Exploratory data analysis

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The analyzes of explorative data provide critical techniques for preparing raw data to be interpreted in a more inferential way. This technique leads to the reduction of dimensionality through the creation of factors and indices. The ISSP (2009) Canadian social survey provides data on various topics such as success in life and tension between different groups of people who use different questions. The paper focuses on reducing variables' dimension through the creation and reliability analysis of weighted factors to advance life and construct a conflict index. Factor Analysis for Getting ahead From the “Total explained Variance” table in the appendix section there the eigenvalues greater than 1 indicates that the getting ahead concept can reduced to five factors. Using the “Rotated Component matrix” in the appendix variables with correlation ≥ 0.600 were included since they indicated strongly correlation. Table 1 below indicates a summary for variables include under each factors: Note variables “Getting ahead: How important is a wealthy family” and “Getting ahead: People have equal chance of getting into university” were include since the correlations were less than 0.600.

1

2

3

4

5

Getting ahead: How imp. is knowing the right people

Getting ahead: Have to be corrupt to get to the top

Getting ahead: How imp. is a person's race

Getting ahead: How imp. is well-educated parents

Getting ahead: How imp. is ambition

Getting ahead: How imp. is political connections

Getting ahead: If from best sec school, have good chance to obtain uni edu

Getting ahead: How imp. is a person's religion

Getting ahead: How imp. a good education yourself

Getting ahead: How imp. is hard work

Getting ahead: How imp. is giving bribes

Getting ahead: Only rich can afford costs of attending uni

Getting ahead: How imp.is being born a man or woman

Factors for getting a head in life as outlined by the above variables include using:

  1. Connections
  2. Corruption
  3. Social constructs
  4. Education background
  5. Self-motivation

Creating the conflict index

A reliability analysis was conducted to determine the conflict items (variables) required to construct the index. In this case, the highest Cronbach’s Alpha =0.780 obtained after deleting the variable “Conflicts: between poor people and rich people”. The Conflict index was computed by adding up the other three variables.

Prepare variables Regression analysis

The conflict index constructed from the above section was used as the dependent variable after assigning it the scale level of measurement. The age of respondent was used as independent variable. Note those who refused responded were assigned as missing values.

Regression Analysis

The ANOVA output indicate test statistic F (1, 408) =5.059, p = 0.025. This information indicates that the model is statistically significant. The regression coefficients for age indicate that the conflict index increases by 0.022 units whenever the age of the respondent increases by a year. The model equation:

conflict index=7.691+0.022 age

Appendix

Factor Analysis outputs:

Total Variance Explained

Component

Initial Eigenvalues

Extraction Sums of Squared Loadings

Rotation Sums of Squared Loadings

Total

% of Variance

Cumulative %

Total

% of Variance

Cumulative %

Total

% of Variance

Cumulative %

1

3.541

23.604

23.604

3.541

23.604

23.604

2.086

13.906

13.906

2

1.934

12.895

36.499

1.934

12.895

36.499

1.921

12.806

26.712

3

1.295

8.632

45.131

1.295

8.632

45.131

1.826

12.173

38.884

4

1.150

7.663

52.794

1.150

7.663

52.794

1.679

11.194

50.079

5

1.075

7.167

59.961

1.075

7.167

59.961

1.482

9.883

59.961

7

.824

5.491

71.776

12

.494

3.295

91.794

13

.433

2.883

94.677

14

.420

2.801

97.479

15

.378

2.521

100.000

Extraction Method: Principal Component Analysis.

Rotated Component Matrixa

 

Component

1

2

3

4

5

Getting ahead: How imp. is a wealthy family

.590

.108

.054

.495

-.140

Getting ahead: How imp. is well-educated parents

.180

.161

.147

.809

.024

Getting ahead: How imp. a good education yourself

.004

-.089

.014

.770

.287

Getting ahead: How imp. is ambition

.046

-.051

.029

.172

.734

Getting ahead: How imp. is hard work

.088

-.003

-.008

.017

.862

Getting ahead: How imp. is knowing the right people

.714

.045

.108

.143

.209

Getting ahead: How imp. is political connections

.771

.089

.122

.100

.149

Getting ahead: How imp. is giving bribes

.636

.171

.275

-.105

-.132

Getting ahead: How imp. is a person's race

.373

.118

.710

-.018

.035

Getting ahead: How imp. is a person's religion

.112

.099

.790

-.024

.009

Getting ahead: How imp.is being born a man or woman

.070

.069

.699

.330

-.004

Getting ahead: Have to be corrupt to get to the top.

.066

.655

.259

-.022

.036

Getting ahead: If from best sec school, have good chance to obtain uni edu.

.045

.742

.106

.045

-.109

Getting ahead: Only rich can afford costs of attending uni.

.147

.778

.038

-.004

.026

Getting ahead: Ppl have equal chances to enter university.

-.044

-.470

.037

-.055

.015

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 6 iterations.

Reliability Analysis: Indexing output

Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total Correlation

Squared Multiple Correlation

Cronbach's Alpha if Item Deleted

Conflicts: between poor people and rich people

8.77

9.328

.606

.418

.780

Conflicts: between working class and middle class.

8.55

9.991

.640

.450

.773

Conflicts: between management and workers.

9.04

8.706

.682

.496

.744

Conflicts: btwn ppl at top of society and ppl at bottom.

8.99

7.467

.655

.472

.769

Regression output:

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.111a

.012

.010

3.06540

a. Predictors: (Constant), R: Age

ANOVAa

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

47.534

1

47.534

5.059

.025b

Residual

3833.844

408

9.397

Total

3881.378

409

a. Dependent Variable: Conflict index

b. Predictors: (Constant), R: Age

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

7.691

.513

14.998

.000

R: Age

.022

.010

.111

2.249

.025

a. Dependent Variable: Conflict index

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