Examples of using Two or more variables in English and their translations into Portuguese
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Colloquial
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Official
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Medicine
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Financial
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Ecclesiastic
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Ecclesiastic
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Computer
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Official/political
When there are two or more variables, then each one has a name.
It is important to note that the correlation is a measure of relation between two or more variables.
Four participants had two or more variables categorized as outliers.
Statisticians frequently use correlation to measure the dependence of two or more variables.
To assess the existence of correlation between two or more variables, Pearson correlation test was used.
Confusing Bias: is when one does not distinguish the effect between two or more variables.
Thus the information concerning two or more variables was cross-plotted in contingency tables in order to evaluate the degree of coincidence or association.
The most common measures to assess the collinearity of two or more variables are as follows.
For polynomials in two or more variables, the degree of a term is the sum of the exponents of the variables in the term; the degree(sometimes called the total degree) of the polynomial is again the maximum of the degrees of all terms in the polynomial.
A testable prediction which designates the relationship between two or more variables.
The most common measures to assess the collinearity of two or more variables are as follows: value of tolerance and its inverse, variance inflation factor VIF=1/tolerance.
It is important to note that correlation is a measure between two or more variables, and the coefficient may range from -1.00 to +1.00, -1.00 being a perfect negative correlation and +1.00 a perfect positive correlation.
Correlation: Astatistical measure that indicates the extent to which two or more variables fluctuate together.
Applying it to two or more variables requires adding them to the equation, Y f x f( Y f) x{\displaystyle{\textsf{Y}}\ f\ x=f\({\textsf{Y}}\ f)\ x} This version of the equation must be shown consistent with the previous by the definition for equality of functions,(∀ x f x g x)≡ f g{\displaystyle(\forall xf\ x=g\ x)\equiv f=g} This definition allows the two equations for Y to be regarded as equivalent, provided that the domain of x is well defined.
Relationship charts are used to show a connection or correlation between two or more variables.
By using this system, it was possible to assign a score to 30 patients 61%,whereas it was impossible to assign a score to 14 patients 29% because of missing information regarding two or more variables. In addition, the system was not applicable in 5 patients 10% because those were cases of extrapulmonary tuberculosis.
The simple logistics regression test was used to compare the proportions, when we assessed whether or not there were associations between two or more variables.
The research tries to understand the patterns of relationships between two or more variables within two communities.
It was, still, verified the correlation of the acquired data; in which the presence or absence of relation between two variables is identified and, in case it exists, it is also quantified by the Pearson's correlation coefficient;which measures the degree of dependence of two or more variables.
The hypothesis should express in a clear, precise andconcise fashion either a relationship with or difference between two or more variables, including the variables of the study and its effect.
Regression analysis is an advanced method of data visualization andanalysis that allows you to look at the relationship between two or more variables.
Multiple correspondence analysis is a descriptive technique that allows the interpretation of associations between two or more variables for a graphical representation in two axes.
The Hosmer and Lemeshow measure of overall adjustment indicates no statistically significant difference between the observed andpredicted ratings for all models with two or more variables.
Individually means only one variable was shown in the text;associated means two or more variables were reported.
Multicollinearity was considered high when it waspossible to observe simultaneously if a condition index was greater than 30, if a component contributed 90.0% or more to the variance of two or more variables, and if there was a tolerance lower than 0.1 variance inflation factor- VIF, lower than 10.
The topic of functions appears in ensino médio(secondary/high school) not only as a topic of mathematics, but also in the subjects of physics, chemistry andgeography, from the analysis of the phenomena that involves two or more variables and also through the analysis of charts and tables.
Samuelson(pp. 5, 21-24) finds three sources of meaningful theorems sufficient to illuminate his purposes: maximizing behavior of economic units(as to utility for a consumer and profit for a firm) economic systems(including markets and economies)in stable equilibrium qualitative properties between two or more variables, such as an alleged technological relationor psychological law indexed by the sign of the relevant functional relationship.
Regression techniques can be used to determine if a specific case within a sample population is an outlier via the combination of two or more variable scores.