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Data analysis

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Introduction…………………………………………………………………………………………………………….. 1

Part 1: Text analysis…………………………………………………………………………………………………. 2

Text analysis option 1: analysing a set of interview transcripts……………………… 2

Text analysis option 2: analysis of articles……………………………………………………. 3

Part 2: Quantitative data-analysis……………………………………………………………………………… 4

Quantitative data-analysis tasks…………………………………………………………………. 4

Reflective log/diary…………………………………………………………………………………………………… 5

Assessment criteria…………………………………………………………………………………………………… 5

Length…………………………………………………………………………………………………………………….. 5

A checklist for your submission…………………………………………………………………………………. 5

Part 1: text analysis……………………………………………………………………………………. 5

Part 2: quantitative analysis……………………………………………………………………….. 5

Submitting the assignment………………………………………………………………………………………… 6

Further inquiries………………………………………………………………………………………………………. 6

References…………………………………………………………………………………………………………….. 6

BH7630 data analysis – detailed marking grid (2 pages)……………………………………………… 7

BH7630 Data analysis – overall marking criteria grid…………………………………………………. 9

Introduction

This assignment is in two parts: analysis of text (qualitative data analysis) and analysis of numbers (quantitative data analysis). You must complete both parts. Each part carries equal weight. This assignment accounts for 25% of the module mark. It is not a condition of passing the module that you pass this assignment.

Please consult the end of this assignment document for a list of what you should submit, and how to submit it.

Part 1: Text analysis

The focus of this part is on demonstrating the technical skills of analysing text using thematic analysis techniques. We recommend the “framework” approach (Ritchie and Spencer, 1994) which has been introduced in class. You can combine it with “template analysis” (King 2004) which is similar in many respects.

If you choose Option 2 below you can also draw on systematic literature review techniques in addition to ‘framework’ analysis

For further details and references to ‘template’ analysis and relevant systematic literature review techniques, please see the Online Research Resources folder on StudySpace, and refer to the slides and your session notes.

The skills we asking you to demonstrate are those of:

  • separating those parts of the text relevant to your aims and research questions (i.e., the data) from those parts of the texts that seem irrelevant
  • identifying a set of categories into which to classify the data
  • creating an annotated list of the categories in order to guide the process of categorization (the code book)
  • categorizing segments of data, labelling them with the category names or labels (‘codes’). and validating the consistency of this activity
  • creating data matrices or tables to ‘extract’ and assemble data relevant to each research question (or sub-question)
  • using the data matrices to explore the data and to identify patterns in the data
  • producing a short report answering your research questions, thus demonstrating your ability to begin writing up the analysis

You must choose between the following two options. The assessment criteria are the same for each.

Option 1: analysing a set of interview transcripts

Transcripts of four interviews with construction project managers about their work have been provided on StudySpace. The transcripts have been anonymised to protect the identity of the company, interviewees and interviewers. In these transcripts “education” and “power” refer to types of construction project.

The aim of the analysis is to understand what construction project managers’ work is like from their perspective. The research questions that you need to answer are:

  • What is a project manager’s job like in terms of
  • Who do they report to, and who reports to them?
  • Who are their ‘stakeholders’?
  • What tasks and activities do they perform?
  • What do they like least and most about their work?
  • Why are they doing this job?

The most efficient way to accomplish the tasks is to load the texts into Excel at the earliest opportunity, and work in Excel throughout the analysis stages. If you do any preliminary work on hard copies of the transcripts, you may need to copy this into Excel.

(We strongly advise you against attempting to use any dedicated qualitative data analysis software like Nvivo. It takes a long time to learn how to use these tools effectively, it is not necessary, and it is best to practise the techniques without using these tools.)

Option 2: analysis of articles.

You need to formulate the aims and research questions that determine the focus and direction of the analysis. These are a necessary prerequisite for any analysis.

Identify five good quality research articles reporting the results of an empirical study on a subject relevant to your course (such as for your dissertation). These will be the source text material that you will analyse. Papers reporting empirical study results are easier to analyse than literature review or conceptual papers. This does not preclude you from having research questions on the lines of “What theories, frameworks or models have been used to underpin this study?” or “What are the main propositions of the theory, theories, frameworks or models that have been used to underpin this study?”.

A two stage data extraction process is common in systematic literature reviews. First, relevant characteristics of each article are summarized onto article data sheets. You can adapt examples like the article analysis summary sheet on StudySpace, or those in systematic literature review reports (see references). You can also develop your own new set of categories. In the second stage, these sheets are used to create analysis matrices (like those in ‘framework’). You may take a one- or a two-stage approach for this assignment.

It is difficult to use Excel alone for analysis of articles because it is difficult to turn pdf files into text to import into Excel. For this option we recommend you use Qiqqa, a free program designed for working with pdf files which facilitates a text analysis approach. More details about Qiqqa are provided in a note on StudySpace.
Part 2: Number analysis

The data set was drawn from the British Household Panel Survey (BHPS). You do not need to know anything else about this data set, but if you are interested you can find further information here: https://www.iser.essex.ac.uk/bhps. The research questions for this section are:

  1. a) Are there differences between workers from different types of organisations with regards to their annual gross income?
  2. b) Do the results of examining these potential pay differences change when additionally accounting for employees’ age?

 For task 1. a), ensure that you consider all possible comparisons between workers from the five different types of organisations. For task 1 b), you only need to consider the overall effect of type of organisation.

  1. a) Is there an interrelation between the personality trait openness and overall job satisfaction?
  2. b) Does the result of examining this potential interrelation differ for female and male workers?

For task 2. b), remember that there are different ways to examine differences in the strength of interrelations. Try to find a way to account for openness, gender, and the interaction of both variables (i.e., ‘openness’ by ‘gender’) in one analysis.

 The sample is quite large. Accordingly, it is likely to find significant differences and interrelations. Therefore, you need to carefully evaluate the size of differences and the strength of interrelations.

Quantitative data-analysis tasks

Start with a description of the study sample in terms of demographics and work-related variables. After that, address the research questions above.

For each of the research questions, you have to

  • Select an appropriate statistical technique to answer the research question.
  • Do the analysis.
  • Report the following: (i) State your objective, (ii) explain why you chose which inferential statistical technique, (iii) present and explain the statistical result, (iv) present appropriate descriptive statistics and graphical illustrations that help to understand the result, and (v) briefly describe and explain the finding in words (i.e., what does the statistical finding actually mean, and how could it be explained?).

You need to present outputs of your inferential statistical analyses in the text (i.e., SPSS outputs). You should pay special attention to descriptive statistics, to graphical displays, and to the interpretation of findings. Please note that interpreting findings means more than explaining the statistical output.

Reflective log/diary

You should keep and submit a reflective log/diary of the assignment work.

Assessment criteria

As indicated above, the two main parts of the assignment are text analysis, and number analysis. In addition you should include a short reflective log or diary.

You can find the assessment criteria grids at the end of this document.

Length

We do not expect you to write more than 4,000 words overall for this assignment excluding the analysis materials and related rough working.

 

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