Lecture: Professor Dr Chen Chwen Jen

Group: GO3- D

Jahmiahton Binti Abdul Jalil (99223)

1. Purpose: Used test hypothesis and confirm existing theory.

2. Data type: Data is typically expressed in numbers and graphs.

3. Sample size: A larger sample size is required to achieve statistically significant findings.

4. Data analysis: Data is analyzed using mathematics and statistics.

1. Purpose: Used to develop a hypothesis and understand or explore an idea.

2. Data type: Data is expressed in words.

3. Sample size: Requires fewer respondents compared to quantitative research.

4. Data analysis: Analyzed by summarizing, categorizing, and interpreting the textual data.

• Qualitative research is defined as the systematic collection, organization, and interpretation of textual data. The term "strategy" emphasizes the fact that qualitative research is a deliberate, thoughtful process that takes into account context as well as the strengths and limitations of qualitative methods.

• It is a systematic collection, organization, and interpretation of textual data. It is designed to address phenomena that are difficult to measure quantitatively, reflecting the idea that "not everything that can be counted counts and not everything that counts can be counted".

• It also typically uses inductive methods. This means that it works "from the ground up" to investigate phenomena in order to develop understanding and generate hypotheses.

1. Creating an in-depth analysis of processes, mechanisms, or settings.

2. Providing detailed descriptions of participant perspectives and experiences.

1. https://www.youtube.com/watch?v=wbdN_sLWl88&pp=ygUUcXVhbGl0YXRpdmUgcmVzZWFyY2g%3D (Youtube)

1. https://www.youtube.com/watch?v=a-XtVF7Bofg&pp=ygUUcXVhbGl0YXRpdmUgcmVzZWFyY2g%3D (YouTube)

2. https://notebooklm.google.com/notebook/a41ce2f3-450c-4e1a-9dae-ff2d55c1c61e?authuser=1 (Google Notebook LM)

3. Lim, W. M. (2024). What is quantitative research? An overview and guidelines. Australasian Marketing Journal (AMJ). https://doi.org/10.1177/14413582241264622 (Journal Article)

Writing content about quantitative research helped me understand the structure and precision required for this approach. I used to believe that research was primarily about conducting surveys and analyzing the results, but I've learned that numbers and statistical analysis are at the heart of many studies. Learning about hypothesis testing helped me understand how researchers use data to prove or disprove claims. It taught me that every good quantitative study starts with a strong hypothesis and concludes with a meaningful interpretation supported by evidence. This understanding will help me create a more detailed process for future projects.

1. Create the hypothesis.

2. Choose the significance level.

3. Choose the appropriate statical test.

4. Collect and organize data.

5. Calculate the test statistic.

6. Determine the p-value.

7. Make the decisions.

8. Report the results.

9. Consider the possibility.