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Graduate School of Life Sciences course timetable

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Fri 22 Sep – Mon 27 Nov

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Monday 25 September

14:00
An Introduction to data analysis in R new (1 of 5) [Places] 14:00 - 17:00 University Information Services, Titan Teaching Room 1, New Museums Site

R is a free, software environment for statistical and data analysis, with many useful features that promote and facilitate reproducible research.

In this course, we introduce the R language, and cover basic data manipulation and plotting. We explore more advanced data analysis techniques using the packages dplyr and ggplot. Finally we introduce the concept of reproducible research, and how this may be assisted using 'literate programming'—combining documentation with code.

After the course you should feel confident to start exploring your own dataset, using the materials and references provided.

Sessions

If you book onto this course you must attend all of the sessions as detailed below. Failure to attend a session or cancellation of your place less than 48 hours before the start of the first session will result in an administrative charge of £50.

Please ensure you have permission from your supervisor to attend this course before you make your booking!

Trainers

Dr Michael Grayling, MRC Biostatistics Unit

Dr Simon Frost, Department of Veterinary Medicine

Dr Matt Castle, GSLS

Tuesday 26 September

09:30
An Introduction to data analysis in R new (2 of 5) [Places] 09:30 - 12:30 University Information Services, Titan Teaching Room 1, New Museums Site

R is a free, software environment for statistical and data analysis, with many useful features that promote and facilitate reproducible research.

In this course, we introduce the R language, and cover basic data manipulation and plotting. We explore more advanced data analysis techniques using the packages dplyr and ggplot. Finally we introduce the concept of reproducible research, and how this may be assisted using 'literate programming'—combining documentation with code.

After the course you should feel confident to start exploring your own dataset, using the materials and references provided.

Sessions

If you book onto this course you must attend all of the sessions as detailed below. Failure to attend a session or cancellation of your place less than 48 hours before the start of the first session will result in an administrative charge of £50.

Please ensure you have permission from your supervisor to attend this course before you make your booking!

Trainers

Dr Michael Grayling, MRC Biostatistics Unit

Dr Simon Frost, Department of Veterinary Medicine

Dr Matt Castle, GSLS

14:00
An Introduction to data analysis in R new (3 of 5) [Places] 14:00 - 17:00 University Information Services, Titan Teaching Room 1, New Museums Site

R is a free, software environment for statistical and data analysis, with many useful features that promote and facilitate reproducible research.

In this course, we introduce the R language, and cover basic data manipulation and plotting. We explore more advanced data analysis techniques using the packages dplyr and ggplot. Finally we introduce the concept of reproducible research, and how this may be assisted using 'literate programming'—combining documentation with code.

After the course you should feel confident to start exploring your own dataset, using the materials and references provided.

Sessions

If you book onto this course you must attend all of the sessions as detailed below. Failure to attend a session or cancellation of your place less than 48 hours before the start of the first session will result in an administrative charge of £50.

Please ensure you have permission from your supervisor to attend this course before you make your booking!

Trainers

Dr Michael Grayling, MRC Biostatistics Unit

Dr Simon Frost, Department of Veterinary Medicine

Dr Matt Castle, GSLS

Friday 29 September

09:30
Working Across Cultures new [Places] 09:30 - 13:00 17 Mill Lane, Seminar Room B

Working Across Cultures: A Practical Introduction to Intercultural Communication

Have you considered how culture may be influencing your professional relationships and interactions? Do you know which factors to consider when dealing with other nationalities? Are you using to your advantage what you may have already noticed or experienced? The workplace today is truly international in composition and intercultural competency is an invaluable and positive addition to your skill set.

This half day session is an introduction to the field of intercultural communication with an emphasis on practical application and developing self-awareness. It is a fun, engaging, relevant topic that will enable you to work more confidently and effectively with any nationality. You will become familiar with key variations across national cultures, so that you can recognise if/when and why cross-cultural misunderstandings are occurring, as well how to be more flexible in your approach.

You can expect a mixture of trainer-led content, as well as interactive exercises in pairs and small groups

An Introduction to data analysis in R new (4 of 5) [Places] 09:30 - 12:30 University Information Services, Titan Teaching Room 1, New Museums Site

R is a free, software environment for statistical and data analysis, with many useful features that promote and facilitate reproducible research.

In this course, we introduce the R language, and cover basic data manipulation and plotting. We explore more advanced data analysis techniques using the packages dplyr and ggplot. Finally we introduce the concept of reproducible research, and how this may be assisted using 'literate programming'—combining documentation with code.

After the course you should feel confident to start exploring your own dataset, using the materials and references provided.

Sessions

If you book onto this course you must attend all of the sessions as detailed below. Failure to attend a session or cancellation of your place less than 48 hours before the start of the first session will result in an administrative charge of £50.

Please ensure you have permission from your supervisor to attend this course before you make your booking!

Trainers

Dr Michael Grayling, MRC Biostatistics Unit

Dr Simon Frost, Department of Veterinary Medicine

Dr Matt Castle, GSLS

14:00
An Introduction to data analysis in R new (5 of 5) [Places] 14:00 - 17:00 University Information Services, Titan Teaching Room 1, New Museums Site

R is a free, software environment for statistical and data analysis, with many useful features that promote and facilitate reproducible research.

In this course, we introduce the R language, and cover basic data manipulation and plotting. We explore more advanced data analysis techniques using the packages dplyr and ggplot. Finally we introduce the concept of reproducible research, and how this may be assisted using 'literate programming'—combining documentation with code.

After the course you should feel confident to start exploring your own dataset, using the materials and references provided.

Sessions

If you book onto this course you must attend all of the sessions as detailed below. Failure to attend a session or cancellation of your place less than 48 hours before the start of the first session will result in an administrative charge of £50.

Please ensure you have permission from your supervisor to attend this course before you make your booking!

Trainers

Dr Michael Grayling, MRC Biostatistics Unit

Dr Simon Frost, Department of Veterinary Medicine

Dr Matt Castle, GSLS

Monday 2 October

10:00
Statistics for Biologists in R new (1 of 7) [Full] 10:00 - 12:30 University Information Services, Titan Teaching Room 2, New Museums Site

R is a free, software environment for statistical and data analysis, with many useful features that promote and facilitate reproducible research.

In this course, we introduce the R language, and cover basic data manipulation and plotting. Before moving on to explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear model analysis. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.

Sessions

If you book onto this course you must attend all of the sessions as detailed below. Failure to attend a session or cancellation of your place less than 48 hours before the start of the first session will result in an administrative charge of £50.

Please ensure you have permission from your supervisor to attend this course before you make your booking!

Trainers

Jonathan Patrick, Department of Plant Sciences

Matt Castle, GSLS

14:30
Statistics for Biologists in R new (2 of 7) [Full] 14:30 - 17:00 University Information Services, Titan Teaching Room 2, New Museums Site

R is a free, software environment for statistical and data analysis, with many useful features that promote and facilitate reproducible research.

In this course, we introduce the R language, and cover basic data manipulation and plotting. Before moving on to explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear model analysis. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.

Sessions

If you book onto this course you must attend all of the sessions as detailed below. Failure to attend a session or cancellation of your place less than 48 hours before the start of the first session will result in an administrative charge of £50.

Please ensure you have permission from your supervisor to attend this course before you make your booking!

Trainers

Jonathan Patrick, Department of Plant Sciences

Matt Castle, GSLS

Tuesday 3 October

14:30
Statistics for Biologists in R new (3 of 7) [Full] 14:30 - 17:30 University Information Services, Titan Teaching Room 2, New Museums Site

R is a free, software environment for statistical and data analysis, with many useful features that promote and facilitate reproducible research.

In this course, we introduce the R language, and cover basic data manipulation and plotting. Before moving on to explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear model analysis. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.

Sessions

If you book onto this course you must attend all of the sessions as detailed below. Failure to attend a session or cancellation of your place less than 48 hours before the start of the first session will result in an administrative charge of £50.

Please ensure you have permission from your supervisor to attend this course before you make your booking!

Trainers

Jonathan Patrick, Department of Plant Sciences

Matt Castle, GSLS

Thursday 5 October

09:30
Statistics for Biologists in R new (4 of 7) [Full] 09:30 - 12:30 University Information Services, Titan Teaching Room 2, New Museums Site

R is a free, software environment for statistical and data analysis, with many useful features that promote and facilitate reproducible research.

In this course, we introduce the R language, and cover basic data manipulation and plotting. Before moving on to explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear model analysis. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.

Sessions

If you book onto this course you must attend all of the sessions as detailed below. Failure to attend a session or cancellation of your place less than 48 hours before the start of the first session will result in an administrative charge of £50.

Please ensure you have permission from your supervisor to attend this course before you make your booking!

Trainers

Jonathan Patrick, Department of Plant Sciences

Matt Castle, GSLS

Friday 6 October

09:30
Statistics for Biologists in R new (5 of 7) [Full] 09:30 - 12:30 University Information Services, Titan Teaching Room 2, New Museums Site

R is a free, software environment for statistical and data analysis, with many useful features that promote and facilitate reproducible research.

In this course, we introduce the R language, and cover basic data manipulation and plotting. Before moving on to explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear model analysis. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.

Sessions

If you book onto this course you must attend all of the sessions as detailed below. Failure to attend a session or cancellation of your place less than 48 hours before the start of the first session will result in an administrative charge of £50.

Please ensure you have permission from your supervisor to attend this course before you make your booking!

Trainers

Jonathan Patrick, Department of Plant Sciences

Matt Castle, GSLS

14:00
Statistics for Biologists in R new (6 of 7) [Full] 14:00 - 17:00 University Information Services, Titan Teaching Room 2, New Museums Site

R is a free, software environment for statistical and data analysis, with many useful features that promote and facilitate reproducible research.

In this course, we introduce the R language, and cover basic data manipulation and plotting. Before moving on to explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear model analysis. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.

Sessions

If you book onto this course you must attend all of the sessions as detailed below. Failure to attend a session or cancellation of your place less than 48 hours before the start of the first session will result in an administrative charge of £50.

Please ensure you have permission from your supervisor to attend this course before you make your booking!

Trainers

Jonathan Patrick, Department of Plant Sciences

Matt Castle, GSLS

Monday 9 October

09:30
Statistics for Biologists in R new (7 of 7) [Full] 09:30 - 12:30 University Information Services, Titan Teaching Room 2, New Museums Site

R is a free, software environment for statistical and data analysis, with many useful features that promote and facilitate reproducible research.

In this course, we introduce the R language, and cover basic data manipulation and plotting. Before moving on to explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear model analysis. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.

Sessions

If you book onto this course you must attend all of the sessions as detailed below. Failure to attend a session or cancellation of your place less than 48 hours before the start of the first session will result in an administrative charge of £50.

Please ensure you have permission from your supervisor to attend this course before you make your booking!

Trainers

Jonathan Patrick, Department of Plant Sciences

Matt Castle, GSLS

Monday 27 November

09:30
How to write an academic paper and get it published [Places] 09:30 - 16:30 17 Mill Lane, Seminar Room B

The course takes an evidence-based approach to writing. Participants will learn that publishing is a game and the more they understand the rules of the game the higher their chances of becoming publishing authors. They will learn that writing an academic article and getting it published may help with their careers but it does not make them better researchers, or cleverer than they were before their paper was accepted; it simply means they have played the game well.

Suitable for GSLS postgraduates in any discipline who are keen to learn how to write academic papers and articles efficiently as well as more established researchers who have had papers rejected and are not really sure why.

If you want a better chance of your name on a paper, this is for you!

Trainer

Olivia Timbs is an award-winning editor and journalist with over 30 years' experience gained from working on national newspapers and for a range of specialist health and medical journals.

Cancellation and Non-attendance Policy Due to high demand we cannot accept cancellations for this course within 48 hours prior to the event. Any cancellations made after this time will be considered as a non-attendance. Participants who do not attend on the day will be subject to a £50 fee. By booking a place on the course you accept these terms.