Chapter-5
Analysis & Interpretation
5.1 Types of Analyses
The data gathered only produces meaningful insights when analysed systematically. The analysis of the test data was made using descriptive, inferential and associative analysis technique.
Measures such as mean and standard deviation are forms of descriptive analysis used to describe the sample data-matrix. The descriptive measures were typically used early in the analysis process and they laid the foundation for subsequent analyses.
The process of generalising the results obtained from the sample to be applicable for the target population that it represents, is termed as inferential analysis. Such statistical procedures allow drawing conclusions about the population based on the information contained in the data-matrix provided by the sample. Inferential statistics includes hypotheses testing and estimating the true population values based on sample information.
The statistical technique used to determine systematic relationship among the variables in research problems is termed as associative analysis. It investigates ‘if’ and ‘how’ two or more variables are related. Depending upon the statistics used the strength of the association and/or the direction of the association between the two variables can be ascertained.
5.2 Hypotheses of the Study:
After reviewing relevant literature (papers, abstracts and relevant theories) the research problem was stated as Exploration of the Indian Mindset beyond Indian Frontiers and 5 hypotheses were formulated. The present study intended to test the following hypotheses and the results ensuing from the research are also detailed here.
The present study intended to test the following hypotheses:
5.2.1 Hypotheses
H01 - Expatriate Indians manifest low discrepancy in their beliefs, preferences and action-orientations.
HA1 - Expatriate Indians manifest high discrepancy in their beliefs, preferences and action-orientations.
H02 – Expatriate Indians manifest low sensitivity to contextual cues: judging people and time, sensing other’s mindset, watching for opportunities.
HA2 – Expatriate Indians manifest high sensitivity to contextual cues: judging people and time, sensing other’s mindset, watching for opportunities.
H03 - Discrepancy and context sensitivity do not affect the ways expatriate Indians behave.
HA3 - Discrepancy and context sensitivity jointly affect the ways expatriate Indians behave.
H04 - While enabling contexts induce them to behave in negative ways, the disabling contexts make them behave in positive ways.
HA4 - While enabling contexts induce them to behave in positive ways, the disabling contexts make them behave in negative ways.
H05 - In case a situation changes from disabling to enabling, expatriate Indians shift from being positive to negative in their behaviour.
HA5 - In case a situation changes from disabling to enabling, expatriate Indians shift from being negative to positive in their behaviour.
5.3 Data Analysis Results:
Factor Analysis is a general term used for a class of procedures, primarily employed for data reduction and summarization. To identify a new, smaller set of variables to replace the original set of correlated variables in subsequent multivariate analysis, FactorAnalysis was employed.
5.3.1 FactorAnalysis of Factor 1.0
Duplicity in Mindset
Table 5.1 KMO and Bartlett's Test /Kaiser-Meyer-Olkin Measure of Sampling Adequacy. / 0.609 /
Bartlett's Test of Sphericity / Approx. Chi-Square / 1.252 /
Df / 153 /
Sig. / 0.000
In this table the "measure of sampling adequacy" (MSA) test has been given, this has become the standard test procedure for the factor analysis. KMO value is 0.609 which is mediocre in order to proceed with a factor analysis. This test provides a minimum standard which should be passed before a factor analysis (or a principal components analysis) is conducted. In the case of the present research data, the test statistic is satisfactory (1.252), and accordingly the null hypothesis may be rejected (Sig. = .000) at 153 degree of freedom.
Table 5.2 Communalities
Communalities / Initial / Extraction /People talk ideals, but behave in selfish manners / 1.000 / 0.577 /
People believe that hard work pays, but do not exert enough / 1.000 / 0.464 /
People genuinely care for others, but don’t behave accordingly / 1.000 / 0.603 /
People don’t like to be supervised, but work hard only when they are supervised / 1.000 / 0.430 /
People run after power and position, although they want peace of mind / 1.000 / 0.673 /
People work hard to acquire material wealth and also remain concerned for spiritual growth / 1.000 / 0.724 /
Calm and composed people flare up at the slightest provocation / 1.000 / 0.695 /
People, who offer pooja and prayers regularly, also indulge in unethical practices / 1.000 / 0.764 /
People make promises, but give excuses for not keeping them / 1.000 / 0.676 /
People perform religious rituals but also believe that spirituality is beyond religious rituals / 1.000 / 0.775 /
People favour their friends and use them for personal gains also / 1.000 / 0.754 /
People dislike corrupt persons, but remain close to them for personal gains / 1.000 / 0.725 /
People believe in science but are superstitious in behaviour / 1.000 / 0.750 /
People, who live in metropolitan cities, remain rooted in their native culture / 1.000 / 0.733 /
People over react emotionally, but also calculate their gains and losses carefully / 1.000 / 0.694 /
People believe in destiny but struggle hard to succeed in life / 1.000 / 0.785 /
People want to remain honest, but bribe to get done what they want / 1.000 / 0.601 /
People avoid working hard for others, but work diligently for themselves / 1.000 / 0.520 /
Extraction Method: Principal Component Analysis.
Extraction- The values in this column indicate the proportion of each variable's variance that can be explained by the retained factors. Variables with high values are well represented in the common factor space, while variables with low values are not so well represented.
Initial communalities are estimates of the variance in each variable accounted for by all components or factors.
Extraction communalities are estimates of the variance in each variable accounted for by the factors (or components) in the factor solution. Small values are indicative of variables that do not fit well with the factor solution and should possibly be dropped from the analysis.
Table-5.3 Total Variance Explained /Compo
nents / 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 / 3.027 / 16.814 / 16.814 / 3.027 / 16.814 / 16.814 / 2.023 / 11.240 / 11.240 /
2 / 2.307 / 12.814 / 29.629 / 2.307 / 12.814 / 29.629 / 1.944 / 10.799 / 22.039 /
3 / 1.676 / 9.309 / 38.937 / 1.676 / 9.309 / 38.937 / 1.919 / 10.659 / 32.698 /
4 / 1.495 / 8.306 / 47.243 / 1.495 / 8.306 / 47.243 / 1.764 / 9.800 / 42.498 /
5 / 1.305 / 7.250 / 54.493 / 1.305 / 7.250 / 54.493 / 1.500 / 8.335 / 50.832 /
6 / 1.078 / 5.992 / 60.484 / 1.078 / 5.992 / 60.484 / 1.488 / 8.264 / 59.096 /
7 / 1.055 / 5.861 / 66.346 / 1.055 / 5.861 / 66.346 / 1.305 / 7.249 / 66.346 /
8 / .870 / 4.834 / 71.179 /
9 / .852 / 4.733 / 75.912 /
10 / .772 / 4.291 / 80.203 /
11 / .673 / 3.742 / 83.945 /
12 / .575 / 3.194 / 87.139 /
13 / .522 / 2.901 / 90.040 /
14 / .429 / 2.382 / 92.422 /
15 / .415 / 2.307 / 94.729 /
16 / .374 / 2.079 / 96.808 /
17 / .346 / 1.921 / 98.729 /
18 / .229 / 1.271 / 100.000
This table contains the information regarding the 18 possible factors and their relative explanatory power as expressed by their Eigen values in addition to assessing the importance of each component. The Eigen values assist in selecting the number of factors. In this research study the latent root criterion, seven components were retained.
a. Factor- The initial number of factors is the same as the number of variables used in the factor analysis. However, not all 18 factors will be retained. In this example, only the first 7 factors will be retained.
b.Initial Eigenvalues- Eigenvalues are the variances of the factors. Because the factor analysis was conducted on the correlation matrix, the variables are standardized, which means that the each variable has a variance of 1, and the total variance is equal to the number of variables used in the analysis, in this case, 18.
c.Total- This column contains the eigenvalues. The first factor will always account for the most variance (and hence have the highest eigenvalue), and the next factor will account for as much of the left over variance as it can, and so on. Hence, each successive factor will account for less and less variance.
d.% of Variance- This column contains the percent of total variance accounted for by each factor.
e.Cumulative %- This column contains the cumulative percentage of variance accounted for by the current and all preceding factors. The third row shows a value of 66.346 % which means that the first three factors together account for 66.346 % of the total variance.
f.Extraction Sums of Squared Loadings- The number of rows in this panel of the table correspond to the number of factors retained. This example indicates that seven factors be retained, so there are seven rows, one for each retained factor. The values in this panel of the table are calculated in the same way as the values in the left panel, except that here the values are based on the common variance. The values in this panel of the table will always be lower than the values in the left panel of the table, because they are based on the common variance, which is always smaller than the total variance.
g.Rotation Sums of Squared Loadings- The values in this panel of the table represent the distribution of the variance after the varimax rotation.Varimax rotation tries to maximize the variance of each of the factors, so the total amount of variance accounted for is redistributed over the seven extracted component.
Table 5.4 Case Processing Summary
/ No. of Respondents / % /Cases / Valid / 314 / 99.7 /
Excluded* / 1 / 0.3 /
Total / 315 / 100 /
*List-wise deletion based on all variables in the procedure.
This table shows that validity of the data is 99.7% which is quite satisfactory as 314 respondents were used in the Cronbach's Alpha.
Table 5.5 Reliability Statistics /Cronbach's Alpha / No. of Items /
0.656 / 14
The Cronbach's alpha value is0.656, which indicates a medium level of internal consistency of the scale for this specific sample.
5.3.2 FactorAnalysis of Factor 2.1
Context Sensitivity: Judging People and Time
Table 5.6 KMO and Bartlett's Test /Kaiser-Meyer-Olkin Measure of Sampling Adequacy. / 0.480 /
Bartlett's Test of Sphericity / Approx. Chi-Square / 32.475 /
Df / 10 /
Sig. / 0.000
KMO value is 0.480 which is minimum in order to proceed with a factor analysis. In the case of the present research data, the test statistic is satisfactory (32.475), and accordingly the null hypothesis may be rejected (Sig. = .000) at 10 degree of freedom.
Table 5.7 Communalities
Communalities / Initial / Extraction /People know when to remain silent and when to say what / 1.000 / 0.604 /
People know when to delay a decision or action and when to rush into it / 1.000 / 0.421 /
People distinguish genuine friends from opportunists / 1.000 / 0.676 /
People are alert to opportunities and work timely to utilize them / 1.000 / 0.459 /
People have ability to figure out what others expect, and behave accordingly / 1.000 / 0.271 /
The variables with high values are well represented in the common factor space. Small values indicate variables that do not fit well with the factor solution, and should possibly be dropped from the analysis.
Table 5.8 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 / 1.286 / 25.723 / 25.723 / 1.286 / 25.723 / 25.723 / 1.280 / 25.591 / 25.591 /
2 / 1.145 / 22.897 / 48.620 / 1.145 / 22.897 / 48.620 / 1.151 / 23.029 / 48.620 /
3 / .970 / 19.404 / 68.024 /
4 / .891 / 17.815 / 85.839 /
5 / .708 / 14.161 / 100.000
This table shows that the initial number of factors is the same as the number of variables used in the factor analysis. However, not all 5 factors will be retained.
In this case, only the first 2 factors will be retained.
FactorAnalysis of Factor 2.2
Context Sensitivity: Sensing Other’s Mindset
Table 5.9 KMO and Bartlett's Test /Kaiser-Meyer-Olkin Measure of Sampling Adequacy. / 0.521 /
Bartlett's Test of Sphericity / Approx. Chi-Square / 43.369 /
Df / 6 /
Sig. / 0.000
KMO value is 0.521which is mediocre in order to proceed with a factor analysis. In the case of the present research data, the test statistic is satisfactory (43.369), and accordingly the null hypothesis may be rejected (Sig. = .000) at 6 degree of freedom.
/ Table 5.10 Communalities // Initial / Extraction /
/ People sense what others mean and intend / 1.000 / 0.618 /
/ People are concerned about what others think of them / 1.000 / 0.599 /
/ People sense what future holds for them at the place they work / 1.000 / 0.599 /
/ People intuitively know whom to trust and whom to distrust / 1.000 / 0.610 /
Extraction Method: Principal Component Analysis.
The variables with high values are well represented in the common factor space. Small values indicate variables that do not fit well with the factor solution, and should possibly be dropped from the analysis.
Table 5.11 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 / 1.415 / 35.381 / 35.381 / 1.415 / 35.381 / 35.381 / 1.216 / 30.388 / 30.388
2 / 1.010 / 25.261 / 60.641 / 1.010 / 25.261 / 60.641 / 1.210 / 30.253 / 60.641
3 / .895 / 22.380 / 83.022
4 / .679 / 16.978 / 100.00
This table shows that the initial number of factors is the same as the number of
variables used in the factor analysis. However, not all 4 factors will be retained.
In this case, only the first 2 factors will be retained.
FactorAnalysis of Factor 2.3