DAA 401REQUIREMENTSFOR
DATAANALYSISASSIGNMENT
Contribution to grade: 30% Due: 25 May 2020
The primary objective of this assignment is to increase and subsequently assess your understanding about undertaking and reporting quantitative empirical analyses (CLOs 3, 4). Such skills should also enhance your ability to critically assess other empirical research, as well as inform decisions on methodological and analysis choices as you develop and examine research questions in the future (i.e., partially draw on CLOs 1,2).
For this assignment, you are given a dataset (in .sav and .xls format) that contains a sample of 200 responses. This dataset provides the basis for you to complete some empirical analysis.
This sample is a random subset of a larger sample (N=260) used in the published article on location-aware mobile advertising (see Richard & Meuli, 2013). For this assessment, you need to identify a novel research question drawing on the variables in the dataset and state associated hypotheses, in a testable form. Novel, here, refers to a hypothesis that the article does not state and/or test. Please note that the dataset has been reduced and altered from the original – which may mean that your analysis and results of similar hypotheses could differ substantially from those reported in the article. Next, you need to undertake quantitative analyses of your hypotheses and report the results appropriately.
You should begin your preparation by reading thoroughly through the published article and the questionnaire items utilised in the original survey. Next, assess which variables you might expect to be systematically related and express your focal relationship(s) in the form of a research question and hypotheses. Carefully choose the wording for your hypotheses as this may affect how best to test for differences and relationships. Analyse the data using appropriate quantitative statistical techniques. It does not matter if your hypotheses are supported by the data – the assessment considers whether testable hypotheses have been formed and whether the techniques have been used and reported correctly. One of the tests of a hypothesis that you report should be a multivariate analysis, where you assess whether the relationship between your focal variables is affected when other potentially related variables are included in the analysis concurrently.
Your completed data analysis assignment should:
- identify a novel research question that relates to the variables in the dataset provided, including rationales for what you view investigating this question would inform;
- develop and clearly articulate one or more testable hypotheses associated with this research question that 1) compares the means across subsamples within the dataset, as well as 2) allowing for a multivariate assessment of one (or more) of your hypotheses, that is, where the comparison(s) of interest are assessed while controlling for the potential effects of other variables via a multiple regression or an ANOVA;
- evaluate briefly the extent to which the sample that you will use for your analysis is a particularly suitable one given the population to which your research question relates. What are the sample’s strengths and limitations – fully support your assessment;
- complete appropriate quantitative analyses that allow you to indicate if the hypotheses are/are not supported;
- summarise and contrast the findings from your quantitative analyses;
- document the implications of the findings and how you chose to analyse the data; and
- indicate any limitations of your analyses.
The marking rubric for this assignment matches the criteria noted in the bullet points above. It will be used, in part, to provide you with feedback across this range of areas in a concise manner.
The maximum word limit for addressing the bulleted points is 2,000 words. Please stick to this limit! Appendices should include copies of tables, outputs, … from your analysis as support. They may be referred to (but are not marked) when the details you report for the hypothesis tests require clarification. All marks will be associated with how you summarise your analyses in the body of your assignment. Full and correct citation of articles in APA format is required. Structure and style, clarity and conciseness, technical writing skills and vocabulary also contribute to the effectiveness of communication in your assignment.
The data analysis is to be submitted through Blackboard by 4:00pm Thursday 25 May 2020 using a .pdf or .doc format. No printed copies need to be submitted as the assignment will be marked online.
Format
Spacing & Font: 1.5-spaced, Times New Roman, font size 12 preferable.
Late Submission:In fairness to other students, work submitted after any deadline will incur a 5% penalty (of the mark obtained) for each day late, including weekends. In the event of bereavement or prolonged illness affecting your ability to meet deadlines, discuss your situation with the Course Coordinator. You must substantiate your claim with appropriate documentation, for example, a medical certificate.
Key reference:
Richard, James E. & Paul G. Meuli (2013). Exploring and modelling digital natives’ intention to use permission-based location-aware mobile advertising. JournalofMarketingManagement, 29(5-6): 698-719. DOI: 10.1080/0267257X.2013.770051
| Courselearningobjectives(CLOs) | Students who pass this course should be able to: |
| 1 | Compare scientific methods and methodologies, advantages and disadvantages relative to other research paradigms, and related research methods in business. |
| 2 | Construct a critical evaluation of literature relevant to an area of enquiry. |
| 3 | Design logical arguments and/or hypotheses from the literature and theory. |
| 4 | Plan and produce methods to appropriately analyse and interpret the results. |
| 5 | Design and present a comprehensive, scientific research project related to a business issue relevant to identified stakeholders. |
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