Module Details

Module Code: STAT6014
Title: Intro Stats for Phys. Sc.
Long Title: Intro Stats for Phys. Sc.
NFQ Level: Fundamental
Valid From: Semester 1 - 2019/20 ( September 2019 )
Duration: 1 Semester
Credits: 5
Field of Study: 4620 - Statistics
Module Delivered in: 7 programme(s)
Module Description: This module provides an introduction to data analysis and probability theory. The emphasis will be practical and will be assisted by a statistical software package.
 
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Graphically display and numerically summarise data using methods of descriptive statistics.
LO2 Apply the rules of probability and use probability distributions to model random variables.
LO3 Model the relationship between two continuous variables using simple linear regression.
LO4 Use a statistical software package to perform exploratory data analysis and fit simple linear regression models.
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).
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
Descriptive Statistics
Collection and presentation of data: frequency distributions, histograms, box plots, cumulative frequency, contingency tables. Calculation of summary statistics: measures of central tendency and measures of dispersion.
Probability
Classical, frequentist and axiomatic definitions. The elementary rules for calculation of probabilities. Independent events, mutually exclusive events, conditional probability, tree diagrams and Bayes' theorem.
Probability Distributions
Random variables. Discrete and continuous distributions. Properties of probability density and cumulative density functions. Expected value and variance. Binomial, Poisson, and Normal distributions. Use of statistical tables.
Regression and Correlation
Bivariate relationships, scatter diagrams, coefficient of correlation and coefficient of determination. Simple linear regression and transformation of variables to achieve linearity.
Module Content & Assessment
Assessment Breakdown%
Coursework30.00%
End of Module Formal Examination70.00%

Assessments

Coursework
Assessment Type Short Answer Questions % of Total Mark 15
Timing Week 7 Learning Outcomes 1,2
Assessment Description
In-class test: descriptive statistics and probability.
Assessment Type Practical/Skills Evaluation % of Total Mark 15
Timing Week 12 Learning Outcomes 1,2,3,4
Assessment Description
Statistical software lab assessment
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 Formal lecture Every Week 3.00 3
Lab Contact Analysis of simple case studies using statistical software Every Week 1.00 1
Independent & Directed Learning (Non-contact) Non Contact Exercise sheets Every Week 3.00 3
Total Hours 7.00
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 Formal Lecture Every Week 2.00 2
Lab Contact Analysis using statistical software Every Week 1.00 1
Independent & Directed Learning (Non-contact) Non Contact Exercise Sheets Every Week 4.00 4
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 3.00
 
Module Resources
Recommended Book Resources
  • Currell, Graham; Dowman, Antony. (2009), Essential mathematics and statistics for science, Wiley-Blackwell, [ISBN: 0470694480].
Supplementary Book Resources
  • James McClave and Terry Sincich. (2018), A First Course in Statistics, 12. Pearson, [ISBN: 9781292165417].
  • Allan G. Bluman. (2013), Elementary Statistics: A Step by Step Approach, 9. McGraw-Hill, [ISBN: 978-00735349].
  • O'Shea, T. L.. (2013), Essential Statistics for Researchers, IT Tralee, [ISBN: 095750].
  • Ross, Sheldon M. (2014), Introduction to probability and statistics for engineers and scientists, Elsevier, [ISBN: 0123948428].
  • Neil J. Salkind. (2016), Statistics for People Who (Think They) Hate Statistics, 6. SAGE, [ISBN: 978-150633383].
This module does not have any article/paper resources
Other Resources
 
Module Delivered in
Programme Code Programme Semester Delivery
CR_SCHQA_8 Bachelor of Science (Honours) in Analytical Chemistry with Quality Assurance 3 Mandatory
CR_SESST_8 Bachelor of Science (Honours) in Environmental Science and Sustainable Technology 3 Mandatory
CR_SINEN_8 Bachelor of Science (Honours) in Instrument Engineering 3 Mandatory
CR_SCHEM_7 Bachelor of Science in Analytical and Pharmaceutical Chemistry 3 Mandatory
CR_SPHYS_7 Bachelor of Science in Applied Physics and Instrumentation 3 Mandatory
CR_SPHYS_6 Higher Certificate in Science in Applied Physics and Instrumentation 3 Mandatory
CR_SCHEM_6 Higher Certificate in Science in Chemistry 3 Mandatory