Module Details
Module Code: |
DATA C8Z01 |
Full Title:
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Statistics using R
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Valid From: |
Semester 1 - 2020/21 ( September 2020 ) |
Language of Instruction: | English |
Module Owner:: |
Fiona Lawless
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Module Description: |
The module lays solid foundations in statistics using the R programming language.
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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).
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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.
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Descriptive Statistics
Frequency tables, measures of central tendency & variation; Graphical representation of data
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Processing of Data
Missing Data, Outliers
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Probability Theory
Basic Laws of Probability, Probabilistic Problem Solving, Bayes Theorem
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Probability distributions
Binomial, Poisson, Normal and other distributions, Monte Carlo method
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Hypothesis Testing
One Sample, Two Sample, Paired Sample and ANOVA hypothesis testing
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Regression Analysis
Scatterplots, Correlation & Simple Linear Regression Analysis.
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Bootstrap
Bootstrap methods, Density estimation.
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Module Assessment
|
Assessment Breakdown | % |
Course Work | 20.00% |
Project | 20.00% |
Practical | 20.00% |
Final Examination | 40.00% |
Module Special Regulation |
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AssessmentsFull Time
Part Time
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.
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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
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Supplementary Book Resources |
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Andy Field, Jeremy Miles, & Zoe Field. (2013), Discovering Statistics using R, SAGE Publications, [ISBN: 9781446289136].
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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 |
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Other Resources |
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W. N. Venables, D. M. Smith and the R
Core Team. An Introduction in R,
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[Website], Online Statistics Education: An
Interactive Multimedia Course of Study,
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[Website], Khan Academy,
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[Website], DataCamp,
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