FA19: Statistical Modeling and Regression Analysis
2.5
Edx259 learners
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This course FA19: Statistical Modeling and Regression Analysis provides an introduction to the fundamentals of regression analysis. You will learn the basics of linear regression, logistic regression, Poisson regression, generalized linear regression and model selection. You will also gain experience in using the R statistical software to implement and interpret regression models. This course is designed to help you develop the skills to apply regression analysis to real-world data.
Statistical Inference and Hypothesis Testing in Data Science Applications
3.0
Coursera82 learners
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This course will teach students about the theory and implementation of hypothesis testing in data science applications. Students will learn to use hypothesis tests to make informed decisions from data, including the general logic of hypothesis testing, error and error rates, power, simulation, and the correct computation and interpretation of p-values. The ethical implications of misuse of testing concepts will also be discussed. This course is part of the MS-DS degree offered on the Coursera platform.
Studying Cities: Social Science Methods for Urban Research
1.5
Coursera0 learners
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This course, Studying Cities: Social Science Methods for Urban Research, provides an introduction to the research cycle and the necessary tools to understand and evaluate key steps in scientific research. Through video lectures, in-video questions, and a final peer review, you will gain insight into the different steps of the research cycle, build a firm foundation for your own future research endeavors, and learn the components and criteria of the theoretical framework and operationalization, research strategies, and the collection and analysis of quantitative and qualitative data.
Essentials of Data Science With R Software - 1: Probability and Statistical Inference
1.5
Youtube4 learners
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This course provides an introduction to the essentials of data science with R software, focusing on probability and statistical inference. Students will learn the fundamentals of probability theory and statistical inference, and how to apply them to data analysis. They will also gain an understanding of how to use R software to implement these concepts and draw correct statistical conclusions.
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