Modules

Core Module Information
Module title: Statistical Research Methods
SCQF level: 11:
SCQF credit value: 10.00
ECTS credit value: 5
Module code: SOE11621
Module leader: Megan Crawford
School The Business School
Subject area group: Management
Prerequisites

None.
Description of module content:

In this module you will learn a selection of scientific approaches to organise and interrogate business-related data. Emphasis is given to data presentation with the purpose of facilitating understanding. The concept of using statistical inference to make judgements and inform decision-making is explained. You will learn how to reduce complex data to relevant variables. The module concludes with an introduction to statistical modelling using linear regression and an overview is given of general linear models.

Exploring and describing data
Statistical inference – parametric methods, t-tests, and Analysis of Variance
Statistical presentation of data
Multivariate methods – exploratory factor analysis and segmentation methods
Statistical Modelling – OLS regression, general linear models
Learning Outcomes for module:

LO1: Demonstrate an understanding of the application, organising and summarising of quantitative data
LO2: Critically assess the statistical significance between and within groups
LO3: Evaluate and apply appropriate data collection methods to your study
LO4: Critically analyse different forms of data to produce research results
LO5: Understand how to construct and diagnose statistical models in research context
LO6: Critically interpret, summarise, visualise, and discuss research results
Full Details of Teaching and Assessment
2022/3, Trimester 2, ONLINE,
VIEW FULL DETAILS
Occurrence: 002
Primary mode of delivery: ONLINE
Location of delivery: CRAIGLOCKHAR
Partner:
Member of staff responsible for delivering module: Joanna McVicar
Module Organiser:


Learning, Teaching and Assessment (LTA) Approach:
The LTA is rooted in the premise that the development of sound knowledge of the role of statistical methods is a cornerstone to the collection, analysis, and modelling of data to support business decision-making and research. The module is facilitated by two research-active academics with inputs from research projects and industry collaborations. The module is run in workshop format over two days and based on a participative and learner-focused pedagogical approach – where you will be encouraged to participate in hands on data analysis and knowledge discovery. Underpinning business and industrial research from both public and private sectors will support and refresh the module content.


Formative Assessment:
Formative assessment will be given in the second workshop session. You will present your analyses and interpretations from a dataset, provided on Moodle. Feed forward will be provided on your methodological approach, data selection, statistical approach, and interpretations of the output.

Summative Assessment:
The assessments are summative and will include an investigation using inferential statistics to address key research questions from a questionnaire created dataset, and a more complex study of linked data in which statistical modelling will be applied. The first report will task you with reporting Bivariate Statistical Analysis and Interpretation. The assessment is modelled after a market research study, where you will have to download qualitative data, develop hypotheses, select appropriate variables from the dataset to address their hypotheses, execute appropriate inferential statistics, and accurately interpret the findings, making industry recommendations. The second report will be a quantitative research report based on a topic of your choice, yet relevant to your degree plan. You will be assessed on your abilities to devise a research aim, generate hypotheses, select relevant data, apply modelling analytic techniques, validate their analysis, interpret, and present your work in a professional report.

Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)
Online Seminar 16
Online Guided independent study 84
Total Study Hours100
Expected Total Study Hours for Module100


Assessment
Type of Assessment Weighting % LOs covered Week due Length in Hours/Words
Report 40 1,2,3 19 HOURS= 00.00, WORDS= 1500
Report 60 4,5,6 21 HOURS= 00.00, WORDS= 3000
Component 1 subtotal: 40
Component 2 subtotal: 60
Module subtotal: 100

Indicative References and Reading List - URL:
Contact your module leader
 

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