Module: Data Analysis

Module Specifications.

Current Academic Year 2024 - 2025

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Date posted: September 2024

Module Title	Data Analysis
Module Code	EF108 (ITS) / BAA1002 (Banner)
Faculty	DCU Business School	School	DCU Business School
Module Co-ordinator	Robert Gillanders
Module Teachers	Ann Largey, Declan Curran, Lubani Nondo, Seyed Aref Mahdavi Ardekani
NFQ level	6	Credit Rating	5
Pre-requisite	Not Available
Co-requisite	Not Available
Compatibles	Not Available
Incompatibles	Not Available

None

Description

The purpose of this module is to provide students with an introduction to data analysis and interpretation. Students will learn about sources of data, methods of data presentation and description, and how to conduct simple hypothesis tests and make inferences. On completion of the module, students should be able to draw on statistics appropriately to support their own arguments and be able to better understand and critique statistical analysis they encounter in academic papers in subsequent courses. Students are expected to attend lectures and to actively participate in workshops and tutorials. Term exercises will be assigned in order to focus students' study and ensure timely review of course material.

Learning Outcomes

1. Define and calculate basic statistics used to describe distributions.
2. Present data in a meaningful way, using graphs and tables.
3. Perform calculations and manipulate data using a spreadsheet package, including estimation of a single variable regression.
4. Explain what a hypothesis test is, conduct simple hypothesis tests and interpret statistical significance.
5. Comment on statistical analysis in academic papers and identify shortcomings.

*Type*	*Hours*	*Description*
Workload	Full-time hours per semester
Lecture	18	No Description
Lecture	6	Workshops - Two of these sessions to be used as computer practicals
Independent Study	67	Review of lecture material, additional reading, preparation for workshops
Independent Study	8	Completion of Assessment 1
Independent Study	6	Completion of Assessment 2
Independent Study	20	Completion of Assessment 3
Total Workload: 125

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

Data description & presentation
Topics will include: Types of data; Displaying data graphically; Descriptive statistics – definitions, uses, examples; Correlation; Applications using data relevant to programme disciplines; Sourcing data.

Statistical Estimation
Statistical decision theory; Hypothesis tests; Interpretation of test statistics (p values, F tests etc); Regression output interpretation – using firstly statistical estimation, then reviewing data analysis section (eg. to show importance of causation v correlation)

Critiquing statistical analysis
Drawing on papers from relevant disciplines, show the different ways in which statistics are used to inform and augment debate. Examine the statistics used and conclusions drawn. Highlight potential shortcomings (eg. external factors outside scope of project that may have impact, reverse causation.)

Assessment Breakdown
Continuous Assessment	100%	Examination Weight	0%

Type	Description	% of total	Assessment Date
Course Work Breakdown
Assignment	Take home exercise	15%	Week 6
Assignment	Take home computer based exercise	15%	Week 8
Participation	Constructive participation	10%	Every Week
Assignment	Final term assignment	60%	Sem 2 End

Reassessment Requirement Type
Resit arrangements are explained by the following categories: Resit category 1: A resit is available for both* components of the module. Resit category 2: No resit is available for a 100% continuous assessment module. Resit category 3: No resit is available for the continuous assessment component where there is a continuous assessment and examination element.
* ‘Both’ is used in the context of the module having a Continuous Assessment/Examination split; where the module is 100% continuous assessment, there will also be a resit of the assessment
This module is category 1

Indicative Reading List

by Gary Koop: 0, Analysis of economic data, 978-0470713891
Beverly Dretzke,: 0, Statistics with Microsoft Excel, 978-0136043874
Deborah Rumsey,: 0, Statistics II for Dummies, 978-0470466469
by Deborah Rumsey: 2003, Statistics for dummies, Wiley, Hoboken, N.J., 978-0764554230
Deborah Rumsey: 2005, Statistics workbook for dummies, Wiley, Hoboken, N.J., 978-0764584664

Other Resources

None