First analyze the data and compile the information in SPSS detailing specific areas and frequencies of the research. Identify the important takeaways from the research and add all non related information into another section giving great detail as to why it may or may not have been pertinent to the study. Key points and notes on how to comprise the fourth chapter is below. Include only data related to the study such as the questions 1 – 24, all other information can be disregarded. With the, data ensure each hypothesis matches with relevant information in the study and identify why it’s important and what information is needed to study further.
Include charts, figures, explanations, footnotes, etc. in great detail
The data analysis section of a psychology survey-based, mixed methods dissertation needs to address both the quantitative and qualitative aspects of your research. Here’s what information to include:
Quantitative Data Analysis:
Description of Survey Instrument: Briefly describe the survey instrument used, including the type of questions (e.g., Likert scale, multiple choice), number of items, and any relevant psychometric properties (e.g., reliability, validity).
Data Cleaning Procedures: Explain how you handled missing data, outliers, and any data transformations performed.
Statistical Techniques: Detail the specific statistical tests used to analyze the quantitative data. This might include descriptive statistics (means, frequencies), correlation analyses, regression analyses, or hypothesis testing (depending on your research questions).
Results Presentation: Present the key findings from your quantitative analysis. Use tables, figures, and charts to clearly illustrate results (e.g., means, standard deviations, p-values, effect sizes).
Qualitative Data Analysis:
Coding Scheme: Describe the coding scheme you used to analyze the qualitative data from open-ended questions or interviews (if applicable). This could be thematic analysis, grounded theory, or another approach.
Data Management Software (Optional): If you used software to manage and analyze qualitative data (e.g., NVivo, Atlas.ti), mention it here.
Themes Identified: Explain the key themes that emerged from your qualitative analysis. Provide illustrative quotes or excerpts from participant responses to support your identified themes.
Integration of Findings (Crucial for Mixed Methods):
Triangulation: Explain how you integrated the findings from your quantitative and qualitative analyses. Discuss how the results from both approaches support, complement, or even contradict each other. This is a crucial aspect of demonstrating the strength of a mixed methods design.
Interpretation and Discussion: Discuss the overall implications of your findings in the context of existing research on the topic. How do your results contribute to understanding the psychological phenomenon you investigated?
Additional Considerations:
Software Used: Briefly mention the statistical software you used to analyze the quantitative data (e.g., SPSS, R).
Limitations: Acknowledge any limitations of your study, including limitations of the survey instrument, sample size, or potential biases.
By providing a clear and detailed explanation of your data analysis methods and results, you can effectively demonstrate the strength and value of your mixed methods dissertation in psychology.
Next, with all the data provided detail the chapter five of the dissertation by hitting all the key point detailed in the template. Information for both chapters four and five.
Lastly comb through the entire dissertation and restructure it from a proposal point of view to a final dissertation point of view. Additionally, separately give a abstract for a dissertation defense with all the information included. A PowerPoint would also be helpful and if costs extra please let me know. Please make sure to include all sources.
All items will be posted for review, files with information regarding the dissertation in the template, and make sure to be detailed in decisions to each figure and how it is or isn’t pertinent to the research. The .SAV is the SPSS file to be ran.
