Module: Statistics for Business

Latest Module Specifications

Current Academic Year 2025 - 2026

Module Title	Statistics for Business
Module Code	BAA1082 (ITS: MT5154)
Faculty	DCU Business School	School	DCU Business School
NFQ level	9	Credit Rating	5

Description

Data Collection, Analysis and Reporting for Business

Learning Outcomes

1. Differentiate between different types of data sources / measurement types
2. Use descriptive statistical and data visualisation techniques to summarise business data sets
3. Explain the nature of sample error and calculate this error for a number of sample parameters
4. Choose the appropriate statistical techniques for testing a variety of statistical hypotheses
5. Interpret statistical output and effectively present the results of this output
6. Provide an overview of the role of statistics in an increasingly data driven business world. Demonstrate the role of statistics in designing sustainable strategies with focus on eco-efficiency

*Type*	*Hours*	*Description*
Workload	Full time hours per semester
Lecture	24	No Description
Workshop	12	No Description
Assignment Completion	50	No Description
Online activity	15	No Description
Independent Study	25	No Description
Total Workload: 126

Section Breakdown
CRN	20851	Part of Term	Semester 2
Coursework	0%	Examination Weight	0%
Grade Scale	40PASS	Pass Both Elements	Y
Resit Category	RC1	Best Mark	N
Module Co-ordinator	Andreas Robotis	Module Teacher	Ann Largey, Gerard Conyngham

Type	Description	% of total	Assessment Date
Assessment Breakdown
Assignment	Data Analysis Assignment - Create a Datafile in SPSS - Generate Descriptive Statistics in MS EXCEL and SPSS - Calculate Probabilities using MS EXCEL - Calculate Confidence intervals using MS EXCEL - Run Statistical Tests in SPSS -	60%	n/a
Essay	Short Essay on role of data analysis and analytics in business	10%	n/a
Assignment	Review and Critique a number of questionnaires / measurement instruments	10%	n/a
Group assignment	Build a Regression Model	20%	n/a

Reassessment Requirement Type
Resit arrangements are explained by the following categories; RC1: A resit is available for both^* components of the module. RC2: No resit is available for a 100% coursework module. RC3: No resit is available for the coursework component where there is a coursework and summative examination element. ^* ‘Both’ is used in the context of the module having a coursework/summative examination split; where the module is 100% coursework, there will also be a resit of the assessment

Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

1. Introduction to Data Analysis
Role of Data Analysis in Business, Role of Technology in Data Analysis, Big Data and Data Analytics

2. Data Collection / Measurement
Data Collection, Questionnaire Design, Reliability and Validity, Data Cleaning and Missing Data, Measurement Types, Data Types,

3. Descriptive Statistics
Frequency Distributions, Measures of Central Tendency, Measures of Dispersion, Crosstabs and Correlation, Presentation, Graphical Tools and Data Vsiualsation

4. Probability
Probability Laws, Empirical and A Priori Probabilities, Probability Distributions; Binomial and Poisson Distributions, Normal Probability Distribution

5. Statistical Estimation/Sampling Error
Sampling Error, Sampling Distributions, Central Limit Theorem, Confidence Intervals for means and proportions, Selecting appropriate sample size

6. Hypothesis Testing / Statistical Tests
What is a Statistical Test? General approach to statistical tests, Statistical Significance, Summary of Statistical Tests for Difference

7. Regression / Forecasting / Predictive Analytics
Multivariate Analysis, Linear Regression. Over view of Forecasting Techniques; Time Series, Predictive Analytics

Indicative Reading List

Books:

Mr. Gerry Conyngham: 0, Detailed Course Handouts for Each Section,
Field, Andy P: 2018, Discovering statistics using IBM SPSS statistics, 5TH Ed., SAGE,
Pallant J.: 2016, SPSS survival manual: a step by step guide to data analysis using SPSS for Windows, 6th Ed., Oxford University Press,
Curwin J. and Slater R: 2008, Quantitative Methods for Business Decisions, 6th Ed., Thomson Learning,

Articles:
None

Other Resources

None