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Learn Statistical Methods, earn certificates with free online courses from University of Michigan, Johns Hopkins, Columbia University, Georgia Tech and other top universities around the world. Read reviews to decide if a class is right for you.
Explore longitudinal Australian poverty data, examining factors influencing household poverty status, persistence patterns, and community correlations from 2006 to 2016.
Discover the foundational concepts that support modern data science and learn to analyze various data types and quality to make smart business decisions.
Explore fractal and multifractal analysis methods for geophysical data, including self-similar and self-affine fractals, with demonstrations of software and applications to atmospheric and climate data.
Learn Python-based data analytics, covering statistics, probability, hypothesis testing, regression, ANOVA, clustering, and decision trees. Gain practical skills for data-driven decision making and statistical analysis.
Learn the fundamentals of data fluency and how data can help you make better decisions.
Learn how anyone, in any industry, can speak the language of data analysis. Find out how to prepare data, explore it visually, and describe it using statistical methods.
Comprehensive introduction to probability, distributions, and data analysis for graduate students. Develop skills in applying statistical methods, interpreting results, and using Minitab software for research and reporting.
Learn to analyze and forecast time series data using ARIMA models, smoothing methods, and advanced techniques. Gain practical skills in R for handling financial, medical, and weather-related temporal data.
Become a UX data scientist! From qualitative data analysis to big data Web analytics, you will be able to leverage insights from data to make empirically-based recommendations.
Define several types of observational studies, interpret their results, and describe how health registries can be used to make decisions about best clinical care.
The second in a series of four courses which help you to master statistics fundamentals and build your quantitative skillset for progression in high-growth careers, or to use as step towards further study at undergraduate level.
Comprehensive introduction to essential mathematical and statistical concepts, methods, and techniques for quantitative careers or further study. Covers calculus, linear algebra, probability, and statistical analysis.
Learn why a statistical method works, how to implement it using R and when to apply it and where to look if the particular statistical method is not applicable in the specific situation.
The objective of the course is to introduce basic concepts and statistical methods employed for assurance of quality in products, processes and systems in an industrial environment
Master hypothesis testing for two means and proportions in independent and dependent samples, covering large and small sample sizes.
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