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Natasha McKeever

Topics Covered

  • Research ethics: why it matters
  • Recruiting your participants for your research and getting their consent
  • What to consider if you are recruiting vulnerable participants
  • Could your research put you or your participants at risk of harm?
  • Storing personal data
  • Archival and internet research

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Reviews summary

Informative research ethics

This course provides an excellent and informative introduction to research ethics. It is particularly useful for undergraduate students completing research for their final year project, but it is also suitable for postgraduates and academic researchers.
The course is useful for undergraduate students completing research for their final year project.
"This course is useful for learners undertaking research with people using social research methods such as questionnaires, interviews etc."
"The course is essential for undergraduate students completing research for their final year project but it is also suitable for postgraduates and academic researchers."
The course is very informative.
"extra ordinary , excellent and really Informative course."

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Provides a comprehensive overview of research ethics, covering the ethical principles that govern research involving human subjects, offers a variety of cases in which researchers have faced ethical dilemmas, and discusses the policies and procedures that institutions have developed to protect the rights of research participants.
Provides a practical guide to research ethics, offering advice on how to design and conduct research studies in an ethical manner. It covers a wide range of topics, including informed consent, confidentiality, conflict of interest, and data management.
Explores the ethical and legal issues surrounding informed consent in medical research. It provides a detailed analysis of the concept of informed consent, and it offers guidance on how to obtain informed consent from research participants.
Provides a practical guide to research ethics for social scientists. It covers a wide range of topics, including informed consent, confidentiality, conflict of interest, and data management.
This comprehensive textbook provides a detailed overview of the principles and practices of data collection in the social sciences, covering topics such as research design, sampling, data quality, and ethical considerations. It offers a strong foundation for understanding the entire data collection process.
This practical guide to data collection methods helps researchers design and implement effective studies, encompassing a wide range of techniques, including surveys, interviews, observations, and archival research. It provides clear and detailed instructions for each method and emphasizes the importance of reliability and validity.
This textbook offers a comprehensive introduction to survey research, covering the entire process from research design to data analysis. It provides theoretical foundations, practical guidance, and real-world examples, helping students understand the strengths and limitations of survey methods.
This introductory text provides a clear and accessible overview of data collection and analysis principles. It covers fundamental concepts such as data types, sampling techniques, data cleaning, and statistical analysis, making it suitable for beginners in data science and related fields.
Focuses on qualitative interviewing techniques, providing a step-by-step guide to conducting effective interviews. It covers ethical considerations, interview design, data analysis, and common challenges researchers may encounter. It offers a valuable resource for those interested in qualitative data collection methods.
This comprehensive encyclopedia provides an extensive overview of social science research methods, including data collection techniques such as surveys, interviews, observations, and experiments. It covers both quantitative and qualitative approaches and serves as a valuable reference for researchers seeking a deeper understanding of various data collection methodologies.
Explores big data analytics techniques and their applications across various fields. It covers data collection methods for handling large and complex datasets, as well as advanced analytics methodologies such as machine learning and predictive modeling. Researchers interested in leveraging big data for insights and decision-making will find this book valuable.
Provides an introduction to multivariate analysis methods, such as principal component analysis, cluster analysis, and discriminant analysis, using the R programming language. It explains the underlying concepts and provides practical examples and exercises, making it suitable for researchers interested in applying multivariate techniques to their data.

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