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Analysis of variance       Article     History   Tree Map
  Encyclopedia of Keywords > Glossaries > Glossary of Statistics > Analysis of Variance /   Michael Charnine

Keywords and Sections
LINEAR MODELS
TWO-WAY ANALYSIS OF VARIANCE
MULTIPLE COMPARISONS
FRIEDMAN TEST
MEANS
FACTORIAL
DESIGN
INTERACTION
ANOVA
REGRESSION ANALYSIS
MULTIPLE REGRESSION
MULTIVARIATE ANALYSIS OF VARIANCE
EXPERIMENTAL DESIGN
DISCRIMINANT ANALYSIS
VARIANCE
LECTURE
DISCRIMINANT FUNCTION
MULTIPLE DEPENDENT
F-DISTRIBUTION
ONE-WAY ANALYSIS OF VARIANCE
Review of Short Phrases and Links

    This Review contains major "Analysis of Variance"- related terms, short phrases and links grouped together in the form of Encyclopedia article.

Definitions

  1. Analysis_of_variance is used to compare variances from more than two groups.
  2. Analysis_of_variance is a technique for analyzing experimental data.
  3. Analysis_of_variance is used to test the hypothesis that several means are equal.
  4. Analysis_of_variance is a statistical technique which may be used for making many simultaneous comparisons (e.g.
  5. Analysis_of_Variance is a very useful and powerful technique for this, and not surprisingly it is widely used throughout the behavioral sciences.

Linear Models

  1. All of these are available in PROC NPAR1WAY (nonparametric 1-way analysis_of_variance) in SAS.
  2. Topics include elementary analysis_of_variance, simple linear regression; topics related to analysis_of_variance and experimental designs.
  3. It could also be used to supplement an intermediate or advanced course on linear models, analysis_of_variance, or variance components.
  4. Topics include advanced graphical procedures, linear models (regression and analysis_of_variance), multivariate techniques, and SAS macros.

Two-Way Analysis of Variance

  1. A one-way analysis_of_variance was conducted to evaluate the effect of consumption of alcohol on reaction time.
  2. The example Example: Two-Way ANOVA uses two-way analysis_of_variance to study the effect of car model and factory on car mileage.
  3. The initial techniques of the analysis_of_variance were pioneered by the statistician and geneticist Ronald Fisher in the 1920s and 1930s.
  4. Review the Results Figure 11.10 displays the analysis_of_variance table and the parameter estimates.
  5. Tatsuoka, M. (1975). The general linear model: A "new" trend in analysis_of_variance.

Multiple Comparisons

  1. Multiple comparisons tests for an analysis_of_variance may be applied when the effects are fixed.
  2. Most people use computer programs to perform the Analysis_of_Variance and multiple comparison tests.
  3. Use S-PLUS to do an analysis_of_variance with the Scheffe method for multiple comparisons.

Friedman Test

  1. Interpretation: The Friedman test can be seen as a two-way analysis_of_variance with one observation per cell.
  2. The Friedman test is used for two-way repeated measures analysis_of_variance by ranks.
  3. Correlation regression analysis_of_variance and nonparametric tests.

Means

  1. In general, the purpose of analysis_of_variance (ANOVA) is to test for significant differences between means.
  2. Note that analysis_of_variance tests the null hypotheses that group means do not differ.
  3. This post hoc test can be used to determine the significant differences between group means in an analysis_of_variance setting.

Factorial

  1. Prerequisites include a course on factorial analysis_of_variance.
  2. Analysis_of_variance for factorial designs.

Design

  1. Experimental design with emphasis on analysis_of_variance.
  2. Prerequisite: EDMS 645. A second-level inferential statistics course with emphasis on analysis_of_variance procedures and designs.

Interaction

  1. In a two factor analysis_of_variance, such comparisons can involve either main effect of interaction means.
  2. Recall the classical analysis_of_variance gave a p-value to test column effects, row effects, and interaction effects.

Anova

  1. Example with a one-way analysis_of_variance ( ANOVA) with 3 groups and 7 observations.
  2. Since it is a non-parametric method, the Kruskal-Wallis test does not assume a normal population, unlike the analogous one-way analysis_of_variance.
  3. This review introduces one-way analysis_of_variance, which is a method of testing differences between more than two groups or treatments.
  4. In a one-way analysis_of_variance, we may think of the data as consisting of g independent samples (possibly of different sizes) from g populations.
  5. The example Example: One-Way ANOVA uses one-way analysis_of_variance to determine if the bacteria counts of milk varied from shipment to shipment.

Regression Analysis

  1. Some statistical measures include regression analysis, mean, kurtosis, skewness, analysis_of_variance and variance.
  2. Least squares principles used to integrate topics of multiple linear regression analysis, the analysis_of_variance and analysis of covariance.
  3. Currently listed as STAT 689. The analysis of messy and complex data sets using analysis_of_variance, analysis of covariance and regression analysis.

Multiple Regression

  1. Multiple regression with dummy variables yields the same inferences as multiple analysis_of_variance (MANOVA), to which it is statistically equivalent.
  2. A continuation of STA 3381. Development and applications of two-sample inference, analysis_of_variance and multiple regression.
  3. Multiple regression and analysis_of_variance, with emphasis on statistical inference and applications to various fields.

Multivariate Analysis of Variance

  1. Fundamental concepts and analytical skills in analysis_of_variance, including crossed and nested designs, as well as fixed- and random-effect models.
  2. Further, one can use proc glm for analysis_of_variance when the design is not balanced.
  3. Inference for the multivariate normal distribution, including Hotelling's T - and multivariate analysis_of_variance.
  4. There are several statistical methods for analyzing designs with random effects (see Methods for Analysis_of_Variance).
  5. In multivariate analysis_of_variance, you instead look for the linear combination of the original variables that has the largest separation between groups.

Experimental Design

  1. ISBN 0-471-21187-7 Lindman, H. R. (1974). Analysis_of_variance in complex experimental designs.
  2. Prerequisites: BIOM 601 or (BIOM 402 and BIOM 405). Also offered as AGRO 804. The principles of experimental design and analysis_of_variance and covariance.

Discriminant Analysis

  1. Topics covered including multivariate analysis_of_variance, discriminant analysis, canonical correlation analysis and principal components analysis.
  2. Analysis of molecular variance (AMOVA) : A statistical (analysis_of_variance) method for analysis of molecular genetic data.
  3. Analysis of covariance (ANCOVA) is a blending of regression and analysis_of_variance (Roscoe, 1975).
  4. In this paper, multivariate analysis_of_variance (MANOVA) and discriminant analysis (DA) are used.
  5. It includes hypothesis testing, regression and correlation analysis and analysis_of_variance.

Variance

  1. The computation for the Brown-Forsythe test for equal variance is also similar to the computation for the one-way analysis_of_variance.
  2. The computation for Levene-s test for equal variance is similar to the computation for the one-way analysis_of_variance.
  3. Response: ICC (1) is based on the assumptions of the analysis_of_variance that within-group variance is error.

Lecture

  1. This lecture presents some of the basic concepts that underlie the analysis_of_variance.
  2. This lecture discusses the importance and implications of statistical power both in general and with specific reference to the analysis_of_variance.

Discriminant Function

  1. Stated in this manner, the discriminant function problem can be rephrased as a one-way analysis_of_variance (ANOVA) problem.
  2. This lectures introduces the multivariate analysis_of_variance (manova) and its statistical counterpart, discriminant functions analysis (dfa).

Multiple Dependent

  1. This extension of the Mann-Whitney U test to multiple samples is a nonparametric alternative to one-way analysis_of_variance.
  2. ANOVA (analysis_of_variance): A test for significant differences between multiple means by comparing variances.
  3. Multivariate Analysis_of_Variance (MANOVA) is an extension of the concepts and techniques of ANOVA to situations with multiple dependent variables.
  4. Related analysis_of_variance for fixed, random, and mixed effects models, multiple comparison procedures.
  5. The techniques will include least squares analysis_of_variance and covariance, multiple and polynomial regression, and multiple discrimination.

F-Distribution

  1. The F-distribution, which is the distribution of the ratio of two (normalized) chi-square distributed random variables, used in the analysis_of_variance.
  2. F-distribution: A family of probability distributions used for hypothesis tests in analysis_of_variance and regression.

One-Way Analysis of Variance

  1. Description : Statistical analyses include t-tests, analysis_of_variance, rates and proportions, nonparametric methods and regressions.
  2. One and two sample t-tests, one-way analysis_of_variance, inference for count data and regression.
  3. Critchlow DE, Fligner MA. On distribution-free multiple comparisons in the one-way analysis_of_variance.
  4. Books about "Analysis of Variance" in Amazon.com

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  Originally created: August 16, 2007.
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