This paper discusses a research study conducted by Rodger W. Griffeth titled “ Innovative Theory and Empirical Research on Employee Turnover.” The researcher studied the variability in the mix of; tenure and ability together with personality types have relations with the effectiveness and success of any work. A change in the characteristics of individuals in a group, tends to change the main characteristics within the entire group, or rather, it has an impact on a group level performance due to changes in either, skills, abilities, talents and other cohesive factors that are considered to affect the overall task performance. Previous studies have shown that, the dynamics of a team or a group changes over time, not as a result of the changing reactions and norms in the environment but also as a result of the change in the quality of the members. This study will describe the steps or the procedures and the actions that a researcher would consider in the management of data that may be used in this study. The progress of this paper will shift from the issues that should be put in place before data collection, during data collection and then the analysis process.
Data ownership entails to who gets the legal rights to have the data after the research process is finished. In our case, the data will be owned by the general public governments and the interested institutions to analyse or draw some inference concerning the data. In this data, collection procedures will be executed in a way that the data will be consistent, reliable and valid. After the data is collected, it will be important to store them in a safe place, so that the data can be used in reconstruction, when needed. The collected data should be protected from harm or distortion; this is relative to both the electronic and written data they should be guarded against physical damage and protecting data integrity and such things as theft. Data should be retained for future use, with regard to time for the sponsors or the guidelines of the funders. Data analysis will follow, and it pertains how raw data are chosen, interpreted, and evaluated into significant and meaningful conclusions that the general public can understand and interpret. Data is then expected to be shared, through dissemination to other researchers, institutions and the general public; finally this analysed data and the shared bit is reported, and pertains to the publication of the findings, with regard to both the positive and the negative findings.
We are particularly interested in the analysis of the performance of a group, when the factors that affect performance are controlled. A population sample will be selected through a stratified random sampling; this is done by randomly selecting elementary schools in the country and then selecting the number of subjects that we want to include in the study. Such a study requires a lot of resources in terms of financial assistance, work force, and the stationeries and the technological knowhow. Application of a grant or a contract will be considered. Institutional grants or otherwise known as the assistance funding are usually awarded to research projects, especially those that have a beneficial outlook for the institutions. Institutional contracts on the other side can be seen as the procurement funding that is funding with an aim of acquiring a product, service or a property, either of these two would be a major source of funding in our case.
After acquiring the funding, piloting process follows, piloting is required to gauge the consistency, reliability and validity of both the collected data and the instruments used to collect the data, if either is not met, then the necessary adjustments are made to ensure that the expected results are replicated. After the piloting project is done, and mark that the piloting process, entails using almost the same amount of data that the main research uses, so as to estimate the difficulties that the main study might be faced with, in terms of the personnel employment, ethical issues, language familiarity, financial estimation and other factors that may cause the data not to be collected with the precision required, not also that all other processes that we expect to carry out in the main research, like data analysis, are carried out altogether to allow researchers to see the expected or the estimated statistics, this is of course done through various deployment of statistical knowledge that ensures that data is a representative of the population parameter, in terms of unbiasness of the statistics, sufficiency, and consistency.
After recruitment of the qualified personnel and the enumerators, they are taught on how to go about the collection of the data; we all know that if the data is not well collected then the whole statistics is not correct. Other specialists, for instance, data analysts, project managers, finance managers and so on, are enlightened on the various expectations of the project. After this initial and yet important task, the main data collection takes place. Data collected is expected to take the bulk of time to ensure that the data is collected with accuracy, basically, data that are collected in any research is done to prove or disapprove, the set hypotheses and to justify a point to the general public. Data is collected, while ensuring validity of data, reliability of data, and the precision required. Collecting reliable and valid data ensures that the evaluated data is good, that is, the research will be honest and precise and more people will be able to trust it can use it in the various uses. Record keeping is another important thing in the research process the records attempts to retain the progress of the project, and may answer questions that may prop up for instance, why and how data was collected. For small projects, use of note books are applicable in record keeping, but in large projects like this, electronic records are used to enable researchers to efficiently do the same and do comparison across similar projects.
There are different electronic gadgets that allow researchers to store, audit and enter data, security of these devices are, however, essential. In most projects, though, the employment of both the written and electronic records are used, this research intend to use the same in data recording. Attention to procedures and policies, the guidelines that people are aware of are applied to allow in the implementation and dissemination of the data. Data storage is another step used data management; this is a method that precedes data collection. Data storage is essential for safeguarding the research investments, for revision or to be used in the future for other researchers. The stored data may also be used to establish precedence when a similar research is undertaken; the stored data are also used in the event of legal allegations. Electronic is again used in data storage, to appropriately allow the use in the future; this is through the use of documentation of the various softwares that accompany the electronics. Electronic storage ensures that, data is rapidly accessed at a low cost and the ability to retrieve the data is achieved. The electronics have also the backup system that ensures that data is secure.
Data protection is done is such a way that hacking and theft is avoided, electronic data will be protected through the following ways: use of Ids and passwords that cannot be easily cracked, changing passwords frequently to ensure that only the project members can access the data access of data can also be done is such a way that one can only access them through a central server and ensure that external wireless devices are restricted from accessing the data. The system can also be protected, through the use of updated virus, in servers and computers, use the updated software and storage devices, and use of firewall.
After all these stuff is done, we have to translate the numbers into a meaningful inference, there is no single method for data, analysis, the data analysis comes from a particular project. Our data particularly will be given to the project statistician; however, in case we introduce a new statistician from outside, someone will be responsible for ensuring that he understands the projects well. In data analysis, the common data problems we expect will be, whether to include of exclude the outliers, what to do in case of missing data, when to alter or amend the data, and how to organise and present the data. Within the data management, data cleaning methods will also be applied especially when, the instruments have problems or malfunctions, when some data are lost or the interruption or deviation of the procedures.
Some ethical issues are expected in data analysis, for instance, forging, that is, reporting experiments never performed, cooking, using those results that tend to fit the hypothesis, and trimming, the smoothing of data that is irregular to make it look precise and accurate. Statisticians will be alerted to point out where they suspect such occurrences to allow repetition of the process in order to have accurate results. Other issues in data collection involve, inducement of participants to take part in the study processes, coercion of participants, threatening participants and obtaining data from them without, their knowledge. Such events will be prevented by having at least two project supervisors that will ensure the correct protocol is observed in the research study.
References
Assembly, U. N. (2006). Report of the Secretary-General on the Work of the Organization. Washington: United Nations Publications.
Nations, U. (2009). Statistical Commission Report on the Fortieth Session (24 to 27 February 2009), Issue 4. New York: United Nations Publications.
Rodger W. Griffeth, P. W. (2004). Innovative Theory and Empirical Research on Employee Turnover. New York: IAP,.
Weiten, W. (2010). Psychology: Themes and Variations. Belmont: Cengage Learning.
