Biology in the Senior Phase presents many opportunities to analyse data to understand and interrogate the meaning behind results obtained through experimentation. Analysis of data can involve an assessment of variation to inform sample size, or it could involve comparing data to explore correlation and significance.

This course will explore some of these areas, through simple experimentation to gather data, and then look at various methods to analyse the data. This will involve the use of R and Excel, as well as simple analyses that can be performed without software.

Course Dates: 26th February 2025
Closing Date: 17th January 2025

Course Leader

Annie McRobbie
01383 626070
annie.mcrobbie@sserc.scot

Accommodation

No accommodation is provided for 1-day courses at SSERC.

Location

The course will be held at SSERC in Dunfermline. Our SSERC buildings are at 2 Pitreavie Court, Dunfermline, KY11 8UU. SSERC is a short (5-10 minutes) walk from Rosyth railway station and close to the end of the A823(M) spur off Junction 2 of the M90 motorway. Car journey times (approximately): Edinburgh – 30 min; Glasgow – 60 min; Aberdeen – 2.5 hours; Inverness – 3 hours.

Cost

The cost of this course is £60.

 

Course Aims 

This course aims to support the analysis of data obtained through experimentation. The course would be well suited to new teachers delivering Advanced Higher Biology, but also for Senior Phase generally to start building the skills needed to think about data and what we can learn through analysis. In large part, this course will focus on the use of the programme R. This programme runs on a PC – it is worth reflecting on this before embarking upon the course since your own school context might make implementing the content of the course challenging.

   

Course Outcomes 

By the end of this course, you should be able to:    

·        Navigate the interface of R. 

·        Input a dataset into R. 

·        Use code to produce descriptive statistics of a data set.  

·        Construct a labelled boxplot of a dataset to determine variation within and between data sets. 

·        Calculate standard deviation and standard error. 

·        Construct suitable charts for presentation of data. 

·        Identify appropriate statistics to analyse data and write code to predict the statistical significance of results obtained.