Data Analysis: Using Quantitative methods to study international migration

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The quantitative method of analysing data involves collecting and analysing numerical data. It is mainly composed of data collection methods like surveys, questionnaires, statistics and analytical techniques that are enhanced by computer processing (Bryman, 2012). This study aims at using qualitative methods to analyse data on international migration. In this context, the data mainly entails social facts. The three graphs to be analysed have information relating to immigration from and to the UK as a country of citizenship between 1991 and 2006, the frequency rate at which negative and positive messages in relation to migration are unveiled between 2014 and 2016, and percentages of the populations of South-East London Boroughs, that are born in the UK, by the country birth in 2011.

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The data sourced from census and summarised in the graph above was collected by the IPPR (Institute for Public Policy Research) research team. The graph is based on the airport influx of migrant groups, with a focus on the A8 group. A8 is an abbreviation referring to the eight Eastern and Central European countries (Poland, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Slovakia and Slovenia) that joined European Union (EU) in the fifth month of 2004 (Pollard et al., 2008). The IPPR created it to enhance the accuracy of the overall research relating to extensive migrants’ fluctuation. The line graph used as the method of representation enhances the determination of the relationship between populations of various migrants from the groups of countries on the graph.

The collected data on analysis can be improved through the following action plan. First, specific quantities per the groups of the countries should be obtained per year. Secondly, their percentages should be obtained from the population of the UK to enhance proportional comparison. These percentages can be represented in a bar graph, as the representation in more accurate, than the line graph since the horizontal continuity in the line graph implies data, even at the points of no quantification.

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The rise in the level of immigrants from other foreign and Commonwealth countries, from 1999 to 2003, had various impacts on the UK due to a diverse composition of migrants. They are considered long-term migrants, as they stayed for more than one year. Socially, this brought a drastic alteration in the UK’s social class, ethnic composition and religious culture among others. The outcome of the movement was enhanced by the UK’s reluctance to exit EU due to the employment benefits associated with the EU membership. This reluctance attracted lots of other foreigners, after foreseeing raise in the UK’s social class, hence higher standard of living.

The content of the graph above was retrieved from the Office for National Statistics in 2013.  The process of obtaining the data involved examination of data that was in the database (records and documents) of the Office for National Statistics. Use of the bar graph as a representation method enhances ease of comparison, as the use of different bar colours, gives the clear distinction of the residence’s percentages. The most appropriate plan that can be applied to improve the quality of this data involves; first obtain the percentages of every group of the residence about all residents per country of birth. The percentages should then be indicated on the bars to enhance ease of identifying the exact quantities. The totals for each group should be added to represent total residents per country of birth. The sum of births per countries can then be plotted on a new bar graph for ease of comparison per country.

Southwark, which appears to have the highest number of residents, experienced an increase in its socio-demographic and lifestyle diversity (Berg, 2015). This led to a rise in diverse languages, hence language barrier, development of mistrust socially and authorities’ fear. The movement towards the origin of the graph from Southward indicates general reductions in some residents per country. This is an indication of the reduction in the social diversities, with Bexley, experiencing the least effect of the diversities generated by the residents.

The data above was collected through the analysis of The Guardian, Observer, Sunday Mail and Daily Mail. This occurred through Lexis Libraries. The focus was on the period between 2014 and 2016, due to the referendum voting that occurred in the same period. The stacked bar graph used for representing this data unveils how the larger cause of migration is divided into subcategories, and how each cause contributes towards the total impact of migration.

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This data can be improved by first, identifying and understanding all its elements. For instances, clarity should be made regarding means of arrival at the bar graphs’ quantification. Secondly, the elements should be defined relevantly for ease of interpretation; that is causes of migration like civil war, unaccompanied should elaborate. Then lastly, validation rules should be specified.

The increase in the positive and negative message of migration in UK in 2016, was enhanced by the UK’s plan to exit EU. This was mainly because most of the migrants were EU citizens. This migrant started experiencing restriction in their movement. The positivity of the messages was mainly composed of reduction in social diversities that enhances social barriers. The negativity involved, issues to do with the drop in the UK’s social class, as the migrants contributed to the country’s standard of living through employment.

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  1. Berg, M., 2015. Resident Involvement in the London Borough of Southwark. London: Compas.
  2. Bryman, A., 2012. Social Research Methods. 4th ed. New York: Oxford Unversity Press.
  3. Pollard, N., Latorre, M. & Sriskandarajah, D., 2008. Floodgates or turnstiles. London: Institute for Public Policy Research.
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