Highlights
Hypothesis Development
Purpose: The group project is an opportunity for the group to demonstrate their knowledge of the specific issues pertaining to quantitative research covered in the course. Based on the objectives of the study, the group will use appropriate statistical techniques discussed in the class in analyzing the data.
Group Formation: Students are required to self-form their own groups of FIVE (MAXIMUM) to work on this assessment throughout the trimester. This is NOT an individual assessment. Group member names are required to be submitted in writing in the lecture or in the email by the end of WEEK 3.
Report Length and Format: The report should be between 2000 and 2500 words typed using MS Word and 1.5 lines spacing with at least 2.5cm margins, excluding the tables, figures, and appendices.
The following is an indicative structure of your report:
Required:
Design a quantitative study and prepare a report on your research project. Descriptive statistics, at least TWO DIFFERENT bivariate tests, and multiple linear regression tests are required to be used in your project. In particular, you are required to:
1.Identify your research questions
2.Develop the appropriate hypotheses associated with each of the above research questions
3.Apply the appropriate statistical techniques to test these hypotheses
4. Use Microsoft Excel to produce the results
5.Interpret your results from Excel and form the conclusions
6.Make useful recommendations to the relevant users of your report.
Notes:
1.Only provide descriptive statistics for variables used in multivariate analysis (only tables required, no need graphs).
2.Bivariate tests include two independent samples t-test, paired samples t-test, one-way ANOVA, chi-square test, correlation, and simple linear regression.
3.The research topics/scenarios covered in our lecture notes cannot be used in the group project.
4.You must clearly state in the report how you collect your data and measure your variables. If it is a dummy variable, please specify which category is your benchmark. If it is a metric variable, you are required to specify the unit of the variable.
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