BA6060 - Quantitative Data Analysis (2018/19)
| Module specification | Module approved to run in 2018/19 | ||||||||||||
| Module status | DELETED (This module is no longer running) | ||||||||||||
| Module title | Quantitative Data Analysis | ||||||||||||
| Module level | Honours (06) | ||||||||||||
| Credit rating for module | 15 | ||||||||||||
| School | Guildhall School of Business and Law | ||||||||||||
| Total study hours | 150 | ||||||||||||
|
|||||||||||||
| Assessment components |
|
||||||||||||
| Running in 2018/19(Please note that module timeslots are subject to change) | No instances running in the year |
Module summary
This module introduces students to the advanced statistical techniques for business research. The module takes over from the skills picked up at level 4 and 5 in particular, the quantitative skills taught and assessed. It re-visits techniques already seen in previous modules but introduces advanced statistical techniques as required in research and dissertation. Indeed, this module provides a support for the analysis section of the final year dissertation for the Business and Management and related courses, particular for those students who chose to follow a positivist paradigm.
The module enables students to gain lifelong and employability skills such as data analyst.
The key skills taught and assess on the module will include advanced use of SPSS in statistical analysis and reporting.
Syllabus
The syllabus is flexible and may contain many of the following topics:
• The positivist paradigm and its advantages
• The formulation of research questions and hypotheses
• The importance of “measuring” data LO1
• Variable and data entry on SPSS LO2
• Parametric and non-parametric tests
• Basic descriptive statistics and univariate statistical analysis
• The Chi-squared test
• The t-Test for comparing averages – Independent and paired samples
• Test for comparing proportions
• Analysis of variance - ANOVA
• Multiple regression analysis
Balance of independent study and scheduled teaching activity
The quantitative data analysis module is designed to encourage students to work independently using their own data, to a significant extent.
Learning outcomes
• Apply an appropriate instrument to collect the required data related to some research questions [LO1]
• Apply appropriate statistical techniques to respond to research questions [LO2]
NOTE:.please consider what is the appropriate number of LOs for a module at this level and with this credit rating.
Assessment strategy
In describing the assessment strategy, describe how:
• Students will be asked to use appropriate techniques of quantitative data analysis for business variables or concepts. They will either collect (or be given data) to respond to research questions or test hypotheses.
Bibliography
Identify core and additional reading
Liaise with Library Services to confirm availability of on-line licenses in academic year
Where possible, the most current version of reading materials is used during the delivery of this module. Comprehensive reading lists are provided to students in their handbooks. Reading Lists will be updated annually.
Textbooks:
Core Text: David R. Anderson, Statistics for Business and Economics, 2014, Cengage
Other Texts: Zikmund & al, Business research methods, 2009, Cengage publication
Journals: To be added
Websites: To be added
Electronic Databases:
Social Media Sources
Other