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Information about the soft- and practical-skills workshops of the CUI Graduate Days 2014

Here you can find further information about the soft- and practical-skills workshops of the Graduate Days of CUI 2014.


Practical statistics: Prof. Louis Lyons (Imperial College and University of Oxford, United Kingdom)

Because many experiments involve complicated and expensive apparatus, it is worth investing effort into analysing the data well. These lectures deal with practical problems that arise in the statistical analysis of data.
The emphasis will be on what the results mean, features to beware of, and trying to understand whether the results are sensible. They cover the determination of parameters and their errors, and also comparing data with various models.

Lecture 1) Introduction (Monday March 10, 2014)
The Introduction includes a reminder of several topics which should already be familiar from an undergraduate course, although we will look at some of these in a new light. We will need these concepts in later lectures. We will also discuss briefly the Bayesian and Frequentist approaches to the meaning of probability, and to determining parameters.


  • Introductory remarks:
    1. Probability and Statistics.
    2. Conditional probability.
    3. Statistical and systematic errors.
    4. Combining different sources of uncertainty
    5. Combining results. BLUE = Best Linear Unbiassed Estimate
    6. Binomial, Poisson and 1-D Gaussian, and relations between them
  • What is probability? Bayes and Frequentist approaches

Lecture 2)  Chi-squared (Tuesday March 11, 2014)
Parameters can also be determined via the chi-squared approach. This is compared with the likelihood method. The main advantage of chi-squared is that it can also be used to provide a measure of ‘goodness of fit’ between the data and a theoretical prediction.


  • Basic idea.
  • Error estimates.
  • Several parameters
  • Correlated errors on y.
  • Errors on x and y.
  • Goodness of fit. Degrees of freedom. Why asymptotic?
  • Errors of first kind and second kind.
  • The paradox
  • Kinematic fits. Toy example.

Lecture 3) Do’s and dont’s with Likelihood functions (Wednesday March 12, 2014)
The likelihood function provides a powerful method for determining a parameter and its uncertainty. An important feature is that it can deal with individual observations, rather than needing histograms. The method is explained with simple examples. Various possible pitfalls are also discussed.


  • Introduction to likelihood. Error estimate.
  • Simple examples: (1) Breit Wigner (2) Lifetime
  • Binned and unbinned likelihood
  • Several parameters
  • Common misapprehensions:
    1. Normalisation
    2. delta(lnL) = 1/2 rule and coverage
    3. Integrating the likelihood
    4. Unbinned L_max as goodness of fit?

Slides of the course: Introduction, Chi-squared, and Likelihood functions.


Presentation skills: Ms. Kerstin Kathy Meyer-Ross (Hochschule für Technik und Wirtschaft, Dresden, Germany)

This talk helps students to improve their personal presentation skills. Topics are, among others: how to structure a presentation so that the audience can it follow easily, designing slides, making the best possible use of visual aids and technical equipment, dealing with interruptions, handling questions, keeping an eye on the time and the best way of finishing in a hurry, common mistakes, what to do when nervous, how to give proper feedback, etc. Furthermore, non-native speakers of English are given tips on spoken language and a number of phrases they can use e.g. for transition.


Scientific writing and writing for funds: Ms. Monica Schofield and Ms. Nina Stedman (TuTech Innovation GmbH, Hamburg)

Acquiring grants fro research has become a very competitive business no longer simply dependent on putting forward purely scientific arguments. Interpreting the criteria set out by funding bodies and writing convincingly to make the case are essential skills needed to win funding and make a career as a researcher.

This workshop will equip early career researchers with core skills on how to prepare grant applications in programmes requiring these to be made in English, such as Horizon 2020. The three sessions will cover an introduction to research funding systems and how to write effectively and convincingly in English.

First session: A short introduction to grant acquisition (Monica Schofield, Monday March 10, 2014)

  • Basic of public funded grants and funding sources
  • Grant acquisition skills
  • The process to get funded
  • Where to get information
  • What you need to start

Second session: Writing your grant proposal in English (Nina Stedman, Tuesday March 11, 2014)

  • Understanding academic writing
  • Understanding structure: writing your proposal narrative

Third session: The portfolio approach to grant writing (Nina Stedman, Wednesday March 12, 2014)

  • How to enhance your message and sell your project
  • How to built your portfolio of expressions for academic purposes

Slides of the course: Schofield and Stedman.