Quantitative and Qualitative Research Methods – Final Module Assessment – October 2021 Cohort
Instructions
Attached are 2 sets of Quantitative and Qualitative data.
Your task is to analyse the data provided and produce a short research report (1200-1500 words) to describe the impact of Covid-19 on university students’ lives.
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In your report, analyse the: a) Quantitative data provided b) Qualitative data provided
and then using your analysis from a) and b):
c) Summarise how students have overall been affected by Covid-19 – This section will be your conclusions.
You must perform some data analysis to write your report. There are no set tasks for you to carry out: you should decide on the most appropriate analysis, based on what you intend to find out. You can use any data analysis software, but please state this in your report. You must explain your methodology (i.e. what analysis did you carry out) and your findings.
Support your explanation with the use of graphs, tables and charts. Take snapshots of your data analysis, and paste these onto the report. You should not be using any data outside the ones provided.
You are advised to produce a balanced report, writing the same amount of quantitative and qualitative content.
Indicative wordcount:
Task a: 450-550 words
Task b: 450-550 words
Task b: 300-400 words
All work must be your own, any work that has evidence of academic improprieties may be subject to penalties and/or awarded a 0 mark, depending on the severity of the academic misconduct.
Please save your report as a Word or pdf file. Name it as follows: preferred name_surname_group_library card number (e.g. Mary_Smith_OPB9_1234567).
Please submit your SPSS, Excel, NVivo, MaxQDA, etc files alongside your report. You must also keep copies of these for future reference.
Please refer to the full FMA brief for additional information and the . Deadline for submission on Moodle is the 11th March at Midnight GMT.
a. Quantitativedatasetinformation
A Social Economic survey has been designed in the UK in order to find out the influences of Covid-19 on Mental Health and Financial Situation of the university students. A subset of this data set including 575 students and 17 variables have selected in a SPSS data set. (UK_Student.sav)
Some variables have measured before and after COVID-19.
Your task:
1. A) You need to define value labels for qualitative/categorical variables according to Table 1.
2. B) Descriptive Statistics
0. Describe the features of these participants briefly by using Descriptive Statistics including appropriate statistical measurements (Mean, SD, percentage, …), tables and graphs. In this part, you just need to describe the Age, BMI, Gender, Health Condition, Level of Study, Marital Status, Wealthy Background and Economic Status.
1. Explore at least three quantitative variables by the categorical variables with reasonable explanation.
2. Demonstrate at least two crosstabs by using the categorical variables, compute the Rows, Columns and Total percentages, and describe these percentages.
Note: Your tables should be concise and clear, and you need to explain them properly. You can support your explanation by the statistical measurements and graphs in a reasonable way.
3. C) Inferential Statistics
You need to define at least five claims (Hypotheses) and test these Hypotheses by appropriate statistical tests and techniques. Your techniques require to include:
iii. One and/or two sample t-test and/or non-parametric tests.
iii. One way and/or two way ANOVA F-test or a non-parametric test.
iii. Finding associations between variables by Chi-square tests and/or Regression Analysis.
Note: For the Hypotheses, you need to explain in a SIAC way, which we mentioned in the classes. You also need to support your finding and results by a clear explanation.
You can ignore normality assumption if it would be violated by the normality tests, but you need to mention that.
Characteristic Variables: Table 1 Characteristic Variables
Variables that have been measured and gathered before and after COVID-19:
1) (SWLS) Satisfaction with life scale. It consists of five items with a seven-point
response format, from “strongly agree” to “strongly disagree”. Scoring:
Though scoring should be kept continuous (sum up scores on each item), here are some cut-offs to be used as benchmarks.
➢ 31 – 35 Extremely satisfied
➢ 26 – 30 Satisfied
➢ 21 – 25 Slightly satisfied
➢ 20 Neutral
➢ 15 – 19 Slightly dissatisfied
➢ 10 – 14 Dissatisfied
➢ 5 – 9 Extremely dissatisfied
2) GHQ 12: Mental distress. Twelve General Health Questionnaire-GHQ, has been used to evaluate mental distress. The GHQ-12 measure has standardized instructions as well as scoring interpretations for the clinician to follow and is administered as a self-report in which the subject is asked to consider 12 questions and how they relate to his or her personal life over the past few weeks. Before and after COVID-19.
Total scores range from 0 to 36 with a score of 11 or 12 considered typical, scores > 15 suggesting evidence of distress, and scores > 20 are considered severe problems with psychological distress.
3) CS: Credit score. Before and after COVID-19.
A credit score is a number designed to represent the likelihood you will pay your bills on time. Higher credit scores generally result in more favourable credit terms.
Scoring : 1 to 710
a) Quantitative guidance and Tips:
1. As a guide, use the methods taught in the course; so conduct appropriate statistical measurements in your own tables, crosstabs and graphs. Conduct appropriate statistical tests for comparisons of the samples and finding associations between the variales. Save your SPSS outputs and write conclusions in your own words to demostrate your understanding of the analysis performed.
2. There is no ‘correct answer’. It is an investigation to determine what conclusions and information you can extract from the data. Students are expected to have different findings and take different approaches.
3. Include any analysis that is statistically insignificant, you are being assessed on your ability to harness appropriate statistical methods and interpret the result correctly.
4. Each time you conduct a statistical test, you should outline what question your analysis is answering/investigating; this will demonstrate your understanding of the statistical process you are using. (Consider the SIAC)
5. There is a wide range of quantitative analyses possible with the dataset, thus given the vast amount of permutations possible there should be no similarities between 2 reports.
6. You may also use any statistical analysis methods to demonstrate further self study that you may have done but this is not a must.
b. Qualitative dataset information
The folder called “qualitative data” shows news about COVID-19 in the UK. The set includes a list of 17 videos in MP4 format.
The topics covered in the news are similar to those in the quantitative study (mental health, financial issues, general student experience when coping with COVID and restrictions).
You should review all data to get a general idea of what college and university students think and how they talk about their experiences.
You are advised to transcribe the content of the videos to make your analysis process easier.
You should then decide upon your research question(s), which will guide your analysis.
Your task:
A) Set a Research Question. This must be applicable to the data provided.
B) Code your data. Remember that your coding needs to be suitable for the type of analysis you wish to perform. Include a coding sheet.
C) Show your categories/themes/concepts. Explain how you have generated these. The process and your focus will be different, depending on your analytical approach.
D) Produce a narrative to describe what emerges from your analysis. Your findings MUST answer your research question and must be grounded in evidence from the data.
E) Include quotes and snapshots from the data. Explain how these support your findings.
F) Include qualitative-appropriate visuals – charts typically used in quantitative research will not be enough.
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