Bias-Variance Theory
Bias-Variance Theory

Package `RMKdiscrete`
Package `RMKdiscrete`

Markov Chains and Monte Carlo Methods
Markov Chains and Monte Carlo Methods

A conceptual interpretation of the renewal theorem with applications
A conceptual interpretation of the renewal theorem with applications

Biased and Unbiased Estimation of the Circular Mean Resultant
Biased and Unbiased Estimation of the Circular Mean Resultant

... variance values, the median, quartiles and lowest and highest decile is shown. Additionally, all variances are multiplied by the sample size n because, as for the linear case, the variance decreases with n by an order of n1 . In this way, the plot can show more details. The fact that the lower quart ...
Credibility - Casualty Actuarial Society
Credibility - Casualty Actuarial Society

Hypothesis Testing in Linear Regression Models
Hypothesis Testing in Linear Regression Models

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Significance Testing
Significance Testing

Causality in Econometrics (3)
Causality in Econometrics (3)

On the Size Distribution of Macroeconomic Disasters
On the Size Distribution of Macroeconomic Disasters

searching for narrow emission lines in x
searching for narrow emission lines in x

Describing Distributions with Numbers
Describing Distributions with Numbers

2766 - Emerson Statistics
2766 - Emerson Statistics

Exercise-book - Part-III Continuous distributions in one-dimension -
Exercise-book - Part-III Continuous distributions in one-dimension -

Gigerenzer`s normative critique of Kahneman and Tversky
Gigerenzer`s normative critique of Kahneman and Tversky

Document
Document

Elementary Statistics on the TI-83 and TI-84
Elementary Statistics on the TI-83 and TI-84

Correlation and Regression
Correlation and Regression

Lecture 7: Average value-at-risk
Lecture 7: Average value-at-risk

Introduction to Markov Random Fields
Introduction to Markov Random Fields

... Conditional Random Fields A special type of a Markov Random Field, a Conditional Random Field allows that each random variable may also be conditioned upon a set of global observations. Define G = (V, E) to be an undirected graphical Markov Random Field model over random variable (Xv )v∈V and O a ra ...
Formalization of Normal Random Variables
Formalization of Normal Random Variables

CHOICE, CHANCE, AND INFERENCE An Introduction to
CHOICE, CHANCE, AND INFERENCE An Introduction to

Interpreting Null Results - Journal of Articles in Support of the Null
Interpreting Null Results - Journal of Articles in Support of the Null

... Journal of Articles in Support of the Null Hypothesis. JASNH, 2002, Vol. 1, No. 3 In summary, when H0is true, it is likely that we will fail to reject it. When H0 is false, we may also fail to reject H0 due to low statistical power. In both cases, our conclusion is to fail to reject the null hypothe ...
Estimating the Value of a Parameter Using Confidence Intervals
Estimating the Value of a Parameter Using Confidence Intervals

History of statistics

The History of statistics can be said to start around 1749 although, over time, there have been changes to the interpretation of the word statistics. In early times, the meaning was restricted to information about states. This was later extended to include all collections of information of all types, and later still it was extended to include the analysis and interpretation of such data. In modern terms, ""statistics"" means both sets of collected information, as in national accounts and temperature records, and analytical work which requires statistical inference.Statistical activities are often associated with models expressed using probabilities, and require probability theory for them to be put on a firm theoretical basis: see History of probability.A number of statistical concepts have had an important impact on a wide range of sciences. These include the design of experiments and approaches to statistical inference such as Bayesian inference, each of which can be considered to have their own sequence in the development of the ideas underlying modern statistics.