Work Addendum

Work Addendum

This is a supplement paper the original proposed, which was earlier submitted for approval. The essay expands on the resources or references which were used in drafting the original proposal. In most cases, references are used majorly in the literature review sections and other parts. It gives an elaboration on the prosed techniques which would be used for data analysis in the real study. Finally, the essay discusses the possibilities when there occurs an increment in data variety.

Resources/references used for the proposal

In the original project, the researcher used current references that are related to the study topic area. All the information acquired from these resources was appropriately referenced as required in any writing standard. The proposal outlined all the used references at the bottom of the paper named ‘reference.’ Books and peer-reviewed articles were used in drafting the essay. These provided relevant information needed in arguing the information required for the study.  The references used were updated and connected to the study topic of the proposal.

Proposed data analysis techniques

The study uses quantitative data. This calls for quantities as well as hard numbers to be used. The data shall incorporate sales numbers, data attained from marketing research like payroll data, revenues, plus others that are objectively countable.  The methods of quantitative analysis depend on the capability of accurately counting and interpreting data anchored on the available hard facts. The proposed techniques for data analysis incorporate the use of regression, hypothesis testing, and Monte Carlo simulations

Regression analysis- the tools for regression studies are required when one needs to make predictions or forecasts which for the future trends. Regression measures the relationship between independent and dependent variables. The Independent variable refers to data the researcher wants to use in giving predictions about the dependent variable. The dependent variable is the data that needs to be measured. In a study, there can only be a single dependent variable. However, the same research can have as many independent ones. Again, regression assists the researcher to uncover sections of operation which can be optimized. Optimization can be made to happen through highlighting relationships and trends between factors.

Hypothesis testing- this is method is similarly known as t-testing.  The approach enables one to compare data that have been collected against set hypotheses as well as assumptions made regarding the study. T-testing assists in making forecasts on how decisions made shall have impacts on an organization. The technique allows for comparisons of two variables to establish correlations, thus make decisions concerning the findings. For example, one might assume that more work hours are equivalent to the high productivity of workers in a station. Therefore, before putting to effect longer working hours in an organization, it is imperative to make sure that there exist real connections to shun unpopular strategy.

Monte Carlo simulation- is the famous technique used greatly in calculating variables that are unpredictable on special factors. The simulation employs probability modeling in order to assist in predicting risks and uncertainties. For one to test a scenario or hypothesis, the technique shall utilize random data and number in order to stage various possible outcomes to any condition anchored on the results. This is helpful tool in various fields which incorporates finance, logistics, and project management among others. Through testing different possibilities, the researcher has the capability of comprehending ways in which random variables have impacts on the project which is undertaken.

Increasing variety of proposed data

Quantitative research uses count data. Analysis of such information must take into consideration data integrity as well as apt analysis of findings acquired from a research. Good statistical analysis always distorts findings deemed to be scientific in nature. In order to increase the variety of proposed data for analysis, the following are considered:

Requisite skills used in analyzing the data- it are often tacit presumptions made by the researcher that appropriate research demonstrates higher standards of data analysis. More often, scientific misconduct which is unintentional leads to poor results of instructions followed. Thus, when adding more data in a study, it is recommended to have a team of statistician to handle such added information (Sandelowski, 2000). Ideally, the investigators are required to have basic understandings on the rationale of choosing one method of analysis over the other. This allows them to supervise the unfolding of their studies up to the ones conducting the analysis. With that, investigators will make informed decisions on whether to increase data variety or not.

Determine significance-as the traditional practice is to determine acceptability standards in support of statistical significance, it might similarly be appropriate to outline if attaining statistical significance has true meaning when data variety is increased. It is essential to look into a situation whether increasing data variety would determine statistical significance of the whole work.

Data presentation- addition of data into the study should be established if it would have impacts on data presentation methods (Onwuegbuzie & Combs, 2010). Most of the times, investigators have the potentiality of enhancing impression of significant findings. This is done through establishing how derived data is presented. It shows the portion of data shown. Thus increasing data variety is likely to interfere with the manner in which data is presented. Adjustments have to be made when some information are added.  In the event of adding data into any study, it is as well imperative to look into various ways of adjusting methods for data recording. Analysis can be influenced by the method in which data was recorded. The events of investigators can be documented through videos which call for transcription of such videos later. The researcher can as well administer survey question to the participants. Therefore, when increasing the data variety in a study, then the method for recording added data should be taken into consideration. This would promote levels of accuracy for the attained results thus boosting the confidence level of the study. Addition of data to be analyzed for the study calls for various issues to be put in place to promote the study credibility.

References

Onwuegbuzie, A. J., & Combs, J. P. (2010). Emergent data analysis techniques in mixed methods research: A synthesis. Handbook of mixed methods in social and behavioral research, 2.

Sandelowski, M. (2000). Combining qualitative and quantitative sampling, data collection, and analysis techniques in mixed‐method studies. Research in nursing & health, 23(3), 246-255.