Unit Outline

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.

Intended Learning Outcomes

As per the Assessment and Results Policy 1.3, your results will reflect your achievement against specified learning outcomes.

On completion of this unit, you will be able to:


1	Develop and justify research questions and hypotheses
2	Apply principles of qualitative data analysis and quantitative data analysis
3	Apply conventions for reporting analyses and results from qualitative data analysis and quantitative data analysis
4	Derive evidence-based conclusions from data analysis

Requisites


REQUISITE TYPE	REQUISITES
Concurrent Pre-requisite	BAA4xx Designing Research
Anti-requisite (mutual excl)	BMA418, BAA710

Alterations as a result of student feedback

To Be Determined

Teaching arrangements


ATTENDANCE MODE	TEACHING TYPE	LEARNING ACTIVITY	CONTACT HOURS	FREQUENCY
On Campus	Workshop	3 x 3-hour on-campus or online workshops (Wk 1)	3	3 times per week
	Other	Drop-in online consultation sessions (Wk 1)	2	2 times per week
	Other	Drop-in online consultation sessions (Wks 2-3)	1	2 times per week
	Workshop	3 x 3-hour on-campus or online workshops (Wk 4)	3	3 times per week
	Other	Drop-in online consultation sessions (Wk 4)	2	2 times per week
	Other	Drop-in online consultation sessions (Wks 5-6)	1	2 times per week
	Other	5-hrs independent learning	5	Weekly
Online	Online Class	3 x 3-hour on-campus or online workshops (Wk 1)	3	3 times per week
	Online Class	Drop-in online consultation sessions (Wk 1)	2	2 times per week
	Online Class	Drop-in online consultation sessions (Wks 2-3)	1	2 times per week
	Online Class	3 x 3-hour on-campus or online workshops (Wk 4)	3	3 times per week
	Online Class	Drop-in online consultation sessions (Wk 4)	2	2 times per week
	Online Class	Drop-in online consultation sessions (Wks 5-6)	1	2 times per week
	Independent Learning	5-hrs independent learning	5	Weekly

Attendance/Engagement Expectations

It is expected that you will attend all on-campus and onsite learning activities. This is to support your own learning and the development of a learning community within the unit.

If you miss a learning activity for a legitimate reason (e.g., illness, family commitments) teaching staff will attempt to provide alternative activities (e.g., make up readings) where it is possible.

If you are unable to attend regularly, please discuss the situation with your course coordinator and/or our UConnect support team.

The Tasmanian School of Business and Economics regularly hosts Masterclasses and Industry Engagement and Employability Events, which students are encouraged to attend. Registration and details will be available via the College of Business and Economics channel on the Uni App and/or via your Unit Coordinator.

How will I be Assessed?

Assessment schedule


ASSESSMENT TASK #	ASSESSMENT TASK NAME	DATE DUE	WEIGHT	LINKS TO INTENDED LEARNING OUTCOMES
ASSESSMENT TASK 1:	Research Report 1	Week 3	50 %	LO1, LO2, LO3, LO4
ASSESSMENT TASK 2:	Research Report 2	Week 6	50 %	LO1, LO2, LO3, LO4

Assessment details

Assessment Task 1: Research Report 1

TASK DESCRIPTION:

The purpose of this assessment task is to develop and demonstrate your ability to apply your knowledge about rigorous analysis of qualitative data using the NVivo software program. You will do this by undertaking and reporting computer-assisted analysis of qualitative data. This assignment is designed to assess your knowledge and skills related to analysing qualitative data and reporting your research findings.

TASK LENGTH:

3500 words, excluding references and appendices

DUE DATE:

Week 3

WEIGHT:

50 %

CRITERION #

CRITERION

MEASURES INTENDED LEARNING OUTCOME


1	Develop and justify research questions, sub-questions and hypotheses	LO1
2	Select and justify analytical methods and techniques	LO2
3	Execute analysis of qualitative data using NVivo	LO2
4	Apply conventions for reporting analyses and results from qualitative data analysis	LO3
5	Derive evidence-based conclusions from data analysis	LO4

Assessment Task 2: Research Report 2

TASK DESCRIPTION:

During this unit you will have developed knowledge about the principles of rigorous data management and analysis using quantitative data. You will also have also developed practical skills in undertaking rigorous analysis using the SPSS computer software program. The purpose of this assessment task is to develop and demonstrate your ability to apply this knowledge in a practical context by undertaking and reporting computer-assisted analysis of quantitative data. This assignment is designed to assess your knowledge and skills related to analysing quantitative data and reporting your research findings.

TASK LENGTH:

3500 words, excluding references and appendices

DUE DATE:

Week 6

WEIGHT:

50 %

CRITERION #

CRITERION

MEASURES INTENDED LEARNING OUTCOME


1	Develop and justify research questions, sub-questions and hypotheses	LO1
2	Examine hypotheses using descriptive and inferential data analysis techniques	LO2
3	Execute statistical analyses using SPSS	LO2
4	Apply conventions for reporting analyses and results from quantitative data analysis	LO3
5	Develop and justify conclusions from the data analysis	LO4

How your final result is determined

To pass this unit, you need to demonstrate your attainment of each of the Intended Learning Outcomes, achieve a final unit grade of 50% or greater, and pass any hurdle tasks.

Submission of assignments

Where practicable, assignments should be submitted to an assignment submission folder in MYLO. You must submit assignments by the due date or receive a penalty (unless an extension of time has been approved by the Unit Coordinator). Students submitting any assignment in hard copy, or because of a practicum finalisation, must attach a student cover sheet and signed declaration for the submission to be accepted for marking.

Requests for extensions

If you are unable to submit an assessment task by the due date, you should apply for an extension.

A request for an extension should first be discussed with your Unit Coordinator or teaching support team where possible. A request for an extension must be submitted by the assessment due date, except where you can provide evidence it was not possible to do so. Typically, an application for an extension will be supported by documentary evidence: however, where it is not possible for you to provide evidence please contact your Unit Coordinator.

The Unit Coordinator must notify you of the outcome of an extension request within 3 working days of receiving the request.

Late Penalties

Assignments submitted after the deadline will receive a late penalty of 5% of the original available mark for each calendar day (or part day) that the assignment is late. Late submissions will not be accepted more than 10 calendar days after the due date, or after assignments have been returned to other students on a scheduled date, whichever occurs first. Further information on Late Penalties can be found on the Assessments and Results Procedure.

Review of results and appeals

You are entitled to ask for a review of the marking and grading of your assessment task if there is an irregularity in the marking standards or an error in the process for determining the outcome of an assessment. Details on how to request a review of a mark for an assignment are outlined in the Review and Appeal of Academic Decisions Procedure.

Required resources

Required Reading Materials

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