Publications by rtutor.chiyau
Elementary Statistics with R
Ever wonder how to finish your statistics homework real fast? Or you just want a quick way to verify your tedious calculations in your statistics class assignment. We provide an answer here by solving statistics exercises with R. read more Related To leave a comment for the author, please follow the link and comment on their blog: R Tutorial....
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Analysis of Variance
In an experiment study, various treatments are applied to test subjects and the response data is gathered for analysis. A critical tool for carrying out the analysis is the Analysis of Variance (ANOVA). It enables a researcher to differentiate treatment results based on easily computed statistical quantities from the treatment outcome. read more...
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Multiple Linear Regression
A multiple linear regression (MLR) model that describes a dependent variable y by independent variables x1, x2, …, xp (p > 1) is expressed by the equation as follows, where the numbers α and βk (k = 1, 2, …, p) are the parameters, and ϵ is the error term. read more Related To leave a comment for the author, please follow the link and co...
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Non-parametric Methods
A statistical method is called non-parametric if it makes no assumption on the population distribution or sample size. This is in contrast with most parametric methods in elementary statistics that assume the data is quantitative, the population has a normal distribution and the sample size is sufficiently large. read more Related To leave...
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Type II Error
In hypothesis testing, a type II error is due to a failure of rejecting an invalid null hypothesis. The probability of avoiding a type II error is called the power of the hypothesis test, and is denoted by the quantity 1 – β . read more Related To leave a comment for the author, please follow the link and comment on their blog: R Tutorial...
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GPU Computing with R
Statistics is computationally intensive. Routine statistical tasks such as data extraction, graphical summary, and technical interpretation all require heavy use of modern computing machinery. Obviously, these tasks can benefit greatly from a parallel computing environment where multiple calculations can be performed simultaneously. read more R...
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Hierarchical Cluster Analysis
With the distance matrix found in previous tutorial, we can use various techniques of cluster analysis for relationship discovery. For example, in the data set mtcars, we can run the distance matrix with hclust, and plot a dendrogram that displays a hierarchical relationship among the vehicles. read more Related To leave a comment for the aut...
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Kendall Rank Coefficient by GPU
The correlation coefficient is a measurement of correlation between two random variables. While its computation is straightforward, it is not readily applicable to non-parametric statistics. read more Related To leave a comment for the author, please follow the link and comment on their blog: R Tutorial. R-bloggers.com offers daily e-mail up...
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Support Vector Machine with GPU
Most elementary statistical inference algorithms assume that the data can be modeled by a set of linear parameters with a normally distributed noise component. A new class of algorithms called support vector machine (SVM) remove such constraint. read more Related To leave a comment for the author, please follow the link and comment on their bl...
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Support Vector Machine with GPU, Part II
In our last tutorial on SVM training with GPU, we mentioned a necessary step to pre-scale the data with rpusvm-scale, and to reverse scaling the prediction outcome. This cumbersome procedure is now simplified with the latest RPUSVM. read more Related To leave a comment for the author, please follow the link and comment on their blog: R Tutori...
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