
Coursera – Data Analysis and Statistical Inference
English | Size: 1.28 GB (1,376,028,414 Bytes)
Category: CBTs
Recognize the importance of data collection, identify limitations in data collection methods, and determine how they affect the scope of inference.
Use statistical software (R) to summarize data numerically and visually, and to perform data analysis.
Have a conceptual understanding of the unified nature of statistical inference.
Apply estimation and testing methods (confidence intervals and hypothesis tests) to analyze single variables and the relationship between two variables in order to understand natural phenomena and make data-based decisions.
Model and investigate relationships between two or more variables within a regression framework.
Interpret results correctly, effectively, and in context without relying on statistical jargon.
Critique data-based claims and evaluate data-based decisions.
Complete a research project that employs simple statistical inference and modeling techniques.
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