Introduction
Research methods and quality overall are based on their specific orientation and design, catering to a wide variety of research focuses, aims and hypotheses. There are also many strengths and weaknesses associated with varying research designs and this will consequently be linked to my own research assignment throughout this paper.

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The Cross Sectional Research Method
The first research design to be studied in this paper is the “Cross Sectional Research Method”. This specific design encompasses an analysis of outcomes, methods and exposures associated with a population study. For example, a researcher who uses the Cross Sectional Research Method might examine the relationship between the exposure and outcome of population results but will not be able to determine a final outcome or the reason behind there is a noticeable trend in population statistics (ADA, 2011). The current status and innovative style of this research method is one of its largest strengths as it effectively allows researchers and scientists to conduct present day and current studies, which in turn are more accurate and relevant to 21st century studies. Furthermore, additional research can be conducted once results are drawn from present day studies. Its second strength is the fact that it can provide future researchers with advice and guidelines on how to conduct a study or determine the reasons behind a certain population phenomenon. Researchers can also conduct group work with others and the style allows for further research and collaboration overall within an academic field of study (Creswell, 2009).

Multiple outcomes and solutions can also be sort after with the cross sectional design and there is certainly room for improvement, development and success particularly with more difficult studies and assignments. Population spread and prevalence can also be studied using this research method and are just a few of the different study areas that greatly benefit from this innovative and contemporary research design (ADA, 2011).

There are also a number of weaknesses associated with the cross sectional research design. Its first weakness is that it can not be conducted for historical records, which span a long period of time and it is regarded as only a short term research method. For example, population data for a decade period or longer can not be examined nor analyzed via this research method. Rather, data that is collected simultaneously can be and this causes some stress for researchers and scientists wishing to compare historical data. It is restrictive in this sense whilst other research methods can be primarily used for historical projects (ADA, 2011). Another weakness of this research method is bias and the fact that the researcher can intentionally alter the data and make comparisons to make the results and data more favorable for other researchers and assessors in general. Results and trends with results from an assignment can not be analyzed via this research method.

The Quasi Research Method Design
The second type of research design to be analyzed in this paper is the “Quasi-Experimental Design”. This method is primarily used to analyze cause and effect relationships for different phenomena. This research design is also an exact method and does not depend nor rely on qualitative data or data that does not provide an exact answer or reason. In this sense, the research method is very mathematical in nature and effective for scientific projects and assignments (ADA, 2011). One of its major strengths is its application in the area of social science and can provide a comprehensive analysis of the trends in data and how they produce certain results and effects. For example, in a set of population data, certain trends can be ascertained via this method and this in turn can be used to determine cause and effect. The cross sectional

The second strength of this research design is that it can be used in comparison to other studies and to compare historical data, in contrast to the cross sectional research design. It is very open and non-restrictive in nature. Statistical analyses are however very difficult to conduct with this research method design (ADA, 2011). Furthermore, this research design lacks a certain degree of randomness and results ascertained from it can vary and are not necessarily exact in nature. In many experimental situations, researchers have come up with a number of possibilities to explain a certain cause without any direct answer or indication that the results are valid and reliable in nature.

Application of Research Design in Current Study
My research question is: “Does the income of American citizens affect the prevalence of obesity?”. I will be using the quasi experimental design for this question as I intend on targeting populations with the use of historical data to compare results and determine trends in data. I do not intend on using random populations and am focusing on conducting a quantitative and highly accurate study, possible with the quasi experimental design (Nachmias & Nachmias, 2008). The population or social classes being analyzed in my assignment include the lower, middle and upper classes. I will also be using weight as another dependent variable that will ultimately vary with each income or social class. I intend on analyzing a number of different weight classes in order to ascertain the exact positive and negative influence of family income on family health. This will also allow me to draw comparisons between income levels and resulting weight classes overall, one requirement that the cross sectional research design can not account for or assist with. (Creswell, 2009).

Numerous variables of different nature can drastically influence the results of any research conducted. The researcher or scientist needs to account for each variable and establish some barriers and mediating actions to ensure that the results of the experiment are valid and also reliable. Results and the discussion section of any experiment can be misinterpreted if variables are not accounted for. Variables need to be controlled and effectively monitored throughout the course of the assignment. In my own study, one crucial variable to be constantly analyzed would be external factors influencing body weight in each family (ADA, 2011). For example, lack of education and overall knowledge can negatively influence people’s weight class and their ability to comprehend what is good and bad to eat and carry out. There are existing studies, which also suggest that obesity is related to genetics and this independent variable can not be altered but only monitored and taken into considering when results are drawn from experimental data. A comprehensive analysis of internal and external variables is also required in any experiment (ADA, 2011).

My assignment needs to focus on the cause and effect of obesity in American populations and the cross sectional research method will not be able to study nor ascertain this. It will further negatively impact my results. Surveys will also not be used throughout the course of my experiment and instead, the quasi research method will allow me to draw conclusions from population data from each income and social class (Creswell, 2009).

My hypothesis for my selected research study is that obesity will be less prevalent amongst lower incomes and as such, a quantitative research design such as the quasi research method will allow me to determine whether this hypothesis is correct or alternatively, wrong, requiring further attention and research. I do not intend on using a qualitative research design as it involves bias and some level of change and subjectivity.

    References
  • ADA. (2011).Cross-sectional study design. Retrieved from
    https://ada.portalxm.com/vault/rtk/Docs/20110601%20ADA%20RTK%20CrossSectional.pdf Accessed on 20th July, 2015.
  • Creswell, W. (2009). Research Design: Qualitative, quantitative and mixed methods approaches. Laureate Education Inc, custom ed, Retrieved from SAGE Publications.
  • Frankfurt-Nachmias.C, Nachmias, D. (2008). Research Methods in the social sciences.7th Edition, New York: Worth.