The phrase "a spurious correlation" is correct and usable in written English.
It can be used when discussing a relationship between two variables that appears to be significant but is actually misleading or coincidental.
Example: "The study found a spurious correlation between ice cream sales and drowning incidents, highlighting the importance of not jumping to conclusions based on misleading data."
Alternatives: "a false correlation" or "a misleading correlation".
Of course, there is always the possibility of a spurious correlation.
Clinton's supporters deserve to know whether this apparent statistical anomaly is the result of a hack against our election system or a spurious correlation.
Our conclusions are robust because four alternative hypotheses that may generate a spurious correlation between grazing and coral recruitment were tested and rejected.
The early genealogical studies were criticized on the grounds that the downward trend in the death rate (attributable generally to scientific advancements) introduced a spurious correlation in statistics derived from records extending over long periods of time.
To illustrate, let us generate random data that show a spurious correlation between height and salary.
A spurious correlation in a third attribute, for example, can reduce the uncertainty between the other two.
The latter cases were clearly a matter of growth slowdowns leading to higher debt, not the other way around; the former a case of spurious correlation.
If immigration bias is a source of spurious correlation, then we should observe no hate crimes effect for native-born persons.
Collectively considered, the magnitude and direction of the differential effects in Table 5 plus our additional results when post-9/11 immigrants are excluded from the immigration sample suggest that immigration bias is not a cause of spurious correlation between racial self-identity and hate crimes.
Dornan said this was a "textbook case of spurious correlation", adding it was like showing rising divorce rates and falling smoking levels on the same graph and then trying to claim they were linked.
Moreover, it has to be noted that different market interdependencies which have featured correlations in the past may not show the same behaviour in the future due to a lack of causality (spurious correlation).
