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Quantitative Research Methods - study STEM

Quantitative Research Methods

Assessment 1

Congratulations, you have been accepted to be part of a team funded by the council to assess what can be done to encourage young people in the local area to study STEM (science, technology, engineering and mathematics) topics. As part of the project a sample of young adults have been attending fun events your team have set up. Various data have been collected. 

Your team has created a file of all participants in the project, consisting of:

  1. Gender (1=female; 2=male)
  2. Current favourite subject (1=Languages; 2=Sports; 3=Music; 4=Math)
  3. SES* Quartile (1=low; 2=medium-low; 3=medium-high; 4=high)
  4. At least one parent completed higher education (1=yes; 2=no)                          
  5. Engage (level of engagement as reported by staff, higher scores indicate greater level of engagement)
  6. Satis (self-report satisfaction with the events, higher scores indicate greater level of satisfaction)
  7. Baseline (attitude towards STEM before first event)
  8. Week 1 (attitude towards STEM after 1st event)
  9. Week 2 (attitude towards STEM after 2nd event)
  10. Week 3 (attitude towards STEM after 3rd event)

*Socioeconomic status

As the person with the most solid statistical expertise in the team, you have been asked to compile a concise and professional report that will specifically answer the funder and team queries. 

The queries are:

  1. Do attitudes to STEM improve over time, and if so how?
  2. Does having a parent who has completed higher education influence engagement?
  3. Does SES quartile influence engagement levels and gender matter for this? In other words, do gender and SES influence engagement? Provide full analysis.
  4. Your boss wants to know whether there is a difference in satisfaction between those liking languages and those liking math.

Address each query in turn. For each, please provide four, clearly marked, separate sections:  

  1. A description of the analysis process you have decided to implement (similar to what would be found in the methods section of a research paper). In addition, please support your proposed analysis with a justification (e.g., why this statistical procedure is appropriate, including evidence to support this where relevant, and/or whether steps were required to address any problems with data quality). Include any information regarding assumptions here.
  2. A summary of the analyses and findings as would be found in the results section of a research paper (in APA style). In some cases, follow-up analyses may be appropriate. If so, it is up to you to choose which follow-up analyses, but please also provide a brief rationale justifying your choice (1-2 sentences).
  3. Suitable descriptive statistics to enable the reader to understand the findings and conclusions [you will be assessed on accuracy but also clarity so please ensure these are communicated clearly to the reader, be it in text, table or graph format]. Note, if appropriate, you can combine sections b and c though please justify explicitly. Do not include SPSS outputs.
  4. A summary and conclusion communicating to your reader how the analysis has addressed the query, with a brief discussion of possible implications/recommendations taking into account the results.

Marking – each query will receive equal weighting. For each query, marks will be allotted to sections a-d 80% (20% each), with overall impression another 20%. 

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