Data Analysis and Findings in Thesis Chapter 4

Here are the detailed bullet points summarizing the text:

• The speaker is discussing Chapter 4 of a thesis or dissertation, specifically data analysis and findings.

• The speaker shares their experience of having a problem with a YouTube link, which was resolved by creating a new link.

• The speaker emphasizes that Chapter 4 is a crucial part of the thesis, as it presents the data and findings, which is the student's own work.

• The speaker explains that there are two groups of academics: one that believes Chapter 4 should only present findings, and another that believes it should present both findings and discussion.

• The speaker personally belongs to the first group, believing that Chapter 4 should only present data analysis and findings, and Chapter 5 should include the discussion.

• The speaker advises students to follow their university's guidelines and regulations for writing Chapter 4.

• The speaker highlights the importance of presenting data in a clear and scholarly manner, using tables, graphs, and figures to facilitate reader understanding.

• The speaker explains that the data presentation section should introduce the chapter, summarize background information, and indicate the order of presentations.

• The speaker emphasizes the importance of highlighting the unique contributions of the research and avoiding table reading, where the student simply replicates the data from the tables.

• The speaker explains that the analysis of data should be done in a logical and transparent manner, following the sequence of research questions and objectives.

• The speaker advises students to use a consistent and coherent approach to data analysis, following academic conventions and referring to real theses as examples.

• The speaker discusses the importance of using the right software for data analysis, such as SPSS, Stata, or Smart PLS, and following the guidelines for each software.

• The speaker provides examples of suggested contents for Chapter 4 using different software, such as Stata and Smart PLS.

• The speaker explains that qualitative research studies present findings in a thematic way, following a research question or theme, and may use software such as NVivo or Atlas.ti.

• The speaker advises students to summarize their findings at the end of Chapter 4, highlighting the key contributions of their research.

• The speaker opens up the session for questions and answers, and several participants join in to ask questions and share their experiences.Here is a summary of the text in detailed bullet points:

• In calculating response rates, the minimum sample size is crucial, and it's unacceptable to have fewer responses than the minimum required.

• The response rate varies across countries and industries, and it's essential to achieve the minimum sample size for data analysis.

• When determining the minimum sample size, refer to tables such as Uma Sakura or Christian Morgan's table.

• If the minimum sample size is 384, and you collect 410 responses, you can use all 410, but you cannot have fewer than 384.

• In a thesis, you will never have both a theoretical framework and a conceptual framework; it's either one or the other, depending on the study type (quantitative or qualitative).

• For a quantitative study, you use a theoretical framework, while for a qualitative study, you use a conceptual framework.

• In a quantitative study, you start with a theory, but in a qualitative study, you start from zero and build concepts.

• For data analysis in a quantitative study, you may use software like SPSS, Stata, or SmartPLS, depending on the type of data.

• When using SmartPLS, you don't need SPSS, and you can export data from Excel to SmartPLS.

• In Chapter 4, you present findings, and in Chapter 5, you discuss the findings and make your voice louder.

• In a mixed-methods approach, you can use both qualitative and quantitative methods, and you can use software like SmartPLS and SPSS together.

• In social science research, you need to present demographic profiles of respondents, unlike in pure science research.

• R-square (R2) measures the explainability of a model, and it's essential to report it in your study.

• In qualitative research, you don't need a hypothesis, and you should have a conceptual framework, not a theoretical one.

• When presenting findings in qualitative research, you should highlight important themes and sub-themes.

• You don't need to include all transcribed interviews in your thesis; only highlight the important ones.

• In coding manually, you can use techniques like Brown and Clarke's thematic analysis, but it's recommended to seek guidance from a qualitative research expert.

• When running mediating and moderating variables, it's essential to learn the software and understand the protocols.

• There are various formulas for determining the minimum sample size, such as the sample determination table and the Krishi and Morgan table.

• You can use software like G*Power to determine the minimum sample size.

• In the discussion section, you should write implications, which will be covered in a future session.

• Critical interpretation of findings is essential in Chapter 5, where you discuss the implications and contributions of your study.

• When using different research tools that measure the same construct, you can refer to previous resources and use the tool that's most suitable for your study.

• If you have a large population, you can refer to tables like the sample size determination table to determine the minimum sample size.

• The speaker will provide the Chapter 4 slides and certificate for attendees who fill out a form during the next session.