Research, Data, Data Analysis and Report Writing
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The document outlines the research process and various methodologies, including primary, secondary, and tertiary sources, as well as analysis techniques such as cost/benefit, life-cycle, comparative, process, and sustainability analyses. It discusses the importance of ethical data practices and provides a structured approach for report writing, emphasizing various sections like the abstract, introduction, results, and discussion. Additionally, it highlights the systematic nature of research in generating knowledge and making evidence-based decisions.
Research, Data, Data Analysis and Report Writing
- 2. Defining Research Research: the systematic process of discovering more about something than you already know, ideally so that you can prove a hypothesis, produce new knowledge and understanding, and make evidence-based decisions. Research Methods: techniques of collecting, sorting, and analyzing information/data.
- 3. Primary Sources Primary Sources: research you might conduct yourself in lab experiments and product testing through surveys, observations, measurements, interviews, site visits, prototype testing, beta testing, etc. These include published statistical data, historical records, legal documents, firsthand historical accounts, and original creative works.
- 5. Tertiary Sources Tertiary Sources: reference sources such as dictionaries, encyclopedias, and handbooks that consolidate primary and secondary information. They help you understand your topic and the field's significant concepts, lines of inquiry, or schools of thought.
- 8. Data Analysis Cost/Benefit Analysis: determines how much something will cost vs what measurable benefits it will create. Life-cycle Analysis: determines the overall sustainability of a product or process, from manufacturing through lifetime use to disposal (you can also perform comparative life-cycle analyses or specific life-cycle stage analysis). Comparative Analysis: compares two or more options to determine the “best” solution (given specific problem criteria such as goals, objectives, and constraints). Process Analysis: studies each aspect of a process to determine if all parts and steps work efficiently together to create the desired outcome. Sustainability Analysis: uses concepts such as the “triple bottom line” or “three pillars of sustainability” to analyze whether a product or process is environmentally, economically, and socially sustainable.
- 9. Cost/Benefit Analysis: Outcome: By comparing costs to measurable savings and environmental benefits, the analysis concludes the project will break even in 10 years and generate long- term savings. A city government is deciding whether to install solar panels on municipal buildings. The upfront cost is $500,000, but the panels are expected to save $50,000 annually in energy costs and reduce carbon emissions by 200 metric tons per year.
- 10. Life-Cycle Analysis: Example: A company evaluates the sustainability of two types of packaging: cardboard and plastic. Process: The analysis considers raw material extraction, manufacturing energy, transportation emissions, durability, and end-of-life disposal or recycling. Outcome: While plastic is more durable, cardboard has a lower carbon footprint over its entire life cycle, making it the more sustainable choice.
- 11. Comparative Analysis: Example: An organization needs a transportation solution for employees and compares three options: providing bus passes, installing bike racks, or offering carpool subsidies. Criteria: Costs, employee participation rates, carbon emissions reduction, and ease of implementation. Outcome: Providing bus passes is identified as the best solution, meeting the objectives of cost-effectiveness and sustainability.
- 12. Process Analysis: Example: A factory reviews its manufacturing process for a new product. Steps Analyzed: Raw material procurement, assembly line efficiency, and quality control procedures. Outcome: The analysis reveals that automating the material-handling step could reduce production time by 15% without compromising quality.
- 13. Sustainability Analysis: Example: A corporation assesses a new product against the triple bottom line: Environmental: How much waste and emissions does production generate? Economic: Is the product cost-effective and profitable? Social: Does it create local jobs or improve community well-being? Outcome: The product passes environmental and social criteria but fails economic feasibility, prompting the company to revise its cost structure before proceeding.
- 14. Data Standards Collecting, analysing, and using data must be ethical and consistent with professional standards of honesty and integrity. Lapses in integrity can not only lead to poor quality reports in an academic context (poor grades and academic dishonesty penalties), but in the workplace, these lapses can also lead to lawsuits, loss of job, and even criminal charges.
- 15. Report Structure Title: Craft a descriptive and informative title to let readers decide if this interests them and allow keywords to be abstracted in indexing services. Abstract: write a summary of your report that mirrors your report structure (Hypothesis, Methods, Results, Discussion, Conclusion) in condensed form—roughly one sentence per section. Ideally, sum up your important findings.
- 16. Report Structure Introduction: establish the context and significance of your work, its relevance in the field, and the hypothesis or question your study addresses. Please briefly overview your methodology for testing your hypothesis and why it is appropriate. If necessary for your readers, provide a specialized theoretical framework, background or technical knowledge to help them understand your focus and how it contributes to the field. More detailed reports may require a Literature Review section.
- 17. Report Structure
- 18. Report Structure You can organize this section based on chronology (following your methodology) or on the importance of data in proving (or negating) the hypothesis (most important to least important). Present data visually whenever possible (in tables, graphs, flowcharts, etc.), and help readers understand the context of your data. Results: This section presents the raw data you generated in your experiment and provides the evidence you need to form conclusions about your hypothesis. Present only the data relevant to your results (but if you omit data, you may have to explain why it is irrelevant).
- 19. Report Structure Acknowledging that your generated data is problematic or fails to support the hypothesis is perfectly fine. This points the way for further research. If your findings are inconsistent, try to suggest possible reasons for this. Discussion: this section includes your analysis and interpretation of the data you presented in the Results section regarding how well it supports your original hypothesis. Start with the most important findings.
- 20. Report Structure
- 21. Report Structure
- 22. Report Structure Appendices: any information that does not fit within the body sections but still adds valuable information to your report can be placed in an appendix. Where your Results section may present summarized data, all the data tables may appear in an appendix. You may also include logs, calculations, or notes on analytical methods. Be sure to refer to the appendices in the body of your report to indicate where readers can find additional information.
- 23. ANSWER IN THE COMMENTS FOR A CERTIFICATE What is the difference between Life-Cycle Analysis and Comparative Analysis? What is the difference between Quantitative and Qualitative Data?