Module Details

Module Code: DATA C8Z01
Full Title: Statistics using R
Valid From: Semester 1 - 2020/21 ( September 2020 )
Language of Instruction:English
Duration: 1 Semester
Credits: 10
Module Owner:: Fiona Lawless
Departments: Unknown
Module Description: The module lays solid foundations in statistics using the R programming language.
 
Module Learning Outcome
On successful completion of this module the learner will be able to:
# Module Learning Outcome Description
MLO1 Write basic functions using R data structures.
MLO2 Use R to produce statistical graphics.
MLO3 Apply fundamental concepts and techniques in exploratory data analysis using R.
MLO4 Apply fundamental concepts of probability laws and recognise the appropriate probability distribution to model given problems.
MLO5 Understand, study, design the processing of data and use it to insure integrity of data.
MLO6 Construct and interpret appropriate hypothesis testing and confidence intervals for one, two and paired samples, and more than two samples. Implement hypothesis testing using R.
MLO7 Evaluate correlation and conduct analysis for simple linear regression models using R.
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 DkIT module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
57159 DATA C8Z01 Statistics using R
 
Module Indicative Content
R
Understand and use R data structures. Understand how to use R for mathematical computation programming. Use R to produce statistical graphics and for data analysis.
Descriptive Statistics
Frequency tables, measures of central tendency & variation; Graphical representation of data
Processing of Data
Missing Data, Outliers
Probability Theory
Basic Laws of Probability, Probabilistic Problem Solving, Bayes Theorem
Probability distributions
Binomial, Poisson, Normal and other distributions, Monte Carlo method
Hypothesis Testing
One Sample, Two Sample, Paired Sample and ANOVA hypothesis testing
Regression Analysis
Scatterplots, Correlation & Simple Linear Regression Analysis.
Bootstrap
Bootstrap methods, Density estimation.
Module Assessment
Assessment Breakdown%
Course Work20.00%
Project20.00%
Practical20.00%
Final Examination40.00%
Module Special Regulation
 

Assessments

Full Time

Course Work
Assessment Type Continuous Assessment % of Total Mark 20
Marks Out Of 100 Pass Mark 40
Timing n/a Learning Outcome 1,2,3,4,5,7
Duration in minutes 30
Assessment Description
Bi-Weekly short individual & group exercises or quizzes.
Project
Assessment Type Project % of Total Mark 20
Marks Out Of 100 Pass Mark 40
Timing End-of-Semester Learning Outcome 1,2,3,4,5,6,7
Duration in minutes 0
Assessment Description
Data Project 2. Practical Implementation of some aspects of content of this module that involve analyzing data using R and will form part of a joint project with Applied Database Systems.
Practical
Assessment Type Practical/Skills Evaluation % of Total Mark 20
Marks Out Of 100 Pass Mark 40
Timing n/a Learning Outcome 1,2,3,4
Duration in minutes 60
Assessment Description
An in-class lab test which will require students to use R to answers problems and do some elementary statistics
Final Examination
Assessment Type Formal Exam % of Total Mark 40
Marks Out Of 0 Pass Mark 0
Timing End-of-Semester Learning Outcome 3,4,5,6,7
Duration in minutes 120
Assessment Description
n/a

Part Time

Course Work
Assessment Type Continuous Assessment % of Total Mark 20
Marks Out Of 100 Pass Mark 40
Timing n/a Learning Outcome 1,2,3,4,5,7
Duration in minutes 30
Assessment Description
Bi-Weekly short individual & group exercises or quizzes.
Project
Assessment Type Project % of Total Mark 20
Marks Out Of 100 Pass Mark 40
Timing End of Year Learning Outcome 1,2,3,4,5,6,7
Duration in minutes 0
Assessment Description
Data Project 2. Practical Implementation of some aspects of content of this module that involve analyzing data using R and will form part of a joint project with Applied Database Systems.
Practical
Assessment Type Practical/Skills Evaluation % of Total Mark 20
Marks Out Of 100 Pass Mark 40
Timing n/a Learning Outcome 1,2,3,4
Duration in minutes 60
Assessment Description
An in-class lab test which will require students to use R to answers problems and do some elementary statistics
Final Examination
Assessment Type Formal Exam % of Total Mark 40
Marks Out Of 0 Pass Mark 40
Timing End of Year Learning Outcome 3,4,5,6,7
Duration in minutes 120
Assessment Description
Final Examination
Reassessment Requirement
A 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.

DKIT 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 No Description Every Week 2.00 2
Practical Contact No Description Every Week 4.00 4
Independent Study Non Contact No Description Every Week 10.00 10
Total Weekly Learner Workload 16.00
Total Weekly Contact Hours 6.00
Workload: Part Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact   Every Week 1.00 1
Practical Contact   Every Week 2.00 2
Independent Study Non Contact   Every Week 5.00 5
Total Weekly Learner Workload 8.00
Total Weekly Contact Hours 3.00
 
Module Resources
Supplementary Book Resources
  • Andy Field, Jeremy Miles, & Zoe Field. (2013), Discovering Statistics using R, SAGE Publications, [ISBN: 9781446289136].
  • James, G., Witten, D., Hastie, T., Tibshirani, R.. (2017), An Introduction to Statistical Learning: with Applications in R, Springer-Verlag New York Inc., [ISBN: 9781461471370].
This module does not have any article/paper resources
Other Resources