Title:  Applied Stats & Probability 
Long Title:  Applied Statistics and Probability 
Field of Study: 
Statistics

Valid From: 
Semester 1  2014/15 ( September 2014 ) 
Module Coordinator: 
AINE NI SHE 
Module Author: 
Sean Lacey 
Module Description: 
This module will apply statistics and probability distributions to modern day problems. It will develop graphical visualisation methods, probability theory and distributions. The module will develop knowledge, skill and competence of sampling theory, hypothesis testing and linear regression. 
Learning Outcomes 
On successful completion of this module the learner will be able to: 
LO1 
Graphically display and numerically summarise data using methods of descriptive statistics. 
LO2 
Apply the rules of probability and use probability models for data analysis. 
LO3 
Compute and interpret point and interval estimates of population parameters. Determine required sample sizes. 
LO4 
Describe the structure and compute statistical tests of hypothesis. 
LO5 
Interpret scatterplots, correlation coefficients and the results from simple
linear regression. Use the results of linear regression for prediction. 
LO6 
Analyse statistical output from statistical packages such as IBM SPSS and R. 
Prerequisite 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). 
No recommendations listed 
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 
Corequisite Modules

No Corequisite 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 
Corequisites

No Co Requisites listed 
Module Content & Assessment
Indicative Content 
Data collection and presentation
Collection and presentation of data. Basic descriptive statistics (both graphical and numerical).

Probability
Relative frequency and axiomatic definitions. Laws of probability, conditional probability, independent and mutually exclusive events.

Probability distributions
Random variables. Discrete and continuous distributions. Properties of probability density and cumulative density functions. Binomial, Poisson, normal and exponential distributions. Use of statistical tables.

Sampling
Sampling distributions of proportions and means. Calculate the required sample size to obtain confidence intervals of required
length for a single parameter. Confidence intervals and hypothesis tests for: onesample mean and proportion; difference between twosample means and proportions.

Linear regression
Interpret scatterplots, correlation coefficients and the results from simple
linear regression. Use the results of linear regression for prediction.

Statistical packages
Analyse statistical output from statistical packages such as IBM SPSS and R.

Assessment Breakdown  % 
Course Work  50.00% 
End of Module Formal Examination  50.00% 
Course Work 
Assessment Type 
Assessment Description 
Outcome addressed 
% of total 
Assessment Date 
Practical/Skills Evaluation 
Descriptive statistics 
1,2,6 
25.0 
Week 6 
Practical/Skills Evaluation 
Confidence intervals and hypothesis testing 
3,4,5,6 
25.0 
Week 11 
End of Module Formal Examination 
Assessment Type 
Assessment Description 
Outcome addressed 
% of total 
Assessment Date 
Formal Exam 
EndofSemester Final Examination 
1,2,3,4,5,6 
50.0 
EndofSemester 
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 
Formal lecture 
2.0 
Every Week 
2.00 
Lab 
Statistical package lab 
2.0 
Every Week 
2.00 
Independent & Directed Learning (Noncontact) 
Worksheets 
3.0 
Every Week 
3.00 
Total Hours 
7.00 
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 
Formal lecture 
1.5 
Every Week 
1.50 
Lab 
Statistical package lab 
1.5 
Every Week 
1.50 
Independent & Directed Learning (Noncontact) 
Worksheets 
4.0 
Every Week 
4.00 
Total Hours 
7.00 
Total Weekly Learner Workload 
7.00 
Total Weekly Contact Hours 
3.00 
Module Resources
Recommended Book Resources 

 Mario F. Triola,, Elementary Statistics [ISBN: 0321782682]
 Tadhg L. O'Shea 2013, Essential Statistics fo Researchers [ISBN: 0957505902]
 Perry R. Hinton 2004, Statistics explained, Routledge [ISBN: 9780415332859]
 Colin Gray, Paul R Kinnear, IBM SPSS Statistics 19 Made Simple [ISBN: 9781848720695]
 David S. Moore, George P. McCabe, Bruce Craig, Introduction to the Practice of Statistics & CDRom [ISBN: 9781429286640]
 Supplementary Book Resources 

 Douglas C. Montgomery, George C. Runger, Applied Statistics and Probability for Engineers [ISBN: 9780470053041]
 David S. Moore, The basic practice of statistics [ISBN: 9781429224260]
 B. Burt Gerstman, Basic Biostatistics Pkg w/ 2009 Formulas and Tables [ISBN: 9780763781347]
 Jim Fowler, Phil Jarvis, and Mel Chevannes, Practical statistics for nursing and health care [ISBN: 9780471497165]
 This module does not have any article/paper resources 

This module does not have any other resources 

Module Delivered in
