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Learn how to incorporate propensity score matching into your quantitative research design to reduce selection bias and estimate causal effects.
Learn how to choose, label, describe, evaluate, and apply clusters in quantitative research. Find out how to make sense of and communicate clustering insights.
Learn about the different types of cluster analysis, their applications, challenges, advances, and future directions in quantitative research.
Learn how to compare and benchmark different neural network models and algorithms for quantitative forecasting with practical tips and best practices.
Learn how machine learning can help you optimize your asset allocation, measure your downside risk, and handle complex market conditions.
Learn how to use internal and external validation metrics to measure the quality and validity of your clusters in unsupervised learning.
Learn how to engage stakeholders and communicate cluster randomized trial results in a clear and meaningful way with this article.
Learn how to use pilot testing and pretesting to reduce measurement error and bias, and to enhance the validity and reliability of your quantitative research…
Learn how to deal with missing, noisy, or irregular data in time series classification using imputation, filtering, transformation, or adaptation methods.
Learn about the applications of cluster analysis in education policy and practice, and how it can reveal patterns, trends, and relationships in data.
Learn how to communicate and visualize cluster analysis findings to stakeholders in education using tips and best practices for clarity, conciseness, and impact.
Learn best practices for writing clear and concise captions for your data tables and figures in quantitative research. Improve your data communication skills.
Learn how to handle the data quality and availability issues that affect machine learning applications in quantitative finance. Discover strategies to check…
Learn what t-tests and z-tests are, what assumptions they make, and what limitations they have in quantitative research. Find out how to check and address these…
Learn six steps and best practices for designing a rigorous and reliable randomized controlled trial (RCT) to measure the impact of a new product feature on your…
Learn some methods to analyze and report the results of randomized controlled trials (RCTs) using statistical software, such as R, Stata, or SPSS.
Learn how to develop and improve your quantitative research skills and competencies in six steps, from identifying your research problem to reflecting on your…
Learn how to select the most relevant and informative variables and features for clustering, and how to preprocess, transform, and validate them.
Learn how to create effective data visualizations for quantitative research and storytelling. Avoid common pitfalls and follow these tips.
Learn how to collaborate and share your quantitative data and code with other researchers and practitioners using tips and tools for data format, documentation…
Learn the key concepts and steps to select a suitable sampling method for your quantitative research project. Discover how to overcome the challenges and biases in…
Learn the main steps and challenges of conducting randomized controlled trials (RCTs) to test the causal effects of interventions in quantitative research.