (.010) shows that there is almost no variation. In Analysis of variance (ANOVA) table, the F value (2.468) and the value of P i.e, .118 which is greater than 95% (.05) level of significance reveals that the overall fitness of the model is logically not good. In Coefficient table the Beta value (-.128) which is less than 0 indicates that for every 1-unit increase in the independent variable the dependent variable or outcome will be decreased, the value of t (-.128) and p (.118) indicates that the null hypothesis becomes accepted.

Analysis of Variance between age groups and Exploitativeness

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

R Square Change

F Change

df1

df2

Sig. F Change

1

.004a

.000

-.007

.24591

.000

.002

1

148

.963

a. Predictors: (Constant), age_groups

ANOVAa

Model

Sum of Squares

Df

Mean Square

F

Sig.

1

Regression

.000

1

.000

.002

.963b

Residual

8.949

148

.060

Total

8.950

149

a. Dependent Variable: exploitativeness

b. Predictors: (Constant), age_groups

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

95.0% Confidence Interval for B

B

Std. Error

Beta

Lower Bound

Upper Bound

1

(Constant)

1.554

.044

35.154

.000

1.467

1.642

age_groups

.000

.007

.004

.047

.963

-.014

.015

a. Dependent Variable: exploitativeness

The conclusion we derive from the above Regression analysis table that there is a almost no relationship (R=.004) between independent variable age group and dependent variable exploitativeness, R square value (.000) shows that 0% change in exploitativeness is explained by independent variable age group, the Adjusted R square value (-.007) shows that there is almost no variation. In Analysis of variance (ANOVA) table, the F value (.002) and the value of P i.e, .963 which is greater than 95% (.05) level of significance reveals that the overall fitness of the model is logically not good. In Coefficient table the Beta value (.004) which is almost 0 indicates, the value of t (.047) and p (.963) p indicates that the null hypothesis becomes accepted.

Analysis of Variance between age groups and vanity

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

R Square Change

F Change

df1

df2

Sig. F Change

1

.024a

.001

-.006

.27025

.001

.087

1

148

.768

a. Predictors: (Constant), age_groups

ANOVAa

Model

Sum of Squares

Df

Mean Square

F

Sig.

1

Regression

.006

1

.006

.087

.768b

Residual

10.809

148

.073

Total

10.816

149

a. Dependent Variable: vanity

b. Predictors: (Constant), age_groups

Model

Unstandardized Coefficients

Standardized Coefficients

T

Sig.

95.0% Confidence Interval for B

B

Std. Error

Beta

Lower Bound

Upper Bound

1

(Constant)

1.447

.049

29.786

.000

1.351

1.543

age_groups

.002

.008

.024

.296

.768

-.013

.018

a. Dependent Variable: vanity

The conclusion we derive from the above Regression analysis table that there is a low positive relationship (R=.024) between independent variable age group and dependent variable vanity, R square value (.001) shows that .1% change in vanity is explained by independent variable age group, the Adjusted R square value (-.006) shows that there is almost no variation. In Analysis of variance (ANOVA) table, the F value (.087) and the value of P i.e, .786 which is greater than 95% (.05) level of significance reveals that the overall fitness of the model is logically not good. In Coefficient table the Beta value (.024) which is almost 0, the value of t (.296) and p (.786) indicates that the null hypothesis becomes accepted.

Analysis of Variance between age groups and E

x

Hi!

I'm Delia!

Would you like to get a custom essay? How about receiving a customized one?

Check it out