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).
Not exact matches
If large
variances exist between an investor's independent
analysis and a company's depiction, further
study should be done to either reconcile differences or confirm a company's mischaracterization
of its customer base.
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.
In their
analysis of data from 1423 Swedish women who were
studied from 2.5 to 12 mo postpartum, lactation score was significantly associated with weight retention, but it explained little
of the
variance in PPWR.
The authors note that while the sample size
of the meta -
analyses was large (123,132 to 260,861 participants in different
studies), they used only GWAS summary statistics and can not estimate all genetic
variance factors; some
studies also used different methodologies.
A 2005 meta -
analysis study on BMR * showed that when controlling all factors
of metabolic rate, there is still a 26 % unknown
variance between people.
Russ makes three arguments: 1) A recent
study that compared grit scores among fraternal and identical twins suggests that grit may be heritable to a large degree, which would make it unrealistic to expect schools or others to be able to alter it; 2) The twin
study as well as a meta -
analysis of grit research found that grit only explains about 2 - 3 %
of the
variance in achievement scores, which Russ thinks makes it a poor predictor
of other outcomes; and 3) The meta -
analysis suggests that grit may be highly correlated with conscientiousness, one
of the Big 5 personality traits that psychologists have been
studying for a long time.
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.
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.
He also challenges you to look at the level
of variance in all 200 runs
of the
study and do your own
analysis.
Given the new sample in
Study 4, maximum likelihood
analyses with Varimax rotation forced 5 factors which accounted for 53 %
of the sample
variance.
To address the second research question in
Study 3, an exploratory factor
analyses with a maximum likelihood method with Varimax rotation indicated 5 factors that accounted for 47 %
of the sample
variance.
We performed comparisons
of means using
analysis of variance, with planned post hoc
analyses by the Tukey honestly significantly different test; effect sizes were obtained using mean differences with associated 95 % confidence intervals (CIs) and also calculated using Cohen d for purposes
of comparability with related
studies.