Assumptions of correlation
[DOC File]Correlation and Regression
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One of the assumptions that the correlation statistic depends on is that the relationship between the two variables is linear. This means that there is a straight line that best describes the relationship between the variables. Not all relationships are linear. For example, arousal level …
[DOC File]Bivariate Correlation, SPSS
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Let R be the correlation matrix of X: R=D-½X’HXD-½/(n-1) where the standard deviation matrix D½=sqrt(diag(X’HX)/(n-1)). Compute R-1. For example, and along the diagonal is 1/(1- 2) which is called the Variance Inflation Factor (VIF). More generally VIFi=(1-Ri2)-1 where Ri2 is the R-square from regressing xi on the k-1 other variables in ...
[DOC File]Correlations
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The appropriate correlation coefficient depends on the scales of measurement of the two variables being correlated. There are two assumptions underlying the significance test associated with a Pearson correlation coefficient between two variables. Assumption …
[DOC File]Correlation and Regression Models
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Assumptions necessary for inference in regression: The straight line regression model is valid. The population values of y at each value of x follow a normal distribution, with the same standard deviation at each x value. The observations are independent. It is important to remember that a model merely approximates reality.
Assumptions to calculate Pearson's Correlation Coefficient
Assumptions in Correlation and Regression Models. Both correlation and regression models are based on the general linear model, , but they differ with respect to whether the X variables are considered random or fixed. In the correlation model they are considered random – that is, the values of the X variables obtained in the sample and the ...
[DOC File]UNDERSTANDING THE PEARSON CORRELATION …
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Instantaneous correlation in a hedging model may be based on forecasts of future correlation. An empirical function relating the value of a position to the associated correlation may be derived. The empirical function is then used to vary instantaneous correlation as the underlying value of the position changes. ... “Under these assumptions ...
[DOC File]Measures of Correlation
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The correlation between two dichotomous variables is know as the phi coefficient. Use SPSS to compute that statistic for the relationship between having social problems and dropping out of school. To test the null hypothesis that phi is zero in the population, we need to convert the phi to a chi-square statistic.
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