Discussion Forum 12 – Term Paper

Introduction

In todays world, statistics plays an exclusively vital role in the field of research. As a matter of fact, statistical data helps in the collection, analysis as well as the presentation of data (Peat, 2001). It all boils down to the question, what will the data be used? Nevertheless, this is how statistics has helped me achieve the following course objectives.

Differentiate concepts of descriptive and inferential statistics.

       Being in a position of distinguishing the difference between descriptive or inferential statistics has enabled me to establish the fact that descriptive statistics describes the population while the inferential statistics makes the generalization about the population based on the samples. Thus, I am now able to use measures of central tendencies, charts, graphs and tables to organize, analyze and present data describing a situation sample in a meaningful way. On the other hand, I am now able to use inferential statistics to compare, test and predict data and make tentative conclusions about a population.

Selecting the appropriate statistical analyses and sample size

       Getting to know the type of project and the type of data to collect can be useful in determining the best analytical approach as this will help choose the correct test and the right sample size. Ideally, this is because I will be in a position of clarifying the findings I am interested in as well as the relationship between variables. For example, I now know that to study the difference between variables, it is best to use ANOVA and MANOVA while to study intervals and the ordinal-level, the correct statistical analysis to use is Spearman or Pearson correlations (Munhall, 1994).

Determine appropriate sample sizes for research studies.

A good statistical study is one that is well designed and which helps derive valid conclusions. According to Watson (2008), the two largest factors influencing the power of a study is the sample size and the effect size. The larger the sample size, the smaller the effect size that can be detected while the smaller the sample size, the larger the effect sizes that can be detected. A tiny sample size on the other hand is inconclusive while a study with a significantly massive sample size will waste scarce resources (Munhall, 1994). The most important thing is that the sample chosen should be representative and bias-free.  

Employ statistical and database software in data management

By now, I can comfortably say that database management has helped me manage data efficiently as well as perform multiple tasks with ease. With a single software application, I can use database management systems to store, organize and manage a large amount of information with a single software application. Through the use of popular statistical package such as software R software, I am able to unearth hidden patterns, unknown correlations, market trends, customer procedures and other useful information that can help organizations to make more informed decisions.  

Evaluate the use of data in health science research reports.

It goes without saying that modern technology has necessitated the use of information in making a conclusion and conclusion decisions. It ha there comes to true that there is need generate and record vast quantities of new data. Health-related statistics and data sources are increasingly available on the internet. Getting to understand how to evaluate data in health science research reports has enabled me to establish how social factors, financing systems, organizational structures and processes, health technologies and personal behavior affects access to health care, the quality and cost of healthcare (Silva-Aycaguer, Suarez-Gil, Somoano, 2010)

References

Munhall, P.L. (1994). Revisioning phenomenology: Nursing and health science research (No. 41). Jones & Bartlett Learning.

Peat, J. (2001). Health science research: a handbook of quantitative methods. Sage.

Silva-Aycaguer, L.C., Suarez-Gil, Somoano, A.F. (2010). BMC Medical Research Methodology.

Watson, J. (Ed.). (2008). Assessing and measuring caring in nursing and health science. Springer Publishing Company.