425Z0087 Quantitative Data Analysis Secondary Data Analysis Report Assessment Instructions & Information Semester 1
425Z0087 Introduction to the Assessment
There are two parts to the QDA Assessment as follows:
Completion of Blue Card (10% of final grade)
Your weekly lab work is linked to the completion of a blue card and will represent 10% of your final grade for this module. The deadline for your blue card to be signed off by a lab tutor is Friday, 29th November 2024.
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Completion of Research Report (90% of final grade)
This will be a quantitative research report due on Monday, 6th January, 9 pm. It follows a similar format to your Level 4 WQE assessment; however, the written requirements are much more detailed. The report is an independent piece of work using secondary data that will be provided to you. It is 2,300 words and is worth 90% of the overall module mark.
This information booklet contains all the information that you need to complete your research report; however, please note that the assignment datasets will not be released on Moodle until Friday, 22nd November at 5 pm, therefore, you will not be able to start working on the assessment until that date.
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It is important that you read this booklet very carefully and that you do not deviate from the instructions about presentation, layout, and content; you will lose marks if you do. In line with the learning outcomes of this module, the purpose of the assessment is for you to demonstrate that you can:
- Use SPSS to produce univariate and bivariate analyses; visualise the results.
- Apply the appropriate statistical method to the univariate and bivariate analysis of categorical and scale variables. This includes testing parametric assumptions and choosing the appropriate inferential, bivariate tests to answer your formulated hypotheses.
- Describe the secondary survey data and methods used to answer a research question and critically evaluate these data and methods by identifying their strengths and limitations.
- Report the findings of bivariate analysis with reference to statistical significance and mean values. Interpret and discuss the findings of your analysis with reference to previous research and the current criminological or sociological policy context.
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Use of generative AI
The use of generative AI is permitted in this assessment, so long as it is used in accordance with the instructions provided in the ‘Are you allowed to use AI in assessments?’ section of the AI Literacy Rise Study Pack. All submitted work must be your own original content. For further info: Rise x Future Me at Manchester Met (mmu.ac.uk)
425Z0087 QDA Marking Rubric – Please Read Carefully
| Section instructions | Outstanding 84+ | Excellent 70-84 | Good 60-69 | More needed 50-59 | Much more needed for 40-49 | Unacceptable 0-39 | Not included |
| Intro & literature review table (weight 10%):
You should introduce the research question and the layout of your report. Signpost the reader as to what to expect. There is no requirement for a literature review, just a literature summary table, including a citation to support the choice of each independent variable. |
The introduction is of an outstanding quality. Very detailed, clear. The justification for hypotheses is supported by a range of credible sources in the summary table, demonstrating a profound understanding of the variables’ choice and their linkage to hypotheses. | An excellent introduction that effectively outlines the report’s structure. The sources used to justify hypotheses extend beyond class materials, showcasing comprehensive knowledge and understanding of the variables and hypotheses. | A good introduction and literature review summary table that provides a clear overview of the report. The justification for hypotheses is supported by credible sources, though there might be a need for a more extensive use of literature to strengthen the linkage between variables and hypotheses. | An introduction that might lack depth or coherence. While attempts are made to justify hypotheses in the literature summary table, the use of credible sources could be more robust and detailed, improving the connection between the literature and hypotheses. | Only a small number of references were used with little evidence of real engagement with the material. The introduction might lack clarity, and the connection between literature sources and hypotheses is weak or missing. | Poor attempt at this section, e.g., incomplete or lack of Introduction, literature summary table, references
No link to hypotheses |
No introduction or literature summary table included |
| Hypotheses (weight 5%):
There should be THREE null and THREE research hypotheses. They should start with the null and then have the research hypothesis. The hypothesis should mirror each other and clearly show what is being tested. |
All hypotheses are clearly and correctly presented. They are also succinct and do not waste any words. They correctly distinguish between tests for difference and tests for relationship. | All hypotheses are clearly and correctly presented. They correctly distinguish between tests for difference and tests for relationship but could be a little more concise. | All hypotheses are clearly and correctly presented but require a little more detail. They may not distinguish tests for difference and tests for relationship. | All hypotheses stated but have some errors of presentation, e.g., lack of consistent mirroring. | Some hypotheses are stated but possibly not the required amount. They are also incorrectly presented, e.g., may not mirror each other, may not include research or null. | Section incomplete, and where hypotheses are included, these are poorly presented, do not mirror each other. | No hypotheses included. |
| Method (weight 20%):
This section should include a brief description of the quantitative data and methods used to answer the research question. This should include a description of the dataset, its year of data collection; who is in the sample; data collection techniques; sampling techniques; details of the variables chosen, and the methods of analysis used. It should also include a critical evaluation of these data and methods by identifying their strengths and limitations with reference to specific data and methods used rather than quantitative data/methods more generally. There should be evidence of understanding that this is an SDA approach, using randomly sampled data and inferential testing to answer the research question. |
Clear and comprehensive description of the data. Clear and concise summary of the methods used.
Well-formulated and focused critical evaluation. This section is supported by citations from a range of credible sources. |
Clear and comprehensive description of the data. Summarises the methods used.
Sound critical evaluation supported by citations. |
Clear description of the data and methods used but with some minor gaps.
Some evidence of critical evaluation but this is more general rather than linked to the specific data and methods used in the report. Some supporting citations included. |
Description of the data and methods is included but with a number of gaps.
Limited evidence of critical evaluation with no supporting citations. The student may have partly demonstrated understanding of the importance of exploratory statistics along with inferential statistics and assumptions but with no sources. There is little discussion on the importance of measurement or link to the SDA approach. The student has not mentioned the sampling strategy and the use of hypotheses. |
Description of the data and methods with many gaps.
No evidence of critical evaluation and no sources cited. The student has not discussed the importance of exploratory/inferential statistics and their assumptions. There is little discussion on measurement or links to the SDA approach. The student has not mentioned the sampling strategy and the use of hypotheses. |
An attempt at this section is included however the data description has many gaps and/or methods are not mentioned at all. No evidence of critical evaluation and no sources cited.
|
No Methods section y Included |
| Univariate (weight 10%):
Briefly explores each of the four variables and presents the findings as outlined in the instructions. You should present a frequency table or measures of central tendency, the relevant graph and descriptive summary for all four variables.
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The univariate analysis is error-free. The appropriate tables and charts are included depending on the variable type. Descriptive summaries are clear and concise and include all necessary information. | The univariate analysis is excellent. The appropriate tables and charts are included depending on the variable type. Descriptive summaries are clear and concise but may omit some of the required information. | The univariate analysis is included for all four variables. It is broadly correct although there are a small number of errors, for example, a frequency table is reported for a scale variable instead of a table including Measures of Central Tendency. The descriptive summaries are wordy and may miss some of the required information such as a relevant percentage or “n”. | All four variables are included in the univariate analysis however it requires more attention as there are a number of errors throughout such as incorrect tables/charts for the variable type and/or incomplete descriptive summaries | The univariate analysis is weak and lacks due care and attention. It is incomplete, has considerable errors and omissions such as a lack of descriptive summaries | An attempt at univariate analysis is included however the section has many gaps and descriptive summaries are not included at all. The univariate analysis is not presented for each variable and what is presented contains considerable errors and is hard to follow. | No univariate analysis included. |
| Bivariate (weight 20%):
This section should include three sub-sections. Each sub-section should present the parametric assumptions, inferential statistics, and descriptive summary for each hypothesis. In each sub-section, you should first report your results from the parametric assumption tests and summarise the parametric test results as your justification for choosing the inferential test you used. Results from all parametric assumptions should be screenshot and labelled. Next, in each sub-section, you should include the results of the inferential test, ending with a descriptive summary where you indicate whether there is evidence to reject the null hypothesis and comment on the differences/relationships that you have found. |
Very detailed, clear and comprehensive knowledge and understanding of the appropriate test to use following parametric tests. This led to the correct statistical tests being used and then interpreted correctly. The null hypotheses correctly accept/ rejected with high quality table summaries. | A clear and comprehensive knowledge and understanding of the appropriate test to use following parametric tests. This led to the correct statistical tests being used and then interpreted correctly. The null hypotheses correctly accept/ rejected with high quality table summaries. Perhaps the table summaries could have been more concise, but these were still excellent. | The bivariate analysis was good, and the parametric assumptions clearly followed leading to the appropriate test being carried out. Some of the table summaries were well written but others did not quite follow the template set out in the assignment instructions. In some areas, the incorrect interpretation of the p values lead to the null hypotheses not being correctly accepted/rejected. | There are some areas where the tests carried out are incorrect. This could be when carrying out the parametric tests when the parametric assumptions were not met, or vice versa. An insufficient rationale of the parametric assumptions was not provided. P values were sometimes incorrectly interpreted leading to the null hypotheses being incorrectly accepted/rejected. | The bivariate analysis is poor and does not include the appropriate number of tests. There are many errors and omissions throughout with the instructions not being followe |