BIOL2003K Quantitative Skills for Biologists

Academic Year 2023/2024

The aim of this module is to introduce students to a range of quantitative data analysis skills that they will need to apply throughout their undergraduate studies. Through this module, students will gain a better understanding of statistics and the theories underlying the statistical tests. Students will learn how to select appropriate statistical approaches, handle large datasets, and perform basic statistical analyses using R programming to solve specific biological problems.

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Curricular information is subject to change

Learning Outcomes:

On completion of this module, students should be able to:

1) understand the basic principles of various statistical tests;
2) think quantitatively about biological problems;
3) choose appropriate statistical methods for data analysis based on certain biological issues;
4) use basic quantitative skills in the analysis and interpretation of experimental data;
5) have a better appreciation of the value of statistics to the analysis and interpretation of biological data.

Indicative Module Content:

1) Biological data: type of data, description of samples
2) Probability and common statistical distributions for biological data (normal, binomial distributions)
3) Confidence intervals
4) Testing for differences (principles of hypothesis testing, t-test, Mann-Whitney nonparametric test, paired test)
5) Categorical data (Chi-square tests for association, Fisher's exact tests)
6) Comparing the means of many independent samples (modelling relationship)
7) Linear regression and correlation

Student Effort Hours: 
Student Effort Type Hours
Lectures

20
Practical

10
Specified Learning Activities

30
Autonomous Student Learning

60
Total

120
Approaches to Teaching and Learning:
This module will be delivered in lecture format and collaborative learning activities in workshops and tutorials. 
Requirements, Exclusions and Recommendations
Learning Recommendations:

Students are recommended to have some basic knowledge on R studio and programming beforehand. But this is NOT mandatorily required.


Module Requisites and Incompatibles
Additional Information:
Please note that this module is delivered overseas and is not available to students based at the UCD Belfield or UCD Blackrock campuses.


 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Examination: End-of-term final exam 2 hour End of Trimester Exam No Alternative linear conversion grade scale 40% No

80
Class Test: Midterm quiz Week 6 n/a Alternative linear conversion grade scale 40% No

20

Carry forward of passed components
No
 
Resit In Terminal Exam
Summer Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Feedback will be given to the class, post assessment, for assignments and midterm quiz.

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
 

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