Visualizing Data
The visualization and presentation of data using illustrations such as tables, charts, and graphs makes research work easy to present and comprehend, as is the case in Dr. Hans Rosling’s presentation that shows the relationship between population and health in various countries as well as the changes in population and health as time in year’s changes. The initial presentation is a bubble chart that displays life expectancy at birth against fertility rate. Each bubble represents a particular country, and the size of the bubble is the population (Rosling, 2006). Next, he uses an area chart to show the distribution of income in the world. The area under the curve represents the world population, while the x-axis displays the amount of money earned per day while the area under the curve represents the population. In this illustration, he also uses a pie chart to show the distribution of income. Later the area chart is stratified to show income according to various geographical areas.
The application that Dr. Hans Rosling uses to present data is quite dynamic because he is able to convert the area chart into a bubble chart, and each bubble can be split into its individual constituents (Rosling, 2006). He plots a bubble chart of child survival against GDP per capita from the area chart on world income. The split of a countries bubble generates a line graph for that country as is observesd when he splits the Uganda bubble among others. Dr. Hans Rosling’s presentation techniques make the research work easy to present and comprehend. In addition, variables can be presented dynamically on various charts because of the flexibility of graph plotting and bubble splitting. Lastly, one is able to observe trend through the sequential display of several bubble charts of different years. The weakness of Dr. Hans Rosling’s visualization techniques is that an individual can be objective when presenting or reading the information.
Homeland Security Statistics
The Department of Homeland Security uses statistics in collecting data for research and presenting that data using visual representations such as tables, charts, and graphs that make research work easy to present, comprehend, and compare. Hence, statistics play an important role in communicating information to the public because statistical information is included in report documents. The statistical information is available not only to the public but also to other government agencies as a means of cooperation to ensure that the homeland is safe and secure. The “No FEAR Act Annual Report” is an annual report that is presented at the end of every fiscal year to various government officials (Homeland Security, 2012). The report contains information on cases of discrimination, an analysis of that information, the status of the discrimination cases, the number of workers that have been disciplined on grounds of discrimination, and the implementation of disciplinary action policies just to mention a few (Homeland Security, 2012). Within the ”No FEAR Act Annual Report,” there is a histogram that presents data on the Equal Employment Opportunity program (EEO) complaints activity from 2006 to 2011 (Homeland Security, 2012). This is the first figure in the report, which is titled “Complaints Filed, FY 2006 – FY 2011” (Homeland Security, 2012). The y-axis represents the number of complaints filed per year. Therefore, the y -axis holds the frequency of the histogram with numeric values that run from 0 to 1400 at intervals of 200. On the other hand, the x-axis has ordinal variables of time in years. Years is an ordinal variable because there is a specific sequence that they should follow when presenting. The years start from 2006 and end at 2011 with an interval of 1 year between the years. The shape of the histogram is a plateau for the reason that all the peaks are at almost at the same level.
Correlation and Association
Correlation is the measure of the strength of the relationship between two quantitative variables. Correlation quantifies the magnitude of change in one variable in relation on the change of another variable. The correlation coefficient is denoted by the letter “r” and the value is within -1 and 1 (that is -1 ≤ r ≤ +1). Correlation coefficients are valid in linear relationships; hence, the coefficient can be used to determine whether a linear relationship exists between two variables. A correlation coefficient reads zero (0) when the relationship between two variables is extremely weak or when there is no relationship. If a correlation coefficient is less than zero (that is between -1 and 0), this means that the graph has a downward slope while a correlation coefficient that is greater than zero (that is between 0 and 1) means that the slope is upward. The relationship between two variables is strong if their correlation coefficient value is either closer to -1 or closer to 1. Similarly, the closer the correlation coefficient is to zero the weaker the relationship between two variables. Correlation cannot be measured on a curved graph. On the other hand, an association is a general term as compared to correlation because it refers to a general relationship without the details of the relationship. The types of variables are not significant when determining an association. An association is denoted by the letter “p” and it determines whether a relationship exists between two random research variables, in other words, whether there is statistical dependence between two variables. Some of the statistical methods used to establish whether an association include distance correlation, and odds ratio just to mention a few.
Focus Groups in Homeland Security Preparation
The participants to the focus group were recruited from the low-earning neighborhoods in Los Angeles that have a large percentage of Latino immigrants (Eisesnman et al., 2009). English and Spanish flyers that had recruitment information were distributed to the community, as the means of informing potential participants. The participant’s participation was anonymous, they provided a written informed consent, and they received incentives as motivation for their participation (Eisesnman et al., 2009). The discussion guide was converted to Spanish for communication with populations that did not communicate in English. Moreover, bicultural and bilingual facilitators were involved in the exercise to reduce cultural and language barriers respectively. In addition, some group discussions were held in English while others were held in Spanish; all discussions were transcribed and audiotaped for future reference (Eisesnman et al., 2009).
The issue of bias was minimized in this exercise because the researchers used various methods to address language barrier thereby minimizing the possibility of bias. Therefore, the results of the exercise are representative of the low-income Latino population that lives within the neighborhood of Los Angeles. The results represent their plight because their responses have common themes such as the desire to remain calm in the occurrence of an earthquake, limitations to disaster supplies’ storage, and limitations in communication (Eisesnman et al., 2009). Using the results of the study, the researchers were able to make recommendations that would assist in making the low-income Latino population to be more prepared for disasters. The recommendations; include educating them on the safety measures to observe in case of a disaster, educating them on appropriate types and qualities of supplies, and the use of terms that they are familiar with because some of them do not understand the terms “communication plan” and “disaster kit” (Eisesnman et al., 2009).
Elite Interviews Interviewing elites is not recommended in the homeland security research because it is subject to the ethical issues and matters of openness that are experienced in a personal interview. The first problem is the accessibility and availability of the elite person for the reason that some of them are busy high-ranking officials (Gubrium & Holstein, 2001). The elite may be suspicious of the intention of the interview especially in a situation he/she does not have the acquaintance to the researcher. Elites have their points of view of the community, beliefs, and opinions, which should be presented as they view them without alteration, an alteration of some of their information with reference to them would affect their personal lives (Gubrium & Holstein, 2001).
An elite interviewee who has a strong stance on a particular issue may have the notion the interview is meant to undermine him/her, hence some of them will enquire on the position of the researcher, which is tricky because the researcher should be non-partisan. The other problem of interviewing elites is that the researcher might find himself/herself with a conflict of interest on what is to be written against the view of the interviewee. Another problem is a case whereby a researcher handles an emotionally sensitive topic, whereby he/she needs to be wise and well informed on how to handle the topic to avoid hurting the interviewee emotionally (Gubrium & Holstein, 2001). Lastly, the interviewee is likely to give biased or exaggerated feedback on a certain topics or points to favor his/her interests thereby giving feedback that unreliable. Therefore, the researcher needs to do additional fact finding on the information collected from the interviewee to ascertain the credibility and correctness of the information.
References
Eisesnman, D.P., Glik, D., Maranon, R., Gonzales, L,. & Asch, S. (2009). Developing a Disaster Preparedness Campaign Targeting Low-Income Latino Immigrants: Focus Group Results for Project PREP. Journal of Health Care for the Poor and Underserved.
Gubrium, J. F., & Holstein, J. A. (2001). Handbook of interview research: Context & method. Thousand Oaks, Calif: Sage Publications.
Homeland Security. (2012). No FEAR Act Annual Report. Department of Homeland Security Office for Civil Rights and Civil Liberties. Retrieved from:
Rosling, H. (2006). “Stats that reshape your worldview” [Ted].Retrieved from:
