**Logical Statistical Techniques **

In this assignment, you will have the opportunity to show that you are able to combine some statisticaltechniques in a logical way in order to analyse data and answer specific research questions related a realcase scenario. You will find an SPSS data file called ‘Asia Banks Survey.sav’. The ‘Variable View’ of the SPSSdata will give you an idea of what the variables in that data set represent. You do not have to understandthe details of the various measures in order to complete this assignment successfully. You can (and mayneed to) create new variables based on this data, selectively analyse just some sub-sets of it and/ortransform the data into new values to answer the assignment questions.

In order to pass this assignment you will need to show that you understand the principles and practice ofusing statistical techniques find evidence and make logical conclusions on quantitative based analysis. Todo this you need to show that you are competent in choosing and treating appropriate data, applyingestablished statistical techniques, performing the analysis and reporting your results. Some of thequestions can be answered by basic statistical tests, others may need, for example, multivariateapproaches. Some questions can be answered using several different methods and you will not bepenalised for choosing more complex analyses – we are looking for understanding and basic competenceat threshold level for passing. As always at this level, justification of what you have done is very important.You are not expected to provide a reference list for this assessment, apart from any citations you maywish to make in justification of specific aspects of your chosen analytical methods. This is only done inexceptional circumstances (general appreciation of statistical techniques can be assumed in the readerand it would not be normal to reference techniques from text books for instance).

Background case**
**A major shareholder of four bank corporations in Asia has decided to develop the leadership skills ofbranch managers in the region. For this, after a competitive process they have selected the companyGlobal Exec (Global Executive Training Ltd*) to develop a training programme in leadership throughoutthe different markets in Asia where the four banks operate.

Global Exec is a British-based consulting company which has developed a very good reputation on thequality of their OrganisationalBehaviour and Human Resource development programmes and theirLeadership Training programme is particularly well-known for its high level of efficiency and effectiveness.

Over the years the company has developed a standardised leadership development programme based onhighly interactive activities based on social multimedia technologies, team development workshops andcollaboration projects.

However, this is the first contract Global Exec has won a contract for delivering their training program in such a large regional scope involving different countries in Asia. They want to know if their standardized leadership training programme will have to be adapted or not for an effective delivery in the differentcultures, values and management attitudes predominant in the regions the banks operate.

In order to have a better understanding of the similarities and differences characteristic of the banks andregions where they will deliver their training programme, Global Exec has conducted a major survey withbank branch managers from the four banks. More specifically, the data was collected from a sample ofbank branch managers mainly composed by respondents of three different races: Malay, Chinese, andIndian. Most of the banks have branches in five different regions (Northern, Central, South, West Coast,and East Asia). The four different Banks are identified as Nantong Bank* (Bank 1), Jaipur Bank* (Bank 2),Ampang Bank* (Bank 3) and Union Bank* (Bank 4).

Assignment activity As a member of the Global Exec team of analysts, you are required to conduct somestatistical analysis of the data and write a report that provides evidence and conclusions that will supportthe company’s decision on the extent to which they can preserve standardised formats or makeadjustments in the training programme they will deliver to the bank across different regions. Importantissues concerning Global Exec’s strategic decision are listed below. Analyse them and explain your results.

* DISCLAIMER: This is a fictitious company’s name used in this case. Any association with a name of a real company is a merecoincidence.

1. Are there similarities or differences between races (variable RC) in terms of Interpersonal Trust(variables IPT1-IPT5) and Age of branch managers (variable AGE)?

Clearly state the related hypotheses and conduct the quantitative analysis to test the hypotheses. Explainyour conclusions on the hypotheses based on the results obtained. Discuss the implications of the resultsfor the Global Exec training programme.

*2. Analyse correlation patterns involving the variables AGE, YORG, FAIR, AMB, and IPT.*

Conduct the quantitative analysis and comment on the significant results obtained (if any). Discuss theimplications of the results for the Global Exec training programme.

*3. Use Factor Analysis to reduce the 15 variables measuring the construct ‘Job Related Tension’ (JRT1-JRT15) into a few factors. Analyse and define the meaningful factors that can be derived from the analysis.*

a. Show your summarised results grouping the factors (and related measure items) you have

found.

b. Name each of the new factors found in terms of what they represent in relation to their

respective factor loadings.

4. Can we predict….

a. ‘FEEL FREE TO DISCUSS JOB PROBLEMS’ (variable IPT1 as dependent variable) from ‘YEARS IN

PRESENT ORGANISATION’ (variable YORG)?

b. Variable IPT3 from variable AMB1?

For each item above, clearly state the related hypotheses, conduct the quantitative analysis to testthe hypotheses, and explain your conclusions on the hypotheses and the related implications forthe Global Exec training programme.

*5. Provide an overall conclusion of your report based on the evidence from the results of your analysis forall the questions above. You general conclusion should make clear to the Global Exec directors whetherthey should preserve standardised formats or make adjustments in the training programme they willdeliver to the bank across different regions. If they have to make some adjustments, which bank manageraspects the company should take into account?*

**Solution**** **

Analyzing the Market Variables for the Global Exec Company

**Introduction**

Rolling out new training programs by global executive would be useful for the company’s success. However, such a decisive initiative need to be examined and evaluated for any possible changes and risks that may persist. This paper looks into the possible factors that may determine the success of global executive in the new training roles. The analysis will take various forms including cross tab, correlation, and ANOVA and regression analysis for various elements that may inform the management of the need to decide on the course of the investment.

To determine if there are similarities or possibly differences between races of the respondents given as variable RC in terms of the independent variables like Interpersonal Trust (variables IPT1-IPT5) and Age of branch managers given as variable AGE, the use of crosstab analysis is important. From the study, it was important to realize how the various races would be free to discuss their job problems, and the following table summarizes the Malay, Chinese and the Indian races responses.

**RACE * FEEL FREE TO DISCUSS JOB PROBLEMS**

Crosstab |
|||||||

Count | |||||||

FEEL FREE TO DISCUSS JOB PROBLEMS | Total | ||||||

NOT AT ALL | NOT VERY | FAIRLY | VERY | COMPLETELY FREE | |||

RACE | MALAY | 2 | 3 | 18 | 15 | 11 | 49 |

CHINESE | 1 | 5 | 16 | 10 | 3 | 35 | |

INDIAN | 0 | 3 | 4 | 3 | 6 | 16 | |

Total | 3 | 11 | 38 | 28 | 20 | 100 |

More Malay people participated in the research, a total of 49, the Chinese were 35, and the Indians were 16. However, from their perspectives, most of the races were free to talk about their jobs, 26 people for Malay, 13 people for Chinese and 9 people for Indians in the categories of being very free or free. This means the information provided in the study were majority out of frees will, and the respondents were not compelled or coaxed into giving responses.

Other race-specificanalyseswere undertaken. For instance, the illustration shows the race-specific responses to taking advantage to help at the place of work.

**RACE * PEERS TAKE ADVANTAGE TO HELP**

Crosstab |
|||||||

Count | |||||||

PEERS TAKE ADVANTAGE TO HELP | Total | ||||||

NEVER | NOT VERY OFTEN | SOMETIMES | VERY OFTEN | EVERY OPP | |||

RACE | MALAY | 1 | 12 | 24 | 9 | 3 | 49 |

CHINESE | 2 | 11 | 17 | 5 | 0 | 35 | |

INDIAN | 1 | 3 | 2 | 6 | 4 | 16 | |

Total | 4 | 26 | 43 | 20 | 7 | 100 |

It is possible to conclude from the above illustration that most Malay people are indifferent to whether to take advantage and help or not, as does most Chinese with 24 and 17 respondents’ respectively. Most Indians, however, would very often take advantage and help. It means that the decisions made from the responses are independent of any racial bias.

**RACE * CONFIDENT YOU FEEL PEERS ARE FRANK**

Crosstab |
|||||||

Count | |||||||

CONFIDENT YOU FEEL PEERS ARE FRANK | Total | ||||||

NOT AT ALL | NOT VERY | FAIRLY | VERY | COMPLETELY CONFIDENT | |||

RACE | MALAY | 2 | 6 | 29 | 6 | 6 | 49 |

CHINESE | 0 | 14 | 11 | 10 | 0 | 35 | |

INDIAN | 0 | 3 | 6 | 5 | 2 | 16 | |

Total | 2 | 23 | 46 | 21 | 8 | 100 |

In relation to how the ban respondents would rate their peers’ confidence, majority of the Malaysians indicated that their peers are fairly frank, majority of the Chinese indicates that their peers are not very frank and majority of the Chinese also felt their peers are fairly frank

**RACE * TRUST ON PEERS AND SUPERIORS DECISIONS**

Crosstab |
|||||||

Count | |||||||

TRUST ON PEERS AND SUPERIORS DECISIONS | Total | ||||||

NO TRUST | VERY LITTLE | FAIR | STRONG DEG | COMPLETE TRUST | |||

RACE | MALAY | 1 | 1 | 24 | 20 | 3 | 49 |

CHINESE | 0 | 4 | 22 | 9 | 0 | 35 | |

INDIAN | 0 | 1 | 6 | 8 | 1 | 16 | |

Total | 1 | 6 | 52 | 37 | 4 | 100 |

On ways to handle the superior’s decisions, themajority of the Malay indicated fair and strong regard to the superiors’ decisions, as did the other races. It shows that the chain of command in all the institutions sampled for the study is very close and thus people would so what they are told, in the policies whileat work.

**RACE * PEERS AND SUPERIORS WILLING TO HELP YOU**

Crosstab |
||||||

Count | ||||||

PEERS AND SUPERIORS WILLING TO HELP YOU | Total | |||||

VERY LITTLE | SOME EXTENT | CONSIDERABLE | VERY GREAT | |||

RACE | MALAY | 1 | 26 | 15 | 7 | 49 |

CHINESE | 5 | 19 | 8 | 3 | 35 | |

INDIAN | 1 | 4 | 6 | 5 | 16 | |

Total | 7 | 49 | 29 | 15 | 100 |

Considering the respondent’s view of how well they would take help from their seniors, themajority of the Malay indicated excellent help from their peers, the Chinese did the same, but the majority of the Indians indicates that such help is only considerable or very great. It means that the company may undertake collective training that would see the various members help one another out.

**Correlation Patterns **

Correlation studies show the extent to which one variable, the dependent variable would relate with another variable, independent variables (Trochim& Donnelly, 2001). In this research study, it is useful to understand how various variables like age, years of experience, directives from the superiors and performance evaluations would be related to one another, including the freedom to discuss the job projects. In the illustration that follows, the correlation analysis are presented

Correlations |
||||||

Control Variables | YEARS IN PRESENT ORGANIZATION | SUPERIORS LET YOU KNOW IF THEY EXPECT SOMETHING OF YOU | HOW FAIRLY YOU THINK YOUR PERFORMANCE IS EVALUATED-FAIR | FEEL FREE TO DISCUSS JOB PROBLEMS | ||

AGE | YEARS IN PRESENT ORGANIZATION | Correlation | 1.000 | .267 | -.041 | -.299 |

Significance (2-tailed) | . | .007 | .685 | .003 | ||

df | 0 | 97 | 97 | 97 | ||

SUPERIORS LET YOU KNOW IF THEY EXPECT SOMETHING OF YOU | Correlation | .267 | 1.000 | -.251 | -.226 | |

Significance (2-tailed) | .007 | . | .012 | .024 | ||

df | 97 | 0 | 97 | 97 | ||

HOW FAIRLY YOU THINK YOUR PERFORMANCE IS EVALUATED-FAIR | Correlation | -.041 | -.251 | 1.000 | .199 | |

Significance (2-tailed) | .685 | .012 | . | .048 | ||

df | 97 | 97 | 0 | 97 | ||

FEEL FREE TO DISCUSS JOB PROBLEMS | Correlation | -.299 | -.226 | .199 | 1.000 | |

Significance (2-tailed) | .003 | .024 | .048 | . | ||

df | 97 | 97 | 97 | 0 |

There is alow positive correlation between the years of the experience in the organization and the understanding that the employees have regarding when the superiors want them to know something. Further, there is a low negative correlation between how the employees think their performances are fairly evaluated and their years of experience in the organization. The low correlations point to a market training requirements that would map out the different organizational practices to the understanding of the organizational values by the employees. This points to an opportunity for possible acceptance of the company’s intended training of the bank employees in the region.

**Factor Analysis**

The factor analysis can be useful in the refinement of the variable used in the study to increase the level of the study integrity an accuracy (Stake, 2013). In the analysis, the job-related tension factors were many, and thus they could be reduced through the factor reduction analysis from fifteen to four grouping factors as shown in the below illustration.

Total Variance Explained |
||||||

Component | Initial Eigenvalues | Extraction Sums of Squared Loadings | ||||

Total | % of Variance | Cumulative % | Total | % of Variance | Cumulative % | |

1 | 4.143 | 27.619 | 27.619 | 4.143 | 27.619 | 27.619 |

2 | 1.808 | 12.055 | 39.674 | 1.808 | 12.055 | 39.674 |

3 | 1.317 | 8.781 | 48.455 | 1.317 | 8.781 | 48.455 |

4 | 1.251 | 8.339 | 56.794 | 1.251 | 8.339 | 56.794 |

5 | .995 | 6.634 | 63.429 | |||

6 | .876 | 5.837 | 69.266 | |||

7 | .766 | 5.109 | 74.375 | |||

8 | .682 | 4.544 | 78.919 | |||

9 | .628 | 4.185 | 83.104 | |||

10 | .616 | 4.107 | 87.211 | |||

11 | .497 | 3.314 | 90.525 | |||

12 | .462 | 3.079 | 93.604 | |||

13 | .423 | 2.822 | 96.426 | |||

14 | .341 | 2.271 | 98.697 | |||

15 | .195 | 1.303 | 100.000 | |||

Extraction Method: Principal Component Analysis. |

The new factors, Extraction Sums of Squared Loadings represent the summary of the weighted averages of the initial fifteen factors that were considered job-related. As such, they represent the mean, the variances and other statistical attributes like the averages of the initial fifteen factors.

**Regression Analysis to Predict Variables**

To use the data analytic models to help in finding out if the feeling the employees has to discuss their organizational problems from the years of experience in the organization. A linear regression analysis would be useful in place. The regression analysis shows the model summary with the R and R square values that shows the extent to which one variable would be predicted from the other variable. In this case, the years of experience can only determine 11.9% of the freedom to discuss the job variables, and the other 87.1% would be explained by other factors other than the years of experience. The Anova table shows the level of significance, a value less than 0.05 would give a 95% confidence level, but in this case, the significance level is 0.2 which does not give auseful level of confidence. In the linear regression table, the coefficient of correlation is negative. This the age alone cannot be used to predict the freedom to discuss job problems among the employees. The useful tables in this analysis are presented in the following section.

Model Summary |
||||

Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |

1 | .119^{a} |
.014 | .004 | 1.028 |

a. Predictors: (Constant), AGE |

ANOVA^{b} |
||||||||||||

Model | Sum of Squares | df | Mean Square | F | Sig. | |||||||

1 | Regression | 1.479 | 1 | 1.479 | 1.400 | .240^{a} |
||||||

Residual | 103.511 | 98 | 1.056 | |||||||||

Total | 104.990 | 99 | ||||||||||

a. Predictors: (Constant), AGE | ||||||||||||

b. Dependent Variable: FEEL FREE TO DISCUSS JOB PROBLEMS | ||||||||||||

Coefficients |
||||||||||||

Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||||||||

B | Std. Error | Beta | ||||||||||

1 | (Constant) | 4.593 | .921 | 4.986 | .000 | |||||||

AGE | -.028 | .024 | -.119 | -1.183 | .240 | |||||||

a. Dependent Variable: FEEL FREE TO DISCUSS JOB PROBLEMS | ||||||||||||

Predicting Variable IPT3 from variable AMB1?

In the same manner, the variable AMB1 would only influence 43.8% of the variable IPT3. This means there were are 46.7% of the variable attributes that would be influenced by other factors other than the AMB1. On the same note, the linear regression ANOVA model shows that the level of significance is 0.00 which is less than 0.05, thus having more than 95% confidence level. Finally, the linear regression model shows that the coefficient of regression between the two given variables is – 0.46, hence, the variable, AMB1 can be used to predict the variable IPT3.

Model Summary |
||||||||||||||||

Model | R | R Square | Adjusted R Square | Std. Error of the Estimate | ||||||||||||

1 | .438^{a} |
.192 | .183 | .827 | ||||||||||||

a. Predictors: (Constant), SUPERIORS LET YOU KNOW IF THEY EXPECT SOMETHING OF YOU | ||||||||||||||||

ANOVA^{b} |
||||||||||||||||

Model | Sum of Squares | df | Mean Square | F | Sig. | |||||||||||

1 | Regression | 15.897 | 1 | 15.897 | 23.216 | .000^{a} |
||||||||||

Residual | 67.103 | 98 | .685 | |||||||||||||

Total | 83.000 | 99 | ||||||||||||||

a. Predictors: (Constant), SUPERIORS LET YOU KNOW IF THEY EXPECT SOMETHING OF YOU | ||||||||||||||||

b. Dependent Variable: CONFIDENT YOU FEEL PEERS ARE FRANK | ||||||||||||||||

Coefficients |
||||||||||||||||

Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||||||||||||

B | Std. Error | Beta | ||||||||||||||

1 | (Constant) | 4.181 | .239 | 17.481 | .000 | |||||||||||

SUPERIORS LET YOU KNOW IF THEY EXPECT SOMETHING OF YOU | -.462 | .096 | -.438 | -4.818 | .000 | |||||||||||

a. Dependent Variable: CONFIDENT YOU FEEL PEERS ARE FRANK | ||||||||||||||||

**Conclusion**

The market that the company is planning to venture is arecipe for the kind of training that they plan to roll out. It is useful to realize that most of the employees cannot even relate their age of experience to the kind of performance appraisal applied in the organization. Not many modifications may be necessary as the market equally seems not to have got any kind of performance related training. It would be useful or the organization to take up the initiative and roll out the training programs as soon as it would be appropriate for both the market and the training team.

References

Stake, R. E. (2013). *Multiple case study analysis*.Guilford Press.

Trochim, W. M., & Donnelly, J. P. (2001).Research methods knowledge base.