Assertion: correlation | /r/HasProperty | significant
Facets:
value: statistically
type: MANNER
value: at the 0.05 significance level
type: OTHER
value: as <
type: DEGREE
value: highly
type: DEGREE
value: at .05
type: TEMPORAL
value: at two asterisks
type: OTHER
value: at .01
type: TEMPORAL
value: given the parameters of the test
type: OTHER
value: at alpha
type: OTHER
value: at lower
type: DEGREE
value: at 0.05
type: TEMPORAL
value: statically
type: DEGREE
Source sentences:
text: That is, such correlations are statistically significant at α = 0.05 or lower: they are (highly) unlikely and thus refute the null hypothesis of a zero population correlation.
text: If the test concludes that the correlation coefficient is significantly different from zero, we say that the correlation coefficient is “significant.
text: The correlation was considered significant when P <0.05.
text: If this probability is lower than the conventional 5% (P<0.05) the correlation coefficient is called statistically significant.
text: Many times, you don’t consider a correlation to be significant until it goes above 0.8 (or -0.8 if it is negative).
text: A common fault in statistics is to assume that correlations are significant when they are not, that is, to assume unjustifiably that changes in variables are causally related.
text: If the test shows that the population correlation coefficient ρ is close to zero, then we say there is insufficient statistical evidence that the correlation between the two variables is significant, i.e., the correlation occurred on account of chance coincidence in the sample
text: We conclude that the correlation is statically significant .
text: A common fault in statistics is to assume that correlations are significant when they are not, that is, to assume unjustifiably that changes in variables are causally related.
text: A common fault in statistics is to assume that correlations are significant when they are not, that is, to assume unjustifiably that changes in variables are causally related.
text: In order to test for whether or not a correlation between two variables is statistically significant, we can find the following test statistic:
text: , we can conclude that the correlation between weight and height in this example is statistically significant at alpha = .05.
text: Since my correlation of .73 is actually quite a bit higher, I conclude that it is not a chance finding and that the correlation is “statistically significant” (given the parameters of the test).
text: A common fault in statistics is to assume that correlations are significant when they are not, that is, to assume unjustifiably that changes in variables are causally related.
text: A common fault in statistics is to assume that correlations are significant when they are not, that is, to assume unjustifiably that changes in variables are causally related.
text: In order to test whether the correlation is in fact significant rather than a chance occurrence we have used hypothesis testing.
text: A common fault in statistics is to assume that correlations are significant when they are not, that is, to assume unjustifiably that changes in variables are causally related.
text: Finally Flag significant correlations asks SPSS to print an asterisk next to each correlation that is significant at the 0.05 significance level and two asterisks next to each correlation that is significant at the 0.01 significance level.
text: Finally Flag significant correlations asks SPSS to print an asterisk next to each correlation that is significant at the 0.05 significance level and two asterisks next to each correlation that is significant at the 0.01 significance level.
text: A Single * shows that correlation is significant at .05 (5%) while *
text: * shows that correlation is significant at .01
text: The standard alpha value is .05, which means that our correlation is highly significant, not just a function of random sampling error, etc.
text: A common fault in statistics is to assume that correlations are significant when they are not, that is, to assume unjustifiably that changes in variables are causally related.
text: If r is not between the positive and negative critical values, then the correlation coefficient is significant.
text: If the test concludes that the correlation coefficient is significantly different from 0, we say that the correlation coefficient is “significant”.
text: If the test concludes that the correlation coefficient is significantly different from 0, we say that the correlation coefficient is “significant.
text: If [latex]\text{r}[/latex] is not between the positive and negative critical values, then the correlation coefficient is significant.
text: If the test concludes that the correlation coefficient is significantly different from zero, we say that the correlation coefficient is "significant.
text: If the test concludes that the correlation coefficient is not significantly different from zero (it is close to zero), we say that correlation coefficient is "not significant".
text: If r is not between the positive and negative critical values, then the correlation coefficient is significant.
text: If the test concludes that the correlation coefficient is significantly different from zero, we say that the correlation coefficient is "significant.
text: If the test concludes that the correlation coefficient is not significantly different from zero (it is close to zero), we say that correlation coefficient is "not significant".
text: If \(r\) is not between the positive and negative critical values, then the correlation coefficient is significant.
text: You can also see that Pearson's correlation coefficient is statistically significant as p < .0005
text: If the test concludes that the correlation coefficient is significantly different from 0, we say that the correlation coefficient is "significant".
text: If the test concludes that the correlation coefficient is not significantly different from 0 (it is close to 0), we say that correlation coefficient is "not significant".
text: If r is not between the positive and negative critical values, then the correlation coefficient is significant.
text: If the test concludes the correlation coefficient is significantly different from zero, we say the correlation coefficient is significant.