Module Details

Module Code: STAT7008
Title: Statistical Inference
Long Title: Statistical Inference
NFQ Level: Intermediate
Valid From: Semester 1 - 2018/19 ( September 2018 )
Duration: 1 Semester
Credits: 5
Field of Study: 4620 - Statistics
Module Delivered in: 1 programme(s)
Module Description: This module covers the principles of probability, common probability distributions, sampling theory and inferential statistics, to include both estimation and hypothesis testing.
 
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Apply the rules of probability and use probability models for data analysis.
LO2 Compute point and interval estimates for population parameters.
LO3 Formulate and test statistical hypotheses.
LO4 Interpret the results of statistical tests, and communicate findings clearly and concisely.
LO5 Use appropriate software for statistical and decision analysis.
Dependencies
Module Recommendations

This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named MTU module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
9011 MATH6057 IS Maths & Statistics
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. You may not earn additional credit for the same learning and therefore you may not enrol in this module if you have successfully completed any modules in the incompatible list.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
Requirements

This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.
No requirements listed
 
Indicative Content
Probability
Classical Probability, Relative frequency definition. Compound events, mutually exclusive and independent events. Expected value.
Probability Distributions
Discrete and Continuous variables. Random variables. Discrete and continuous distributions including Binomial, Poisson, Normal Distributions.
Sampling Theory
Discussion of various sampling methods, for example, random, stratified, cluster, systematic, snowball. Sample statistics, sampling distributions, standard error. Discussion of the distribution of the sample mean via the Central Limit Theorem.
Confidence Intervals
Point and interval estimates for means and proportions. Calculation of the required sample size to obtain confidence intervals of required length for a single parameter.
Hypothesis Testing
Hypothesis tests – null hypothesis, alternative hypothesis. Hypothesis tests for: one-sample mean and proportion; difference between two-sample means and proportions.
Software Tools
Statistical software procedures, using packages such as Excel, Minitab, R, for probability distributions, confidence intervals, and hypothesis testing.
Module Content & Assessment
Assessment Breakdown%
Coursework30.00%
End of Module Formal Examination70.00%

Assessments

Coursework
Assessment Type Short Answer Questions % of Total Mark 5
Timing Week 4 Learning Outcomes 1,4
Assessment Description
Series of SAQ tests over the semester
Assessment Type Short Answer Questions % of Total Mark 5
Timing Week 7 Learning Outcomes 1,2,4
Assessment Description
Series of SAQ tests over the semester
Assessment Type Short Answer Questions % of Total Mark 5
Timing Week 10 Learning Outcomes 2,3,4
Assessment Description
Series of SAQ tests over the semester
Assessment Type Practical/Skills Evaluation % of Total Mark 15
Timing Week 12 Learning Outcomes 1,2,3,4,5
Assessment Description
Practical Assessment in Computer Labratory
End of Module Formal Examination
Assessment Type Formal Exam % of Total Mark 70
Timing End-of-Semester Learning Outcomes 1,2,3,4
Assessment Description
End-of-Semester Final Examination
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.

The University reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Delivery of content and material underpinning learning outcomes Every Week 3.00 3
Lab Contact Statistics Computer Laboratory Every Second Week 0.50 1
Tutorial Contact Questions and answers on lecture content, tutorial sheets Every Second Week 0.50 1
Independent & Directed Learning (Non-contact) Non Contact Review of module content, completion of exercise sheets and laboratory work Every Week 3.00 3
Total Hours 8.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 4.00
Workload: Part Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Lecture Every Week 2.00 2
Lab Contact Statistics Computer Laboratory Every Second Week 0.50 1
Tutorial Contact Questions and answers on lecture content, tutorial sheets Every Second Week 0.50 1
Independent Learning Non Contact Review of module content, completion of exercise sheets and laboratory work Every Week 4.00 4
Total Hours 8.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 3.00
 
Module Resources
Recommended Book Resources
  • Tadhg L.O'Shea. (2012), Essential Statistics for Researchers, Treoraí Publications, [ISBN: 9780957505902].
Supplementary Book Resources
  • Jon Curwin. (2008), Quantitative Methods for Business Decisions, Sixth. Thomson, London, [ISBN: 978-1844805747].
  • J.D Cryer, B.F. Ryan & B.L. Joiner. (2013), Minitab Handbook, 6th. Brooks/Cole, [ISBN: 1285175026].
  • Mark L. Berenson, David M. Levine, Timothy C. Krehbiel. (2014), Basic Business Statistics, 13th. Pearson/Prentice Hall Upper Saddle River, N.J., [ISBN: 978-0-13-5009].
  • Charles Henry Brase, Corrinne Pellillo Brase. (2015), Understanding Basic Statistics, 7th. Cengage, [ISBN: 978-13052540].
This module does not have any article/paper resources
Other Resources
 
Module Delivered in
Programme Code Programme Semester Delivery
CR_BBISY_8 Bachelor of Business (Honours) in Information Systems 3 Mandatory