Module Code: H8STATS1
Long Title Statistics I
Title Statistics I
Module Level: LEVEL 8
EQF Level: 6
EHEA Level: First Cycle
Credits: 5
Module Coordinator: Sophie Flanagan
Module Author: ORLA LAHART
Departments: School of Computing
Specifications of the qualifications and experience required of staff

Level 9 Qualification in a numerate / scientific discipline and experience of the practical business application of standard statistical techniques.

Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Demonstrate the use of graphical and numerical techniques in descriptive statistics
LO2 Understand the theory, concepts and methods associated with the analysis of business data, using statistical hypotheses and inferential statistics to assist appropriate judgement and decision-making.
LO3 Understand and apply linear models to calculate correlation and to perform and interpret inference using regression.
LO4 Understand and apply typical software tools for business data analysis
Module Recommendations

This is prior learning (or a practical skill) that is required before enrolment on this module. While the prior learning is expressed as named NCI module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).

No recommendations listed
Co-requisite Modules
No Co-requisite modules listed
Entry requirements  

Module Content & Assessment

Indicative Content
Week 1
Course Introduction, The Role of Data and Statistics
Week 2
Interpreting and Describing Datasets
Week 3
Probability: Sample Spaces, Combinatorial Mathematics, Random Sampling
Week 4
Hypothesis Testing
Week 5
Single Sample Testing
Week 6
Two Sample Testing, Independent Samples
Week 7
Two Sample Testing, Dependent Samples
Week 8
Analysis of Variance
Week 9
Goodness of Fit​
Week 10
Linear Correlation
Week 11
Simple Linear Regression
Week 12
Module Revision
Assessment Breakdown%
End of Module Assessment60.00%


Full Time

Assessment Type: CA 1 % of total: 40
Assessment Date: n/a Outcome addressed: 1,2,4
Non-Marked: No
Assessment Description:
Test on topics covered to date: Interpreting and Describing Datasets, Visualizing Data and Data Presentation, Hypothesis Testing, Single Sample Testing
End of Module Assessment
Assessment Type: Terminal Exam % of total: 60
Assessment Date: End-of-Semester Outcome addressed: 1,2,3,4
Non-Marked: No
Assessment Description:
Module Terminal Exam covering entire curriculum but with a focus on: Two Sample Testing, Analysis of Variance, Goodness of Fit, Correlation and Simple Linear Regression
No Workplace Assessment
Reassessment Requirement
Repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.
Reassessment Description
Reassessment of this module will consist of a repeat examination that assesses all learning outcomes. It is possible that there will also be a requirement to be reassessed in a coursework element.

NCIRL reserves the right to alter the nature and timings of assessment


Module Workload

Module Target Workload Hours 0 Hours
Workload: Full Time
Workload Type Workload Description Hours Frequency Average Weekly Learner Workload
Lecture No Description 24 Per Semester 2.00
Tutorial No Description 12 Per Semester 1.00
Independent Learning No Description 89 Per Semester 7.42
Total Weekly Contact Hours 3.00

Module Resources

Recommended Book Resources
  • James T. McClave,Terry Sincich. (2016), Statistics, 13th. Pearson, p.896, [ISBN: 9780134080215].
  • Neil J. Salkind, Bruce B. Frey. (2019), Statistics for People Who (Think They) Hate Statistics, 7th. SAGE Publications, Inc.
  • John H. Kranzler. (2017), Statistics for the Terrified, Rowman & Littlefield Publishers, p.224, [ISBN: 9781538100288].
Supplementary Book Resources
  • Andy Field. (2018), BUNDLE: Field: Discovering Statistics using IBM SPSS Statistics 5e + SPSS 24, SAGE Publications, Incorporated, p.775, [ISBN: 9781544328225].
  • Dennis Howitt,Duncan Cramer. (2016), Statistics in Psychology Using SPSS, Pearson, p.760, [ISBN: 9781292134215].
  • Antony Davies. (2017), Understanding Statistics, Cato Institute, p.152, [ISBN: 9781944424367].
This module does not have any article/paper resources
Other Resources
Discussion Note: