Students will acquire the skills and techniques required to analyse and manage data, interpret results, and report data analysis methods and findings in a business environment. Qualitative and quantitative research approaches are examined to consider theirrespective contributions, discretely and in combination, to knowledge development through empirical research. The quantitative component covers basic statistical thinking and data analysis techniques. A strong emphasis will be placed on the logic underlying statistical concepts such as probability and probability distributions, normal distribution, sampling distributions, parameter estimation, and hypothesis testing. A range of data analysis techniques will also be covered, including t-test, Analysis of Variance, cross tabulation, regression, correlation, and factor analysis. There is a strong emphasis on the application of statistical techniques to practical research problems in a business context. The statistical computer package SPSS will be used for the statistical analysis of data. The qualitative component examines principles and techniques for organising, analysing and reporting qualitative data. The central principle of this component is the execution of rigorous qualitative data analysis through ‘good housekeeping’ –undertaking, recording and demonstrating careful, rational decision-making in qualitative data analysis (Marshall, 1999). Consequently, strategies for undertaking and reporting analysis of qualitative data are equally emphasised. Strategies for data analysis will include techniques for organising, searching, retrieving and interpreting qualitative data to develop and test theoretical conclusions. Strategies for reporting analytical processes will incorporate techniques for recording and describing data analysis, including the articulation of theoretical conclusions and the use of qualitative data to illustrate and support conclusions drawn. Data analysis processes will be undertaken using NVivo, a computer software program for qualitative data analysis.
|Unit name||Data Analysis and Management|
|College/School||College of Business & Economics
Tasmanian School of Business and Economics
|Coordinator||Doctor Saeed Loghman|
|Delivered By||University of Tasmania|
|Location||Study period||Attendance options||Available to|
- International students
- Domestic students
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|Study Period||Start date||Census date||WW date||End date|
* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (refer to How do I withdraw from a unit? for more information).
Unit census dates currently displaying for 2024 are indicative and subject to change. Finalised census dates for 2024 will be available from the 1st October 2023. Note census date cutoff is 11.59pm AEST (AEDT during October to March).
- Develop and justify research questions and hypotheses
- Apply principles of qualitative data analysis and quantitative data analysis
- Apply conventions for reporting analyses and results from qualitative data analysis and quantitative data analysis
- Derive evidence-based conclusions from data analysis
|Field of Education||Commencing Student Contribution 1,3||Grandfathered Student Contribution 1,3||Approved Pathway Course Student Contribution 2,3||Domestic Full Fee 4|
1 Please refer to more information on student contribution amounts.
2 Please refer to more information on eligibility and Approved Pathway courses.
3 Please refer to more information on eligibility for HECS-HELP.
4 Please refer to more information on eligibility for FEE-HELP.
Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.
Concurrent PrerequisitesBAA4xx Designing Research
You cannot enrol in this unit as well as the following:BMA418, BAA710
The unit will be taught in two modules. In both modules, the first week will be an intensive teaching week with module content delivered using a flipped classroom mode. Students will be provided with recorded lectures and demonstration videos. These will be supplemented by workshops in which students can get additional assistance.
Module 1 (NVIVO) – 3 x 3-hour on-campus or online workshops (Wk 1), drop-in online consultation sessions (Wks 1-3); Module 2 (SPSS) – 3 x 3-hour on-campus or online workshops (Wk 4), drop-in online consultation sessions (Wks 4-6).
|Assessment||Research Report 1 (50%)|Research Report 2 (50%)|
|Timetable||View the lecture timetable | View the full unit timetable|
Selvanathan, E.A., Selvanathan, S. and Keller, G. 2017. Business Statistics Abridged (7thedn), Cengage Learning: Melbourne.
Vieira, ET, 2017.Introduction to real world statistics with step-by-step SPSS instructions. Routledge: Milton Park, Ox. (available as hard copy or e-text)
Critical readings on qualitative and quantitative data analysis and management will be supplied. In addition, the publications listed below are highly recommended for further reading on the topics covered in the unit. There is no prescribed text for the unit
Quantitative Data Analysis and Management
Field, A2013, Discovering statistics using IBM SPSS Statistics (4thedn), Sage, London. Ch17 and 19 (available through MYLO)
Pallant, J 2016, SPSS survival manual: a step by step guide to data analysis Using IBM SPSS, 6thedn, Allen & Unwin, Melbourne.
Tabachnick, B & Fiddell, L 2013, Using multivariate statistics,6th edn, Pearson, Melbourne.
Qualitative Data Analysis and Management
Bazeley, P 2013, Qualitative data analysis: practical strategies. Sage, London.
Bazeley, P & Jackson, P 2013, Qualitative data analysis with NVivo, 2ndedn, Sage, London.
Cresswell, JW 1998, Qualitative inquiry and research design: choosing among five traditions, Sage, Thousand Oaks.
Richards, L 2015, Handling qualitative data, 3rdedn, Sage, London.
|Links||Booktopia textbook finder|
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