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Summer School in Advanced Research Methods 

Summer School 2016

This summer Aston Business School will be delivering a series of Advanced Research Methods courses designed to equip you with the specialist skills needed to become a leader in your chosen academic field.

Unlike most summer schools our programme is comprised of short, affordable courses, typically one to two days in length. The courses will be delivered by Aston’s internationally renowned faculty and will be highly practical in nature.

Courses are open to students (Research Masters and PhD) and faculty from any university, as well as industry researchers.  If required, an assignment can be completed as part of the course for those who need a grade in the subject area.  This will be in addition to a formal certificate of attendance.  The courses will be small enabling you to receive individual attention from our experts.

Further detail of the courses, including bibliographies where relevant are available for download from each course link.  Participants should do the basic reading for their courses in advance in order to maximise the learning.  All courses run from 9.00-5.00 each day.

All courses are subject to cancellation.  Applicants will normally be informed of any cancellation a minimum of one week prior to the course start date.

Please note: In order to keep workshop costs reasonable lunch/refreshments are not provided.

  1 Day Course 2 Day Course 3 Day Course
Student  £75 
£150
£225 

Academic 
£125 
£250 
£375 

Industry/Other  £175 
£350 
£525 

June

Dr Enrico Onali

Dates: 23-24 June 2016

Pre-requisites / Target Audience:

The target audience for this course is early-career researchers and graduate students in accounting and finance who are interested in applying panel data models. Participants should be familiar with correlation, basic matrix algebra and linear regression.

Course description:

Objectives

This two-day workshop provides an introduction to panel data models and how these can be applied for empirical research using STATA. Key objectives of this course are:

  • To provide an understanding of the key issues to consider when using panel data.
  • To familiarise participants with some key papers using panel data in accounting or finance research.
  • To enable participants to apply (where suitable) panel data analysis to their own research.
  • To enable participants to choose between OLS, Random Effects, and Fixed Effects models.
  • To explain how to run and interpret different types of dynamic panel data models.
  • To enable participants to critically examine panel data with STATA and draw meaningful conclusions.

The objectives will be achieved when actively participating during the workshop and by engaging with the literature.

Full course description

Dr Julien Schmitt

Date: 27-29 June 2016

Pre-requisites / Target Audience:

The target audience for this course is early-career researchers and graduate students in Business and Management, Psychology, and other social sciences, with an interest in designing and conducting experiments. Participants should be familiar with basic statistics.

Course description:

1. Objectives

The main objectives of this workshop are:

  • To familiarize participants with the key elements of experimental designs.
  • To enable participants to critically examine experimental settings encountered in research papers.
  • To enable participants to build experiments for their own research.

 

Full course description

July 

Dr Ali Emrouznejad 


Date: 12 July 2016 

Credits: 2.5 per day of delivery

Overview:

The aim of this course is to introduce many of the important idea in data mining with focus of analysing big data, explain them as statistical framework, and describe some of their applications in Business, Finance, Marketing, and Management. Hence, this course covers data mining techniques and their use in managerial business decision making. During this course you will analyse some case studies of well-known data mining methods; e.g. shopping basket analysis, credit card / insurance fraud detection, predicting stock market returns, risk analysis in banking.

Full Course Outline


Text Mining and Social Network Analysis

Dr Ali Emrouznejad

Date: 13 July 2016 

Credits: 2.5 per day of delivery

Overview:

The aim of this course is to introduce principles, issues, techniques and solutions connected with text mining. At the end of this course students will gain knowledge of how recent advances in text mining could help an organization to search for new knowledge by organising, characterising, finding and exploiting large scale textual/unstructured information.

Prof Heiner Evanschitzky, Prof Ad de Jong, Dr Yves Guillaume 

Dates: 12-14 July 2016 

Credits: 2.5 per day of delivery

Pre-requisites / Target Audience:

The target audience for this course is early-career researchers and graduate students in Business and Management, Psychology, and other social sciences, with an interest in latent variable and multi-level modelling. Participants should be familiar with correlation and linear regression.

Overview:

This three-day workshop discusses general data analysis issues of cross-sectional studies. In particular, it deals with multi-level (nested) data and offers hands-on software training. Key objectives are:

  • To provide a solid refresher on multivariate statistics, particularly focusing on topics important for multilevel analysis.
  • To familiarize participants with the key characteristics of nested data.
  • To enable participants to critically examine nested data with specific software and draw meaningful conclusions.
  • To enable participants to apply (where suitable) multilevel analysis to their own research.
  • To enable participants to conceptualize and test moderation and mediation in multilevel models.

Full Course Outline

September 

Dr. Ian Combe, David Carrington

Dates: 12-13 September 2016

Credits: 2.5 per day of delivery

Pre-requisites: None

Overview:

Data collection is a difficult, time consuming and costly activity In any research project. One key skill is to develop an interview protocol incorporating multiple data collection techniques to maximise the amount of data collected. This has the potential to increase the depth of understanding and to increase the output in terms of publications. Most researchers need to get this right first time.

This course is focused on the integration of multiple data collection techniques and subsequent analysis. The course focuses on integrating questionnaires with in-depth qualitative techniques such as sorting technique, causal cognitive mapping and laddering technique. The data collection and analytical techniques have been used by the researchers when interviewing managers as well as consumers.

Full Course Outline

Quotes from Summer School 2015

I am planning to implement the knowledge received in my PhD and beyond”

I received detailed feedback on my own project” 
Excellent teaching on the area”

Contact Us

To find out more details, send an enquiry: abssummerschool@ aston.ac.uk or contact Jeanette Ikuomola on +44 (0)121 204 3219

Booking your place

Booking your place

Register yourself a place here.

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