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PGR Core Library
The course is designed for researchers who have little understanding of statistical methods and wish to apply statistical techniques in practice. By the end of the sessions, you will understand fundamental statistical concepts 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.
This course will focus on statistical methods used to assess the time of an event. You will be shown how to perform survival analysis through the statistics package SPSS, and the interpretation of SPSS output will be considered.
A 10-hour certified course teaches you the importance of data management, the best practices of organising, storing, archiving and quality checking your data, and options for sharing your data to maximise the impact of your research. It is suitable for researchers in any discipline.
This short 4-hour certified course 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. It is suitable for researchers in any discipline who want to develop their data analysis skills to maximise the outputs of their research data.
This 5-hour certified course is suitable for researchers in any discipline 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 also briefly introduced.
SAGE Campus has e-modules on many aspects of qualitative data collection and analysis, including Working with Transcribed Data, Do Your Interviews, Gather Your Data Online, and Collecting Social Media Data. In addition, there are several learner pathways dedicated to statistical and data skills.
This pathway is aimed at all students who haven’t worked with numbers or stats for a while and need a refresher. Using different sets of data, learners will practice finding statistically significant results, discuss p-values and work with samples to measure and investigate people, organizations and societies.
This pathway begins with an overview of the basic R commands and data structures for manipulating data. Learners will progress to generating inferences using quantitative statistical methods, eventually presenting data in an engaging and visual way.
This pathway teaches an overview of the principles, techniques, and tools for presenting data in visually attractive and powerful visualizations. By the end of the learning pathway, learners will be able to present their data in interactive ways using the R programming language.
This pathway teaches an overview of the core elements of the Python programming language and how these can feed into social scientific work. Reviewing essential elements of Python programming, learners will be able to extract data and use visualization techniques when conducting social science research.
There are many courses on LinkedIn Learning that enable you to learn essential tools used in statistical and data analysis. You can practice your skills in NViVo, Python, R, and SPSS.
Research Support - Libraries and Collections
King's Library has collections of resources to help with: