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Statistics and Data Management

Doctoral training opportunities in this theme are available below.Statistics & Data Management Image

Workshops and webinars

King's postgraduate research students and postdoctoral research staff can access and book places on the CDS training courses through our online system Skills Forge. For guidance about course bookings, see Booking & Course Availability.


Analysing Qualitative Data (PGR316)

This course will consider and discuss a range of issues relative to the micro-analysis of qualitative data. Using example data throughout, issues covered will include the analyst’s perspective (the aims and nature of their engagement with the data), coding systems, how to choose extracts for analysis in a systematic fashion, the meaning and importance of interpretation, generalising from qualitative findings and various write-up issues, including the relationship between the analysis and discussion sections of a qualitative report and the creation of impact.

A Comparison of Qualitative Methods (PGR337)

Copyright considerations come into play at many points in academic life – for example, when publishing a journal article or PhD thesis, creating a taught course, or producing promotional material for a conference or event. This course provides an introduction and overview of copyright considerations in scholarly practice. It will help you understand key concepts, learn about the landscape of legislation and licences, what to think about when using copyrighted material in research and teaching, and copyright in works you create.

Qualitative Interviewing (PGR338)

Consider four different types of interviewing, but with a particular focus on semi-structured or ‘qualitative’ interviewing. Learn about the nature of interview questions, the design and structure of an effective interview schedule and the mechanics of conducting a successful interview.

Using NVivo for Qualitative Research (PGR317)

This course will introduce students to the NVivo software package, which is designed to help in the organisation, management and analysis of qualitative data. All the basic functions of NVivo will be covered, including the importation, storage, and organisation of various data sources, the potential for transcription, the creation of cases and nodes, classifications and attributes, and the meanings of these terms will be explained. The process of coding and data analysis will be demonstrated and the use of ‘queries’ explored as a ‘top down’ means of data access. The pros and cons of using software to conduct qualitative research will also be considered.


You can access all on-demand learning from On-demand PGR Training.

PGR Core Library

The three on-demand courses below have been specifically designed for King’s PGR students. See the KEATS course to explore other online courses that cover topics across our 8 key themes of doctoral training.

The course is designed for researchers who have little understanding of statistical methods and wish to apply statistical techniques in practice. The fundamentals of popular statistical procedures and tests will be explained, including descriptive statistics, confidence intervals, hypothesis testing, data transformation, t-tests, Mann-Whitney and Wilcoxon Tests, Chi-square and Fishers Exact Tests, one-way ANOVA, linear regression and binary logistic regression. By the end of the sessions you will understand fundamental statistical concepts so you can decide the appropriateness of statistical procedures and tests, and be able to use SPSS to apply the relevant techniques.

This course focuses on the statistical methods used for measuring agreement for both categorical and quantitative data. You will learn about standard measures and techniques that are used to evaluate the performance of diagnostic tests and assess the agreement between observers. By the end of the sessions you should be able to: gauge the agreement between observers using Kappa, weighted Kappa, Fleiss Kappa and Bland-Altman method; evaluate diagnostics tests by calculating sensitivity, specificity, positive and negative predictive values; assess a quantitative variable as a diagnostic tool by drawing a ROC curve.

This course will focus on statistical methods used to assess the time to an event. Although these methods are usually considered under the heading of ‘survival analysis’ the event could be any event where the focus of interest is the time until it occurs. You will be shown how to perform survival analysis through the statistics package SPSS and interpretation of SPSS output will be considered. By the end of the session you should be able to: estimate survival probabilities using the Kaplan-Meier method; use the log rank test to compare two survival curves; explain published results of Cox regression.

Nature Masterclasses

Find out more about Nature Masterclasses and how to access them. See Nature Masterclasses.

This certified course has been developed by 10 data management experts and is suitable for researchers in any discipline who want to build or enhance their skills in research data practice.
In this course, you will learn about the importance of data management, the best practices of organising, storing, archiving and quality checking your data, options for sharing your data to maximise the impact of your research. You will also be equipped with knowledge of the steps required to create and maintain a data management plan (DMP). The interactive portfolio activity will give you the opportunity to start creating your DMP as you go through the course.

This certified course is suitable for researchers in any disciplines who want to develop their data analysis skills to maximise the outputs of their research data. It introduces the essential elements of robust data analysis in detail so that learners will be equipped with the knowledge to implement best practices in planning and preparing for data analysis. Specific programmes used in data analysis are not the focus, although the course offers useful resources for independent learning.

You will be guided through each step of creating a successful data analysis plan by following this interactive course. Using various examples, the course explains the principles of creating and updating a data analysis plan, the key terms and processes relating to it, common pitfalls and errors, and how to apply best practices for collating and quality checking data.

Developed by Nature Portfolio editors and experts in data analysis, this certified course is suitable for researchers in any disciplines who want to develop their data analysis skills by learning about the key concepts, processes, and methodologies of effective data analysis during research projects. Specific tools for exploring various datasets are introduced, but the course does not offer comprehensive training on these tools.

You will learn each step in conducting data analysis, from choosing the analytic method to presenting the result of your analysis. Through various case studies and interactive activities, the course will equip you with the knowledge to choose the analytic method and tool most suited to your data, and strategies for obtaining feedback, troubleshooting and expressing limitations of your analysis.

SAGE Campus

King's members have free access to the SAGE Campus learning platform.  This includes 200+ hours of structured online learning for skills and research methods. The self-paced courses cover data management skills and research methods, from upskilling in data science and creating data visualisations, to publishing. See further details on the SAGE Campus page.

RDFmapped and LinkedIn Learning

As a member of King's you have free access to LinkedIn Learning.  For more information on how to access LinkedIn Learning, see the Centre for Technology Enhanced Learning.

Search LinkedIn Learning through the lens of Vitae's Reesarcher Development Framework using www.rdfmapped.com.  Developed by King's, this tool allows you to search a curated list of LinkedIn Learning courses and videos relevant to the domains of the RDF.  See: www.rdfmapped.com

Research Support - Libraries and Collections

King's Library has collections of resources to help with:

Statistics and data management

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Undergraduate prospectus

Postgraduate guide