This page is for the academic year 2021-22. The current handbook year is 2022-23
Department: Management and Marketing
Quantitative Methods for Social Science Research I
||Not available in 2021/22
- As specified in Special Regulations
Excluded Combination of Modules
- <If other modules, please enter module code using 'Right Click, Insert module_code' or enter module title>
- Provide students with the advanced quantitative skills necessary to pursue empirical research in micro and macro organisation behaviour;
- Provide students with the advanced quantitative skills required to estimate regression models and interpret the estimates from such models.
- Simple linear regression
- The bivariate model: estimation: the method of OLS; assumptions underlying OLS; recision of OLS estimates; goodness-of-fit; R2.
- Hypothesis testing, tests of significance
- Multiple linear regression
- Specification error
- Dummy variables
- have an advanced knowledge of key quantitative methods and principles
- be able to use several advanced quantitative tools to conduct their own empirical investigations into complex specialised issues, and interpret the results at an advanced level
- have practised problem solving skills at an advanced level and the use of specialised software.
- have enhanced their computer literacy skills;
- have the capacity for sustained independent work and learning at an advanced level and the ability to learn through critical reflection on practice and experience;
- be able to think independently, including problem-solving ability and the ability to operate and exercise appropriate judgement in complex and specialised contexts;
- be able to understand complex research, critically analyse it, and communicate ideas about it to peers;
- have the ability to accept a high level of personal responsibility, including an ability to evaluate and resolve any ethical dilemmas which may arise, in research and professional practice.
Modes of Teaching, Learning and Assessment and how these contribute to
the learning outcomes of the module
- A combination of lectures, seminars and group work will contribute to achieving the aims and learning outcomes of this module. Summative assessment by written examination and applied data analysis will test students' ability to demonstrate what they have learned in the conduct and analysis of a particular issue in depth.
Teaching Methods and Learning Hours
|Preparation and Reading
|Component: Empirical problem sets (in-class)
||Component Weighting: 60%
||Length / duration
|Empirical problem sets (completed in class)
|Component: Written examination
||Component Weighting: 40%
||Length / duration
|Two-hour unseen written examination
Formative assessment, and feedback, may take a number of forms such as answers to questions discussed during workshops, or posted on DUO; discussions with teaching staff during consultation hours, or via e-mail.
■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University