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The Process of Data Analysis

Introduction

The process of data analysis starts immediately after the data is collected. It intends to examine, clean-up, transform and model the collected data to bring out the useful inference in order to make correct decisions. Caution is that the process of data analysis does not correct any bias in the data if it was collected in a biased way. Thus the quality of the data should be stressed before data analysis. Data analysis must take into account of the need, type, and purpose of the analysis. Different data analysis methods will only suit certain agendas (Bryman & Bell, 2007).

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Data analysis entails noticing, thinking, and collecting the unique ideas in the data collected. Analysis will depend on the purpose and the need for the report. The best analysis will need one to either focus on the question, time, period, event, or the topic that the data was collected; in this case the question is the focus since the topic is not available. First one has to read and re-read the data so as to understand the data (Krueger, 1998).

During the reading one should jot down any impression that comes from the data; this will make one identify consistencies and differences in the data. Noticing will engage what will and should be noticed, and the process to noticing them. This is followed by coding of the information noticed. The best method of data analysis that will be used to analyze the given data will be content analysis (Krippendorff, 2004).

The content analysis

Content analysis is a comprehensive method of data analysis that determines what statements of respondents mean. The content analysis gives the better option of analyzing the narrative data provided since it analysis what the respondents have raised in their answers. It also helps to know how the statements relate and establish the emphasis which the respondents put forward. The Open-ended question from a survey of negative workplace relationships: “Please briefly outline how your work environment has made worse a negative relationship you have had at work” gives the basis of the data analysis (Bryman & Bell, 2007). The respondents were taken from a random sample from the administered question.

As cited by Stemler (2001) in the article “An overview of content analysis” there are six questions that should be addressed in any content analysis, these are; “Understand data being analyzed, how it should be defined, Know the population which its being drawn form, context relation on the data being are analyzed, boundaries of analysis and inferences target.”

The question may be from an interview or a question where the respondents gave their feeling on the environment at work could have worsened a negative relation they had at the workplace (Renner, 2003). According to the data given the respondents come from a wide range of professions, workplace, ranks, gender, and experiences. A total of 115 answers are issued in the data from the huge sample of respondents. This may have made up a representative sample of the respondents.

Analysis of the qualitative data would first involve reading the answers given. Noticing the given answer will be an easy task since it will involve checking the same answers or closely related answers given by the respondents. The noticed pattern of data will be recorded on spreadsheet with each narrative answer analyzed to give a short precise answer or phrase that will allow easier inference (Weber, 1990).

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The phrase will explain the idea, concept, behavior, interactions, feelings, or problem stated by the respondents of the question. The phrase will be stated in such a way that it summarizes the meaning of each statement from the respondent and what he/she intended to express.

Rules of content analysis

The set rules and regulations for content analysis are theory driven and are; firstly the amount of data analyzed at a particular time should be state and adhered to. This means that when you state a phrase, line, paragraph, or sentence to code data it should be consistent to the end. Secondly, is what is mean by each category used? The categories should be either inclusive or exclusive. Thirdly, is that the categories must be defined precisely on each property (Renner, 2003).

The few narrative answers from the respondents were as follows; “It encourages competition, especially since one is measured by “who has most projects” that also creates a lonely environment and reduces real team work.” “Poor performance from other person who I have a negative relationship with made me angry and affected my judgment”, “The negative relationship dominated the work place to such an extent that work colleagues became divided into two clear distinct groups. It made the work environment very stressful for all involved and in the end the bastard had to leave!”, “Time pressures can mean that there is not enough opportunity to discuss problems adequately”, “I’m a designer – the company is roughly divided into ‘account teams’ who deal with the clients and admin, and the ‘studio’ where all production and creative staff work. Where I currently work, the workplace is divided into upstairs for studio, and downstairs for account teams. The physical separation exaggerates any (and many!) differences the two parts of the company have and definitely contributes to an ‘us’ and ‘them’ attitude for both sides”, “When one became a supervisor and we were under him. He thought he was better then us and stopped hanging out with us” “Usually in a negative relationship I avoid the person in question. In the work environment I am required to maintain a level of professionalism, which requires me to put aside differences and work with that person, which seems to add more strain to the situation because you both know that neither of you wants to be involved”, “Too much work puts me under stress and so makes me grumpier before speaking with the person I don’t like” and “Boss again – sometimes there can be weeks we don’t speak to each other – he just comes and dumps the work on my desk and leaves the room” among others.

For the above statements different inferences are made, the phrases given for the above answers may be; reduce team work, resignation, time wastage, crisis, disagreements, tension, stress, low concentration, and boredom, pressure, under performance, firing of employees, excommunication, and enmity. Each of these inferences will have a code or category that will be given to simplify the initial statement given (Silverman & Marvasti, 2001). Due to the bulk of data the phrases may be numerous so that to incorporate everyone’s views. The statements must also be sampled randomly and inferred in the correct way possible to avoid bias; they should also be very clear and precise to avoid ambiguity or double statements.

Uses of content analysis

There are three categories of content analysis. They are; being able to make an inference of the statements given, describing the characteristics of communication, and giving the effects of communication. Content analysis is used in terms of purpose, question, and communication constituent. On the part of communication constituent issues such as; source, encoding and decoding procedure, channel, message, and recipient (Creswell, 2009).

The specific uses include; answering queries of disputes, analyzing; individual traits, techniques, styles, and evaluating evidence. It is also important to describe communication patterns, contents, standards, sources, and response. It also assesses the information flow, communication response, inference of personal life conditions (Denzin & Lincoln, 2008). In the data provided the analysis will seek to reveal the effect of a negative workplace relationship on the work, detect the existing problems, give the attitude and behavior of the respondents, and the effects that finally occur.

Types of content analysis

There are two types; the conceptual and relational analysis. In conceptual a specific model is identified for analysis and the frequency of occurrence is recorded. This method was the traditional content analysis. The rules may either be explicit or implicit hence they should be clearly defined before analysis (Creswell, 2009).

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One must first identify the research question and samples to be used. This is followed by coding or categorizing in to manageable sizes. The meaning is the inferred from the units of information and communication that are analyzed and inferred. Relational analysis is based on conceptual analysis which also examines texts for any relationship (Patton, 1990). This method is more flexible and one can decide which concepts will be analyzed.

The advantages of content analysis

Content analysis offers various pros when used in analysis. Firstly, it works on the communication of text and sentences directly; this is important since the key issues of the statements are addressed. Secondly, it is flexible to allow both qualitative and quantitative data analysis (Denzin & Lincoln, 2008).In addition it gives significant insight for a given period of time for the text analysed.

It also gives allowance text analysis which relate categories and relationships and statistical analysis of coded texts and sentences (Janesick, 2003). It is used to infer information for specific purposes in the society, while it is an unmistakable means of investigating interactions. It is also very important in establishing complex models of social structure thus it can be an exact data analysis research method.

Limitations of content analysis

Content analysis offers various cons when used in analysis. Firstly, it is time consuming given the nature of data to be analyzed. Secondly, when relational analysis is applied then there can be increased errors. It also has no theoretical base and hence any inference is based on understanding the relationships. It is also not easy to computerize or automate the system of data analysis since it is mostly based on words (Denzin & Lincoln, 2008).

Conclusion

Data analysis can be a long process but can be simplified when the correct analysis method is applied. The process of data analysis should be thorough and intensive to give the correct inference. With narrative qualitative data content analysis would be useful and most appropriate to induce the information. The content analysis gives us the better option of analyzing the narrative data provided since it analysis what the respondents have raised in their answers. It also helps to know how the statements relate and establish the emphasis which the respondents put forward.

For the Open-ended question from a survey of negative workplace relationships: “Please briefly outline how your work environment has made worse a negative relationship you have had at work” analysis will be easy when content analysis is used. If data is used to make any inference in a report then it must be analyzed perfectly so as to make correct decision in management.

References

  1. Bryman, A. & Bell, E. (2007). Business Research Methods. Oxford: Oxford University Press.
  2. Creswell, J. (2009). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. Thousand Oaks: Sage Publications.
  3. Denzin, N. & Lincoln, S. (2008). Collecting and Interpreting Qualitative Materials. Thousand Oaks: Sage Publications.
  4. Janesick, V. (2003). Stretching Exercises for Qualitative Researchers. London: Sage.
  5. Krippendorff, K. (2004). Content Analysis: An Introduction to Its Methodology. Newbury Park: SAGE Publications.
  6. Krueger, A. (1998). Analysing and Reporting Focus Group Results. Thousand Oaks: Sage Publications.
  7. Patton, Q. (1990). Qualitative Evaluation and Research Methods. Newbury Park: Sage Publications.
  8. Renner, M. (2003). Analyzing Qualitative Data. Madison, Wisconsin: University of Wisconsin.
  9. Silverman, D & Marvasti, B. (2001). Doing Qualitative Research: A Comprehensive Guide. Los Angeles: Sage Publications.
  10. Stemler, S. (2001). An Overview of Content Analysis. Practical Assessment, Research & Evaluation. 7(17), 78-92
  11. Weber, P. (1990). Basic Content Analysis. Newbury Park: Sage Publications.

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