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Research and Statistics: An Introduction to using statistics and data analysis in research projects
Research and Statistics: An Introduction to using statistics and data analysis in research projects
Group size
1-6 students
Outcome
An analysis of a selected dataset including a 1- 2 page written analysis and relevant visualizations
Tuition
$495
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Research and Statistics: An Introduction to using statistics and data analysis in research projects
Statistical Analysis is a key skill for any researcher creating original research. Understanding the meaning of the numbers produced in research is an important part of applying meaning to your research and adding to the academic community! In this pod, we will learn the basics of finding and using appropriate research data for a chosen research question. We'll look at how to ethically collect data, examine the different data collection methods that exist, how to run testing on your data, and finally, how to visually present and interpret your data. This pod will focus on practical analysis of a pre-selected range of data sets suitable for beginners, and is designed to give students the statistics and analysis basics to do data analysis in future research.
Week by week curriculum
Week 1
Introduction to Research and Statistics: Students will learn key terms, be introduced to basic statistical concepts, and will begin to learn how to find research sources online.
Week 2
Data Collection Methods: Students will learn the different methods of data collection and analyze and how to apply them in different contexts. They will also learn more about the IRB process and how to ensure ethical data collection.
Week 3
Data Presentation and Visualization: Students will learn how to turn data into visual representations, and how this information should be formatted for inclusion in an academic journal.
Week 4
Descriptive Statistics: Students will learn the basics of calculating descriptive statistics and also how to interpret this information. Students will be specifically able to explain the meaning of different results, and how these numbers impact our knowledge of different relationships in the real world.
Week 5
Inferential Statistics: Students will learn how to develop a hypothesis statement and the meaning of a “p- value”. They will use this information to then run their own analysis on their data via a correlation or regression analysis.
Week 6
Review and Application: We will walk through the final layout of their final project, and how all previous learnings should be incorporated. Students will have the opportunity to asks questions about their specific projects and gain feedback. Students will also learn the importance of data interpretation, and how to apply this to their relevant field of interest.