a statistical technique by which the results of an observation or experiment are analyzed to determine the relative contributions of the different possible causative factors or variables to the outcome. Abbreviated ANOVA.

(ANOVA) a basic statistical technique for analyzing experimental data. It subdivides the total variation of a data set into meaningful component parts associated with specific sources of variation in order to test a hypothesis on the parameters of the model or to estimate variance components. ANOVA is used to test whether the means of many samples differ but it does so using variation instead of mean. It compares the amount of variation within the samples to the amount of variation between the means of samples. If the 'between variation' is significantly larger than the 'within variation', we conclude that the mean of our response has changed. Click here for more.

A statistical method used to determine whether a relationship exists among two or more variables by formulating concurrent comparisons of the variables.

A perversely titled technique to test whether there is a difference between a set of sample means. The simplest form of analysis of variance looks at the means classified by just one factor, eg. the factor UK nationality would produce four means: English, Irish, Scottish and Welsh. Two-way analysis of variance can handle a second factor as well, eg. Gender: male, female. This way you can look at both factors simultaneously, effectively English male, English female, Irish male, Irish female, etc. The name of the technique includes the word variance because it calculates the variation between the factor means and uses this as the basis of the test.

A widely-used statistical inference technique, based on comparing the variance between samples with the variance within samples. This can tell us whether there is any systematic difference between samples that needs to be explained. See also sample, statistical analysis, variance.

a statistical test which compares the distribution of two or more sample groups to determine if one or more of the groups are significantly different from the others

a statistical technique used to determine whether the difference between two or more sets of scores is statistically significant. 653

A statistical test showing the effects of an “independent variable” on a “dependent variable”; a technique to determine whether there are “statistically significant” differences of “means” between two or more groups.

A statistical method for evaluating the difference among means.

A mathematical process for separating the variability of a group of observations into assignable causes and setting up various significance tests.

A method for analyzing the differences in the means of two or more groups of cases.

(also called ANOVA). A data analytic procedure that partitions the variability into components that are attributed to various factors. The variability that cannot be so explained is called the residual or error variability. The sources of variation are presented as the rows of an analysis of variance table in which the columns represent sums-of-squares, degrees of freedom, and mean squares.

a test that measures the difference between the means of two or more groups

Parametric statistical comparison test for two or more data sets

A statistical analysis by which variance ratios are compared in such a manner as to determine the probability that differences among populations or treatments are too large to be due to chance.

A statistical method for determining the variation in a set of data. ANOVA is used to test whether or not a hypothesis is based on the parameters.

An analytical technique to determine differences among means of two or more variables.

a method of testing metric variables against a single dependent categorical measure to determine whether or not the means differ across all groups.

A statistical technique for testing whether or not, the means of two or more populations are equal. Also known as ANOVA.

A basic statistical technique for analyzing experimental data. It subdivides the total variation of a data set into meaningful component parts associated with specific sources of variation in order to test a hypothesis on the parameters of the model or to estimate variance components. There are three models: fixed, random and mixed.

An analysis of the variation in the outcomes of an experiment to assess the contribution of each variable to such variation.

A technique used to improve the analysis over regression techniques. It can be used for identifying relationships between predictor and criterion variables, whether the predictor variables are quantitative or qualitative in nature.

is a statistical test that is commonly used in regression analysis. ANOVA is used for intercomparison of mean responses to a number of different factors or to a different level of the same factor. [pg. 171-190, 2

Statistical method that yields values that can be tested to determine whether a significant relation exists between variables.

A method for determining the proportion of the variation in a sample that is explained by one or more classification factors.

A statistical procedure that determines whether or not there are any differences among two or more groups of subjects on one or more factors. The F test is used in ANOVA.

In statistics, analysis of variance (ANOVA) is a collection of statistical models and their associated procedures which compare means by splitting the overall observed variance into different parts. The initial techniques of the analysis of variance were pioneered by the statistician and geneticist Ronald Fisher in the 1920s and 1930s, and is sometimes known as Fisher's ANOVA or Fisher's analysis of variance