This tutorial assumes preliminary knowledge of basic applied statistics from a bachelor degree in natural sciences or engineering and aims to extend this on a problem-oriented level. This means that while some essential concepts are repeated, more serious gaps have to be filled up by self study. The main focus is to establish a certain degree of “statistical feeling”, therefore statistical theory is mostly skipped and should be taken from textbooks for full understanding.
Data Analysis with R Selected Topics and Examples 2018.pdf
(1.2 MB, 需要: 8 个论坛币)
Contents:
2 An Introductor y R Session
3 Basic Principles andTerminology
4 Statistical Parameters
5 Distributions
6 Classical tests
7 Correlation and regression
8 Time Series Analysis
9 Multivariate statistics


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