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STAT7008 - Statistical Inference

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Title:Statistical Inference
Long Title:Statistical Inference
Module Code:STAT7008
 
Credits: 5
NFQ Level:Intermediate
Field of Study: Statistics
Valid From: Semester 1 - 2018/19 ( September 2018 )
Module Delivered in 1 programme(s)
Next Review Date: September 2021
Module Coordinator: David Goulding
Module Author: AINE NI SHE
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:
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.
Pre-requisite learning
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 CIT 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
Co-requisites
No Co Requisites listed
 

Module Content & Assessment

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.
Assessment Breakdown%
Course Work30.00%
End of Module Formal Examination70.00%
Course Work
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Short Answer Questions Series of SAQ tests over the semester 1,4 5.0 Week 4
Short Answer Questions Series of SAQ tests over the semester 1,2,4 5.0 Week 7
Short Answer Questions Series of SAQ tests over the semester 2,3,4 5.0 Week 10
Practical/Skills Evaluation Practical Assessment in Computer Labratory 1,2,3,4,5 15.0 Week 12
End of Module Formal Examination
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Formal Exam End-of-Semester Final Examination 1,2,3,4 70.0 End-of-Semester
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 institute reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Workload Description Hours Frequency Average Weekly Learner Workload
Lecture Delivery of content and material underpinning learning outcomes 3.0 Every Week 3.00
Lab Statistics Computer Laboratory 1.0 Every Second Week 0.50
Tutorial Questions and answers on lecture content, tutorial sheets 1.0 Every Second Week 0.50
Independent & Directed Learning (Non-contact) Review of module content, completion of exercise sheets and laboratory work 3.0 Every Week 3.00
Total Hours 8.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 4.00
Workload: Part Time
Workload Type Workload Description Hours Frequency Average Weekly Learner Workload
Lecture Lecture 2.0 Every Week 2.00
Lab Statistics Computer Laboratory 1.0 Every Second Week 0.50
Tutorial Questions and answers on lecture content, tutorial sheets 1.0 Every Second Week 0.50
Independent Learning Review of module content, completion of exercise sheets and laboratory work 4.0 Every Week 4.00
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 Ed., Thomson London [ISBN: 978-1844805747]
  • J.D Cryer, B.F. Ryan & B.L. Joiner 2013, Minitab Handbook, 6th Ed., Brooks/Cole [ISBN: 1285175026]
  • Mark L. Berenson, David M. Levine, Timothy C. Krehbiel 2014, Basic Business Statistics, 13th Ed., Pearson/Prentice Hall Upper Saddle River, N.J. [ISBN: 978-0-13-5009]
  • Charles Henry Brase, Corrinne Pellillo Brase 2015, Understanding Basic Statistics, 7th Ed., 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

Cork Institute of Technology
Rossa Avenue, Bishopstown, Cork

Tel: 021-4326100     Fax: 021-4545343
Email: help@cit.edu.ie