Statistical Tools and Methods of Data Collection
Statistical Tools and Families
Researchers often depend on the data, which is effectively collected and analyzed through various modes and families. Statistics are essential tools and enables for data collection, analysis, presentation, and interpretation across different fields using different tools. For the sake of Mittra the vice president, there is need to effectively use valid tools that would enhance the production and processing of information to reach the required outcome. As the VP of the organization, the essence is that he wants to use the previous information as the statistical tool and families to collect and analyze the information. The number of the refrigerators and the transformers needed for the production of voltage regulators are effectively collected and analyzed to achieve the desired tasks. There are different families which are used by the scholars to ascertain the cases of overstocking and u8nderstocking in the company’s production of transformers in the industry (Mohammadi & Prasanna, 2003). Based on the approaches used by the Vice President Mittra, it is possible that the estimation was below or above the requirements in the industry, which leads to shortage or surplus in production. To effectively collect accurate and applicable information about any given aspect of production, the organization and the management should use several statistical tools and families to enhance the collection, processing, analyzing, and application of the data to solve the problem such as the one given in the case study.
Ratnaparkhi, who was the operations head and who is charged with responsibility of analyzing the research and data collection parameters, has to employ effective and efficient tools to analyze and recommend the information to solve the situation, while also compose a report which would be comprehensive across different levels of management in the organization. The tools would enable the researchers to come up with additional and relevant information about what needs to be done to solve the problems. Instead of using speculations and assumptions, the tools could effectively be used to address the applicability and authenticity of the research through efficient data collection and analysis. Thus, the data collection method should be devoid of error and biasness, while enhancing accuracy and precision of the research towards achieving the set goals and objectives. A-Cat Corporation requires robust statistical process control to effect the changes required in the organization and to make everything efficient in reaching out to the quality control programs, especially those of the transformers (Ramsey & Schafer, 2012). Thus, the most basic tools to use in this regard would be control charts, ranges and means, standard deviation, and other error-free implications in the long run. Besides, the use of previous information to assess and inform the organization on the quality control program would be ineffective and inefficient in informing the organization on the best practices to use in solving the challenges facing it.
Data collection is achieved through a series of statistical tools which enable the organizations and researcher to simplify the collection of data from the primary or secondary sources, and facilitate the dissemination of the information from experiments, observations, questionnaires, and surveys. The statistical tools to be employed in the analysis include tables, texts, semi-tables, and graphical methods, which are essential for the presentation and analysis of the collected data (Mohammadi & Prasanna, 2003). These will apply to data collected across different methods, such as questionnaire, experiment, survey, interview, and observation. The choice of this family of tools is based on the fact that they are applicable across different sources of data, either qualitative or quantitative, or primary and secondary data. Therefore, it would give the researcher the needed flexibility and effectiveness in presentation and analysis of collected data. Therefore, the use of tables, graphs, texts, and semi-tables would enable the researchers to effectively address the issues resulting from the utilization of data collected and presented for analysis. In this regard, researchers are facing the ease of utilizing any aspect or family of statistical tools to outline the utilization of different data sources.
Data Type and Suitability to the Tools
Different sources and types of data will be analyzed using different families of tools, such that it would ease the process of understanding the trends in the data, based on presentation and analysis. For instance, the use of tabular statistical tools to represent data could be suitable for secondary data, mainly involving quantitative data. This is because the quantitative data will be easier to tabulate and present through the numerical trends in the experiments, observations, and questionnaires or even survey of the study. For instance, such variables as age, numerical trends, height, salary, population, and costs could be easier tabulated or even presented and analyzed through textual methods and techniques to enable the researcher and the reader to understand each other effectively (Ramsey & Schafer, 2012). On the other hand, graphs and textual methods could be effective statistical tools for the presentation and analysis of qualitative data from primary sources, such as behavior, response, and trends. This is because it is easier to predict or capture the aspect of qualitative responses to treatments of the variables in the experiment, study, or observation. Therefore, every tool will be effective in whichever type of data, and could also favor the mixed research designs, featuring qualitative and quantitative research designs.
Statistical Tools and the Case Study
The use of a specific family of statistical tool in a given data or case study will greatly affect the outcome or prediction of the trends, through probability. The case of addendum Vice-president Arun Mittra is a situation which calls for the collection of data, which has to be presented and analyzed for comprehension with even low level employees. This means language will be at all point understandable and the tools used be direct and easy to follow for the trends. Therefore, the use of tables would the best statistical method to present the data, as it would be easier to follow on the report, as to whether the organization overstocked or under produced. The use of tables, or even the graphs will favor the presented and analysis of both qualitative and quantitative data, through a mixed research method (Mohammadi & Prasanna, 2003). Ostensibly, it would be easier to focus on the trends which are as a result of the study, experiment, and observation of the performance of the products in the market and how the company can utilize the data from the tables to inform on the action plan. Tables will favor the low level employees to understand the analysis which the Vice President has attached to the data collected; hence will be easier to share the predicaments of the organization.
A-Cat Corporation is in pursuit of quality control programs through statistical processes. based on the data provided on the quality control statistical processes by Ratnaparkhi, the measures of the center, or central tendency has been used to effectively address the analysis process of the production and the state of the stock in the A-Cat Corporation. Based on statistical methods that facilitate decision making in the company, it would be effective to use tables, as it would encompass the quantitative concepts of the provided information on the measures of central tendency, such as mode, median, and mean of the products and the state of overstocking or otherwise (Ramsey & Schafer, 2012). The number of transformation given in the data would enable Mittra, the Vice president of the organization, to provide the sales department with required sales projections, and the number of transformers which will be affected and produced in the ensuing years of 2007-2010. The use of tables and graph would enable for probability and understanding of the trends in the number of transformers needed to avoid the essences such as the production of less or more of the products to the market in the anticipated years, using the previous information from the secondary sources from 2006 downwards. The tabulation of the results would be effective and efficient in understanding of this quantitative data, as the previous trends would be tested against the prevailing market trends and errors to inform on the realities of the market performance.
The use of previous methods could lead to the underestimation of the market value and the real demand or supply balance in the market, hence the need for the use of a more reliable method that would minimize the statistical methods and lead to a more accurate probability in analyzing the prevailing and future market trends in the company (Newton & Rudestam, 2012). This will enable the company to address the shortage of surplus of transformers which could be subjected to understanding of the previous years in the company. The use of statistically generated information would enable the organizations to come up with brilliant ideas, based on efficient in the analysis of the collected secondary of primary data. The decisions to use statistical methods as a form of data collection and analysis enables the company to come up with the important information to give them best trends to guide the business goals and motives. In this regard, it is possible that different families of statistical tools and methods would enable the companies and organizations to come up with informed decisions on the production, sales, marketing, and other essential functions. Consequently, the use of different tools would suit a given circumstance, such as the above case study, to come up with best data collection and analysis methods.
Quantitative Methods for Data-Driven Decisions
For the A-Cat Corporation to make informative decisions based on the number of refrigerators to manufacture and the knowledge of market dynamics there are several methods quantitative methods to use. Quantitatively, there could be such methods as textual, tabular, semi-tabular, and graphical representation of the data collected through the above mentioned tools and families. In this regard, the researcher who is assigned the role by the organizational management will have to look at the most important approach and method to analyze and interpret the information quantitatively to come up with brilliant ideas on the decision (Mohammadi & Prasanna, 2003). Based on the case of A-Cat Corporation, the researchers could apply the knowledge to underscore the number of refrigerators sold against the number of transformers required in the market. The statistics are summarized as a sampled data necessary for informing the management on the best method of decision and to advance the needs of the company in light to the production and sales, overstocking versus under stocking, and the assessment of market dynamics. For instance, textual method would make the organization to gather information and make decision based on reading the assembled information. Tabular method would enhance decision making through provision of a more precise, orderly, systematic, and presentation of data in rows and columns for utilization and for decision making. On the other hand, tabular and textual methods of quantitative data analysis depend on the use of semi-tabular method to mix the diverse view and address the utilization of complex information. Finally, graphical methods would show the trends and visual implications of the data.
For this assignment and the case of A-Cat corporation’s state of production dilemma, there is need to use graphical method to inform on the trends and implications of a given production of transformers and the sale of refrigerators in the firm. This will enable for in-depth analysis and information on the best decision to make in the long run about the context in the organization. There could be other methods that would drive information on decision making in the organizational context, which is essentially used on the quantitative basis and context. For instance, linear regression would represent most of the information on sale and production balance and trend, the same as linear programming, factor analysis as well as data mining in general and specific terms, which both contribute directly to the production of effective information to inform the management on decision making process (Newton & Rudestam, 2012). Therefore, the information presented to the management for analysis could easily be quantitatively analyzed for decision making by the management when they adopt the linear and graphical method, as it would offer the trend and a discussion on the best practices in the long run. Therefore, for effective decision making and for efficient visual impression, the organization should adopt the graphical and linear method of research analysis for information on decision making processes.
Data Analysis towards Decision Making
A-Cat corporation’s problems have been balancing the production and sales to enhance the balance in the company. For effective decision making process in the organization, the company should utilize the essence of statistical analysis for decision making and to reach the best ideas. The process of data analysis and processing for the organization’s problems would stem from the data collection tools and processes which give the researchers the needed information and credibility issues as a benchmark. Following the data collection, the A-Cat corporation management should be focusing on data analysis, presentation, and interpretation, using the most applicable quantitative methods, such as the graphical and linear methods to give the trends on sale of refrigerators and the production of transformers in the company (Mohammadi & Prasanna, 2003). The knowledge of mean number of transformers required by the company in the next couple number of years would be greatly informed by the assessment of the needed goals and objectives in the long run and following the graphical revelations of the trends in the methods used.
The linear impression and analysis of represented data give the impression of what the future will be like, hence information the organization and Mittra on the transformer requirements in the organization. data driven decision making process would require analysis of information or data collected through the effective and efficient family and tools, measuring the data using the appropriate tools and units, free of biasness and error, analysis of the information based on the goals of the problem and the organization’s reason for enacting the processes, and using the represented and analyzed data and relating it to the needs of the organization, such as determination of mean requirements of the transformers in the industry and understanding of the dynamics of the industry which would suit the goals and objectives of the A-Cat corporation (Ramsey & Schafer, 2012). These processes will inform on the best ways in which the organization can use the quantitative measurements and outcomes to realize the needs and aspirations of the company. The decision should align to the culture, practices, goals, and objectives of the organization, and in addressing the challenges.
Following the outline would inform the management on the effective decision making processes and tools, which are reflective of the need to address the concerns of A-Cat Corporation’s production stalemate. Following the above processes will add to the validity of data, which begins at the use of appropriate tool to collect relevant data from the sources, such as previous years’ sales records on the refrigerators and the mean requirement of transformers in the market. In this regard, the organization will realize the real challenges facing the organization and work on ways of facilitating the processes of finding solutions from the collected data and information (Newton & Rudestam, 2012). Therefore, when the Organization follows this process, it will be important in assessing the quality of information and making sure that the challenges facing it are well addressed with the available data. Also, it adds value to the credibility of the information generated, hence the need to effectively follow a procedural method of coming up with solutions to the challenges. The quantitative measurements, analysis, and interpretation of data will effectively address the desires of the organization, since the formal process and steps highlighted would ensure that the researchers are not lost in their quest to find solutions to challenges.
Reliability of the Results
Understanding the reliability of the results would be enhanced through the use of appropriate methods and processes of collection, analysis and presentation for interpretation by the management to find the solutions. In this regard, the information collected and analyzed for decision making using the above process would be devoid of error since it is informed by the goals of the organization and the mission of the research itself. This makes the data to be relevant and applicable in addressing a given concern in the organization in an amicable manner. The data sets provided in the case study are typical of the need to use the previous data to set the trend or to understand the implications of the past on the present and future operations of the organization (Mohammadi & Prasanna, 2003). Through the use of effective and efficient tools and processes, the data is likely to be devoid of error and biasness and would stick to the requirements of the organization itself. The data will most likely to be reliable and relevant in its applicability to solving the problems and informing the decision makers in the organization on the number of transformers that should be produced by the A-Cat Corporation.
The illustration of data-driven decision would be impacted by the desire to addressing the concerns of the organization and the ability of the data collected and analyzed in being applied to the decision requirements in the organization. Following the assessment of the data presented in the case on the previous years’ records and the projection of results on tables, graphs, and other methods of presentation, it is possible that the results and data could address the problems in the organization. based on the ANOVA and other variance application to inform on the requirements in the organization, there is need to critically analyze the graphical trends of the past three years to inform on the coming years since it shows the consumption patterns in the industry. This is informed by the tabular and graphical representation of the consumption and production patterns of the previous years (Newton & Rudestam, 2012). Therefore, the use of previous records to inform on the future is the most basic data-driven decision that can enable the A-Cat Corporation to achieve the required dreams and aspirations all over the place and make the organization competitive in the market through production of reasonable number of transformers into the industry. The adjustments made across the years would be important indicators in the market about the change in consumer patterns and the marketing dynamics to inform the management on the best approach to use in production.
For both internal and external stakeholders, there is need for improved and enhanced data collection and filing in the organization. This would enable the organization to make informed decisions based on the available data which relates to the organization and the industrial and market dynamics. the internal and external stakeholders such as investors, consumers, government agencies, regulators, competitors, employees, and the management stand to benefit a lot from intensive research in the organization especially on the marketing and sales dynamics, which ensure that shortages and surplus productions are reduced to the bare minimal and that there is balance between production and sale of the transformers. This will enhance the confidence of internal and external stakeholders and to achieve the required impressions and opportunities.
The arrival at this decision follows the problems faced in research from scratch based on the resources which the organization employs. These intrigues could be reduced through effective data collection and storage, and which can only be retrieved in the long run to help in cases of challenges. This will address the challenges such as estimation, allegation, and guessing of the number of products which are needed in the market and use of data from unclassified sources and methods.