Module: Statistics

Module Specifications..

Current Academic Year 2023 - 2024

Please note that this information is subject to change.

Module Title	Statistics
Module Code	BE205
School	School of Biotechnology
Module Co-ordinator	Semester 1: Emma Finlay Semester 2: Emma Finlay Autumn: Emma Finlay
Module Teachers	Paul Cahill Paula Meleady Ciaran Fagan Greg Foley Denise Harold Emma Finlay Linda Holland
NFQ level	8	Credit Rating	5
Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

None
Array

Description

This module firstly introduces students to data summarisation and presentation, including numerical measures of location and spread for both ungrouped and grouped data, and graphical methods. Secondly, it reviews the properties of the Normal distribution and calculations of probabilities involving normally distributed random variables and means of large random samples. Thirdly, it looks at concepts in hypothesis testing including Type I and Type II errors and tests for a single population mean and differences between two population means. Fourthly, students will learn how to perform power and sample size calculations and estimate confidence intervals. Fifthly, this module focuses on methods for analysing complex parametric data, basic correlation metrics and linear regression analysis. Sixthly, students will learn about non-parametric tests and then examine elementary aspects of Bayes' theorem, conditionality and odds ratios. The module will conduct work through a simple freely available graphical interface called R for data exploration and calculations.

Learning Outcomes

1. Summarise and explore data numerically and graphically using computational tools
2. Identify and test in an appropriate manner sources of variation in observational and experimental data
3. Perform probability calculations for normally distributed variables
4. Determine p-values, false discovery rates and power in tests
5. Identify and perform some one and two-sample statistical inference procedures for parametric models
6. Calculate and interpret correlation and create simple linear regression model

*Type*	*Hours*	*Description*
Workload	Full-time hours per semester
Lecture	12	Lectures
Lecture	12	Tutorials
Laboratory	12	Compulsory computer labs
Independent Study	89	Independent study
Total Workload: 125

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Data sampling
summarisation and visualisation

R
How to use R for data exploration and calculations

variables
Random variables and the Normal distribution

T-tests
T-tests between categories

Power
Power calculations

ANOVA
What to do with data that has more than two categories or more than two factors that may interact

Correlation
coefficients

Regression
Regression models

Rank-based tests
Non-parametric rank-based tests

Bayes' theorem
Bayes' theorem and odds ratios

Assessment Breakdown
Continuous Assessment	40%	Examination Weight	60%

Type	Description	% of total	Assessment Date
Course Work Breakdown
Loop Quiz	Best ten marks for weekly tutorial questions	10%	n/a
Assignment	Completion of two R coding assigments	30%	n/a

Reassessment Requirement Type
Resit arrangements are explained by the following categories; 1 = A resit is available for all components of the module 2 = No resit is available for 100% continuous assessment module 3 = No resit is available for the continuous assessment component
This module is category 1

Indicative Reading List

0: http://davidmlane.com/hyperstat/index.html "HyperStat Online Statistics Textbook" 2013 by David M Lane, 261658
0: http://www.statsref.com "Statistical Analysis Handbook" 2015 by MJ de Smith.,

Other Resources

None

Programme or List of Programmes

AFU	Age Friendly University Programme
BP	BSc in Bioprocessing
BT	BSc in Biotechnology
GCB	BSc in Genetics & Cell Biology
SHSAO	Study Abroad (Science & Health)

Date of Last Revision

31-OCT-07

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