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Autor:
M. D. Edge
Publikováno v:
Statistical Thinking from Scratch
In this chapter, the behavior of random variables is summarized using the concepts of expectation, variance, and covariance. The expectation is a measurement of the location of a random variable’s distribution. The variance and its square root, the
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https://explore.openaire.eu/search/publication?articleId=doi_________::0971999070c651357a9ae1ced8fba2df
https://doi.org/10.1093/oso/9780198827627.003.0006
https://doi.org/10.1093/oso/9780198827627.003.0006
Autor:
M. D. Edge
Publikováno v:
Statistical Thinking from Scratch
Point estimation is the attempt to identify a value associated with some underlying process or population using data. The unknown number that is the target of estimation is called an estimand. An estimator is a function that takes in data and produce
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https://doi.org/10.1093/oso/9780198827627.003.0008
https://doi.org/10.1093/oso/9780198827627.003.0008
Autor:
M. D. Edge
Publikováno v:
Statistical Thinking from Scratch ISBN: 0198827628
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b15311191de53b5920e3d72981012ab
https://doi.org/10.1093/oso/9780198827627.005.0001
https://doi.org/10.1093/oso/9780198827627.005.0001
Autor:
M. D. Edge
Publikováno v:
Statistical Thinking from Scratch ISBN: 0198827628
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9223272261ef47c94cb9270e6b185b99
https://doi.org/10.1093/oso/9780198827627.005.0002
https://doi.org/10.1093/oso/9780198827627.005.0002
Autor:
M. D. Edge
Publikováno v:
Statistical Thinking from Scratch
This chapter considers the rules of probability. Probabilities are non-negative, they sum to one, and the probability that either of two mutually exclusive events occurs is the sum of the probability of the two events. Two events are said to be indep
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https://doi.org/10.1093/oso/9780198827627.003.0005
https://doi.org/10.1093/oso/9780198827627.003.0005
Autor:
M. D. Edge
There are two traditional ways to learn statistics. One way is to pass over the mathematical underpinnings and focus on developing relatively shallow knowledge about a wide variety of statistical procedures. Another is to spend years learning the mat
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https://doi.org/10.1093/oso/9780198827627.003.0001
https://doi.org/10.1093/oso/9780198827627.003.0001
Autor:
M. D. Edge
Publikováno v:
Statistical Thinking from Scratch
R is a powerful, free software package for performing statistical tasks. It will be used to simulate data, analyze data, and make data displays. More details about R are given in Appendix B.
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https://doi.org/10.1093/oso/9780198827627.003.0003
https://doi.org/10.1093/oso/9780198827627.003.0003
Autor:
M. D. Edge
This chapter marks a turning point. The preceding two chapters considered probability theory, which describes the kinds of data that result from specified processes. The remainder of the book consider statistical estimation and inference, which start
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https://doi.org/10.1093/oso/9780198827627.003.0007
https://doi.org/10.1093/oso/9780198827627.003.0007
Autor:
M. D. Edge
Publikováno v:
Statistical Thinking from Scratch
Bayesian methods allow researchers to combine precise descriptions of prior beliefs with new data in a principled way. The main object of interest in Bayesian statistics is the posterior distribution, which describes the uncertainty associated with p
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https://doi.org/10.1093/oso/9780198827627.003.0012
https://doi.org/10.1093/oso/9780198827627.003.0012
Autor:
M. D. Edge
In virtually every field, researchers find themselves navigating tremendous amounts of new data. Making sense of this flood of information requires much more than the rote application of traditional statistical methods. This book will train researche
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https://explore.openaire.eu/search/publication?articleId=doi_________::dd24f71aa7d2f8e664058f6cdeed315c
https://doi.org/10.1093/oso/9780198827627.001.0001
https://doi.org/10.1093/oso/9780198827627.001.0001