Sentences with phrase «many analyses of variance»

Many statistical techniques, including analysis of variance and linear regression, were developed by evolutionary biologists, especially Ronald Fisher and Karl Pearson.

One - way analysis of variance was used to compare the mean number of nutrients that were correctly identified for different labelling systems (continuous data), followed by Scheffe post hoc testing.

We compared socio - demographic and pregnancy - related characteristics among the three study groups using chi - square tests for categorical variables, analysis of variance (ANOVA) for normally distributed continuous variables and the nonparametric Kruskal - Wallis test for continuous variables that were not normally distributed.

For variables with normal distribution, one way analysis of variance was used to compare mean values.

Practically every scientist uses statistics — from pharmacologists employing regression to understand the relation between the dose of a drug and its effects in the body, to agronomists using analysis of variance to test which fertilizer makes crops grow fastest.

Using analysis of variance, t - tests, or chi - square tests as appropriate, we compared the clinical characteristics among exposure groups and among subjects with World Trade Center cough according to prognostic subgroups: those with predominantly upper - airway symptoms (29 subjects) or lower - airway symptoms (95 subjects) or those with bronchial responsiveness (249 subjects).

For each stimulation site (entorhinal and hippocampal), we completed a two (stimulation vs. nonstimulation condition) by three (blocks 1, 2, and 3) repeated - measures analysis of variance for latency and excess path length.

Genome - wide analysis of variance (ANOVA) revealed that germline SNPs / CNVs and somatic CNAs influenced > 39 % of gene expression probes, roughly half acting in cis and half in trans.

Statistical analysis of One - way Analysis of Variance (ANOVA) and Two - way Analysis of Variance (ANOVA) was carried out for comparing two data groups using GraphPad Prism 6 software for all experiments conducted in duplicates.

Associations between continuous AQUA scores and clinical / pathological parameters were assessed by analysis of variance.

For continuous variables that were normally distributed, we used Student's t test or the one - way analysis of variance.

An analysis of variance of group differences in pre - to post-intervention changes in plasma Aβ40 levels was significant (P < 0.05; Supplementary Table S9).

The analysis of variance for group differences in the ratio of Aβ42 / Aβ40 was significant (P < 0.001; Supplementary Table S9).

The analysis of variance of group differences in change scores was marginally significant (P < 0.08; Supplementary Table S9).

A one - way analysis of variance (ANOVA) was used to assess variations in the time spent by fish in the focal region or in each compartment of the focal region (front, B1, B2, B3, and B4 for the Top view and top, middle, and bottom for the Side view, respectively) among the experimental conditions.

Statistical analyses were made using either Student's two - tailed unpaired t test or analysis of variance (ANOVA) as specified in the figure legends, and Newman - Keuls procedure was used for multiple comparison analysis.

Exposing stats illusions Shalizi warns «causal - sounding phrases... encourage confusion» in many analyses of variance studies (where «due to,» «explained by,» «account for» don't have ordinary meanings).

* P < 0.05, one - way analysis of variance (ANOVA) followed by Tukey's post hoc test.

Statistical analysis was carried out by analysis of variance and Student's t test (two - tailed) as indicated.

The proteins considered in the unsupervised hierarchical clustering analysis were quantified in individual samples and found to be significantly different in abundance by analysis of variance (ANOVA p ≤ 0.01, Table S3); while PCA analysis considered all proteins quantified in each individual sample.

Analysis of variance (ANOVA) statistical comparisons were performed using Statview Software (SAS Institute, Inc., Cary, NC, USA, http://www.jmp.com) with statistical significance set at 0.05.

Assay, sample and side - to - side variation were quantified by analysis of variance and presumptively incorrect decisions related to high - risk disease were determined using the result from each MRD assay, the mean MRD in the patient as the measure of the true value, and each of 3 different MRD cut - off levels which have been used for making decisions on treatment.

«Analysis of variance indicated no significant effect of boron supplementation on any of the dependent variables.

Pre-massage and post-massage data were analyzed using analysis of variance (ANOVA).

General characteristics were compared with analysis of variance with Tukey's post hoc comparisons, and qualitative variables were compared with chi - square tests.

A 2 - way analysis of variance (condition × time) with repeated measures was performed on all dependent variables recorded in the precondition and postcondition tests.

A 2 - way analysis of variance (ANOVA) with repeated measures (time) was performed on all dependent variables recorded in the precondition and postcondition tests (SPSS).

The obtained data were analyzed through the use of the analysis of variance (ANOVA).

A 2 × 2 (trial × gender) analysis of variance with repeated measures and appropriate post hoc was used to analyze the data.

In this course, students will learn how to use a set of quantitative methods referred to as the general linear model — regression, correlation, analysis of variance, and analysis of covariance — to address these and other questions that arise in educational, psychological, and social research.

In simplest terms, the statistical procedure of the Coleman Report relies on a problematic stepwise analysis of variance approach, which makes strong assumptions about which factors are fundamental causes of achievement and which are of secondary significance.

Like many other statistically minded social scientists of his time, he thought of regression and analysis of variance as tools that did not merely break an outcome, such as achievement, into partial correlations.

A statistically significant MANOVA, F (14, 108) = 2.56, p <.01, led us to conduct follow - up univariate analyses of variance (ANOVAs; see Table 11).

To investigate the relationship between school effectiveness and classroom instruction, we initially conducted a multivariate analysis of variance (MANOVA) with the school effectiveness rating serving as the independent variable and eight teacher variables serving as outcome measures (see Table 11).

Statistical techniques do exist such as Analysis of Variance... Read More

For research questions 2, an analysis of variance (ANOVA) was used to identify students» procedural knowledge in areas of fraction concepts and whether there was a significant difference on posttest results between the experimental and control group students» correct answers.

Some of the statistics assignment topics in which we have assisted students are: Standard deviation, analysis of variance, binomial distribution, tree diagram, simplex method, vital statistics, operations research, game theory, normal distribution, skewness and many other.

An initial mixed model was fit by performing a split plot repeated measures analysis of variance (ANOVA) on the rank transformed energy values.

We used a 2 - way analysis of variance (ANOVA) and Tukey honestly significant difference (HSD) tests to determine the effects of sex and reproductive status (treatment = intact versus sterilized) on the areas of the home ranges occupied by our study animals during the breeding and nonbreeding seasons.

A regression analysis points to a clear link between GCR and the aa - index, and the analysis of variance yields R2 = 0.1466 and the p - value = 0.

BPL: Do an analysis of variance.

Have you ever heard of «analysis of variance?»

In fact, there's a wonderful variant of PDM based on the analysis of variance, developed for astronomy, which not only gives excellent results, it's also optimized for statistical efficiency and minimum computational workload (which really helps when analyzing terabyte databases such as come from modern satellite missions).

The first Analysis of Variance I was asked to perform was by hand, before even calculators were easily available.

«In addition to «analysis of variance», Fisher invented the technique of maximum likelihood and originated the concepts of sufficiency, ancillarity, Fisher's linear discriminator and Fisher information.

His 1924 article «On a distribution yielding the error functions of several well known statistics» presented Karl Pearson's chi - squared and Student's t in the same framework as the Gaussian distribution, and his own «analysis of variance» distribution z (more commonly used today in the form of the F distribution).

Statisticians have dealt with this problem of separating effects in unbalanced Analysis of Variance designs in the past.

Or you could do an analysis of variance (ANOVA) using whatever categorizing variables you want.

In this study, the potential predictability of seasonal variations in extratropical storm activity is investigated using analysis of variance to provide quantitative and geographical observational evidence indicative of whether it may be possible to predict storm activity on the seasonal timescale.

The data were analysed using a 2 (framing: loss vs. foregone - gain) × 3 (social norm: control vs. average - norm vs. rank - norm) between - participants Analysis of Variance (ANOVA [37]-RRB- performed using the anova function from the CAR package in the statistical computing software R (used for all subsequent statistical analyses).