Michael Thomas Flanagan's Java Library
Regression Class

Lots of functionality for multiple regressions

Michael Thomas Flanagan's Java Library: Class Regression

The general purpose of multiple regression (the term was first used by Pearson, 1908) is to learn more about the relationship between several independent or predictor variables and a dependent or criterion variable. For example, a real estate agent might record for each listing the size of the house (in square feet), the number of bedrooms, the average income in the respective neighborhood according to census data, and a subjective rating of appeal of the house. Once this information has been compiled for various houses it would be interesting to see whether and how these measures relate to the price for which a house is sold. For example, one might learn that the number of bedrooms is a better predictor of the price for which a house sells in a particular neighborhood than how "pretty" the house is (subjective rating). One may also detect "outliers," that is, houses that should really sell for more, given their location and characteristics.

Multiple Regression Analysis

Together, the couple stalked an elusive sequence of DNA hidden in the heredity of every human cell. The wayward strand appeared to seek out developing brain cells and, like a virus, arbitrarily alter their genetic makeup.

In this way, it might be partly responsible for the infinite variety of the mind.

Brain's Darwin Machine - Los Angeles Times

This Electronic Statistics Textbook offers training in the understanding and application of statistics. The material was developed at the StatSoft R&D department based on many years of teaching undergraduate and graduate statistics courses and covers a wide variety of applications, including laboratory research (biomedical, agricultural, etc.), business statistics and forecasting, social science statistics and survey research, data mining, engineering and quality control applications, and many others.
The Electronic Textbook begins with an overview of the relevant elementary (pivotal) concepts and continues with a more in depth exploration of specific areas of statistics, organized by "modules," accessible by buttons, representing classes of analytic techniques. A glossary of statistical terms and a list of references for further study are included.

Electronic Textbook StatSoft

This glossary provides definitions for terms, concepts, and methods frequently encountered in morphometric literature and discussions. It includes entries for technical terms with more-or-less special meaning in shape analysis and biological morphometrics (e.g., preshape, warps, anisotropy) and some of the casual jargon that may be completely foreign to newcomers to the field (e.g., books of various color - Red, Blue, Orange, and Black). Many definitions provide the general idea behind each entry instead of a technically or mathematically rigorous treatment. As such, they are intended to give readers an intuitive understanding of a particular entry that will allow them to follow the main ideas in the literature without becoming unduly distracted, at first, with technical details. Unless otherwise indicated, the following general notation has been used: n - number of specimens, p - number of points/landmarks, k - number of dimensions, a superscript t will refer to the transpose of a matrix (e.g., At, but that may not be displayed properly by all WWW browsers). Members of the morphometrics community, especially the subscribers to the MORPHMET electronic mailing list, have helped greatly in the selection of terms to be included in the glossary.

Geometric morphometrics glossary (part 1)

public class Regression

Regression - Java

regression analysis is used to model the relationship between random variables: One or more response variables or dependent variables (usually named Y), and the predictors (also called input variables, independent variables or explanatory variables), usually named X1,...,Xp). If there is more than one response variable, we speak of multivariate regression, which is not covered in this article.

Regression analysis is most commonly associated with fitting a curve (function) to some set of measurement data (curve fitting), but it can have several objectives:

* Prediction of future observations, as by curve fitting
* Determining how closely the response can be predicted by the predictor
* Assessing the relationship between the predictors

Regression analysis - Wikipedia, the free encyclopedia

What is SOCR?

It's is online, therefore it exists!

SOCR LogoThe goals of the SOCR Resource are to design, validate and freely disseminate knowledge. Our Resource specifically provides portable online aids for probability and statistics education, technology based instruction and statistical computing. SOCR tools and resources include a repository of interactive applets, computational and graphing tools, instructional and course materials.

SOCR: Statistics Online Computational Resource

The ANOVA Applet should open on its own. If you do not see it in the next 5 seconds it pronbably means your browser is NOT Java-enabled!

Analysis of variance (ANOVA) performs comparisons like the t-Test, but for an arbitrary number of factors. Each factor can have an arbitrary number of levels. Furthermore each factor combination can have any number of replicates. ANOVA works on a single dependent variable. The factors must be discrete. The ANOVA can be thought of in a practical sense as an extension of the t-Test to an arbitrary number of factors and levels. It can also be thought of as a linear regression model whose independent variables are restricted to a discrete set.

ANOVA Java Applet

In general, these documents are intended to reflect current practices and customs, and we have attempted to note where the West Coast and East Coast differ in a number of their practices. However, one of our goals in drafting these documents is also to reflect "best practices" and avoid hidden legal traps, even if doing so means straying from current custom and practice. We have attempted to avoid, or at least point out, certain problematic provisions that have become "market standard" terms. We have generally tried to indicate such issues with a footnote and explanatory language.

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