Presentation of Statistical Information
Decision making within any given organization requires the use of information and data so that the relevant and well-informed decisions that will benefit the whole organization can be made. Managers require information and data to be presented in an easy way to analyze interpret and make the most-suitable decision based on the report provided (Cox, Hand, & Herzberg, 2005). The statistical information should be presented in a simple way and contain graphical, and visualization hence get the meaning of the information and make the most-appropriate decisions for the Industry week (Yergens, Dutton, & Patten, 2014).
The statistical information need to be accurate, precise, clear and concise so that the decision that the manager will be able to make will be well-informed (Brechner, 2009). The presentation of the statistical information that has been obtained from the case study will use tables and graphs (Brechner, 2009). To be able to make the presentation of the statistical information through the table and graphs effective for decision making, the graphs and tables should be directly related to the written text in the case study (Cox, Hand, & Herzberg, 2005). Therefore, this means that the information that is to be contained in the graphs and the tables should act as a summary for the whole case study.
Apart from being directly related to the whole case study, the graphs and tables are also needed to act as supporting evidence to the written text. Furthermore, the graphs and tables must also be clearly labelled (Yergens, Dutton, & Patten, 2014). The manager is quite a busy person who holds a lot of responsibility hence the amount of time that is required to interpret the statistical presentation of the information need to be minimized (Yergens, Dutton, & Patten, 2014). Therefore, this is the reason as to why the presentation of the statistical information using the graphs and tables must be precise and clear (Brechner, 2009). In additional to ensuring that the tables and the graphs are properly labelled with all variables identified correctly, it is important to include footnotes that are summarized for easy understanding of the graphs and tables (Cox, Hand, & Herzberg, 2005).
Graphs and tables will also be the most suitable for the presentation of the statistical information from this case study due to the reason that they provide the visuals that a manager needs to make an informed decision (Brechner, 2009). The graphs and tables also show how the variables obtained are related and how each impacts on the Industry Week hence the manager will be able to make well-informed decisions (Yergens, Dutton, & Patten, 2014). Therefore, it will make the information more accessible to the manager, and also easy to memorize and remember without having to read the whole case study repeatedly.
Limitations of the Study
This case study has got some limitations that make it less reliable in making the final decision by the manager of the organization. Some of the limitations which can be directly identified include the sample size used during the collection of data. The participants in the research were 710 who completed their questionnaires but upon receiving the responses, only 676 of the responses were analyzed to provide the statistical information (case study). Therefore, it means that the actual results of the research were not relayed in this case study. The statistical information that was collected should have included all the responses from the total participants who took part in the research so that the actual results could be obtained. Furthermore, the limitation of this study is based on the margin of error that was assumed to be ± 4 percent (case study). This percentage is quite higher and hence reduced the chances of having accurate statistical information which the manager could then use to make the relevant decisions for the Industry week.
The other limitation of the study is the in-depth follow-up telephone interviews that were conducted. The respondents who were involved in the follow-up interview was 40 in number (case study). Therefore, this was quite less considering that the total number of respondents who had been used in the research was 710 (case study). The number limited the chances of obtaining a wider range of responses during the follow-up interviews by the respondents (Goodhue, Lewis, & Thompson, 2012). The study could also have been faced with the limitation of the questionnaire.
The length of the questionnaires was quite long and hence may have affected the kind of response the participants provided when filling in the answers to the questions (case study). The research that was carried out made use of disproportionate sampling whereby the adverts used were for the year 1992 which had 648 adverts and 1997 that had 690 adverts (case study). Therefore, there is no possibility of knowing the trend based on the number of years that have lapsed between 1992 and 1997 (case study). Therefore, this reduces the chances of the manager being able to make appropriate and viable decisions based on the results of the study.
Brechner, R. A. (2009). Contemporary mathematics for business and consumers. Mason, Ohio: South-Western Cengage Learning.
Cox, D. R., Hand, D. J., & Herzberg, A. M. (2005). Selected statistical papers of Sir David Cox. Cambridge: Cambridge University Press.
Goodhue, D. L., Lewis, W., & Thompson, R. (2012). Does pls have advantages for small sample size or non-normal data? MIS Quarterly, 36(3), 981-A16.
Yergens, D. W., Dutton, D. J., & Patten, S. B. (2014). An overview of the statistical methods reported by studies using the Canadian community health survey. BMC Medical Research Methodology, 14(1), 1-14. doi:10.1186/1471-2288-14-15