Data Analysis and Management
PostgraduateTAS-BAA7102025
Course information for 2025 intake View information for 2024 course intake
- Study method
- 100% online
- Assessments
- 100% online
- Enrol by
- 25 May 2025
- Entry requirements
- Part of a degree
- Duration
- 6 weeks
- Price from
- $3,128
- Upfront cost
- $0
- Loan available
- FEE-HELP available
Data Analysis and Management
About this subject
Upon completion of this subject, the student should be able to:
- 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
- Module 1: Qualitative Data Analysis using NVivo
- Setting up your NVIvo project
- Importing and organising data files
- Recording decisions, processes
- Organising data using cases and case classifications
- Coding data using NVivo
- Developing your code book
- Coding validity
- Reporting on qualitative data analysis
- Autocoding
- Checking reliability and consistency of coding
- Using coding to answer your research questions
- Using coding to explore associations
- Reporting findings from qualitative data analysis
- Module 2: Quantitative Data Analysis using SPSS
- Getting started with SPSS
- Testing for difference
- Testing for association
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 their respective 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.
- Research Report 1 (50%)
- Research Report 2 (50%)
For textbook details check your university's handbook, website or learning management system (LMS).
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Entry requirements
To enrol in this subject, you must be admitted into a degree.
Additional requirements
- Other requirements - Teaching Arrangement: In each module students will be provided with a suite of online materials that will include Pre-recorded content lectures, Video demonstrations of software usage, Practical activities to guide students through the execution of analytical tasks using the software programs. During the teaching weeks, teaching staff will supplement the online content with real-time interactive teaching sessions.
Study load
- 0.125 EFTSL
- This is in the range of 10 to 12 hours of study each week.
Equivalent full time study load (EFTSL) is one way to calculate your study load. One (1.0) EFTSL is equivalent to a full-time study load for one year.
Find out more information on Commonwealth Loans to understand what this means to your eligibility for financial support.