Analysis of Variance

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Analysis of Variance

A process of determining similarities between like groups. Analysis of variance is used in marketing to determine how likely groups with similar demographic backgrounds are to respond to a particular campaign.
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Were calling on them to side with our communities and not support the Rio Grande LNG, Texas LNG, and Annova LNG projects, said Josette Cruz, Save RGV from LNG Coalition.
05 January 2017 - UK-based bespoke software systems provider Scisys plc (SSY: AIM) has closed the acquisition of Munich, Germany-based media software solutions company Annova Systems GmbH for a maximum consideration of USD 29.49m, the company said.
Table 3 shows the descriptive statistics along with one-way ANNOVA for five subscales of Urdu version of KOOS in OA knee patients who were classified according to Kellgren-Lawrence (K/L) grades I-IV based on their X-ray.
In ANNOVA and unpaired T test a "p" value of less than or equal to 0.05 were considered significant.
The significance of data was analysed by analysis of variance (ANNOVA) and the means were compared.
Joeveer (2006), who applied not only regression procedure but also the analysis of variance (ANNOVA), showed that the relative significance of country-specific and firm-specific factors in CEE countries (including Poland) depends on the firm profile.
One way analysis of variance is applied at 95% confidence level to find out the significance difference between the samples of each locality, Tukey's HSD tests were applied at 5% family error rate to classified the significance difference among samples, for ANNOVA and Tukey's HSD statistical programme MINITAB version 16.1 were used.
The ANNOVA table shows that there is no significant association among dependent and independent variables.
Houston-based Annova LNG, LLC filed a request with the Federal Energy Regulatory Commission to begin a review for a mid-scale natural gas liquefaction and transfer facility at the Port of Brownsville, TX.
ANNOVA test was applied for determining significance between different educational groups.
So, when posttest scores were compared, instead of covariant analyses, t-test or one way ANNOVA was sufficient.