If you have studied statistics then you must be aware of the statement, “correlation does not imply causation”. This statement essentially means that we cannot legitimately deduce a cause-and-effect relationship between two variables solely on the basis of an observed association or correlation between them. If you need examples to support this statement then you should visit “Spurious Correlations” website at https://www.tylervigen.com/spurious-correlations.
Created by Tyler Vigen, this website documents examples of what are best described as spurious relationships. These are the relationships in which two events have no causal link, but still appear to due to either a coincidence or a third, confounding variable. The site shows the charts on which two variabes are plotted against the time line along with Pearson correlation (r) value. The site also allows us to discover new correlations. We tried the same and found the following correlations.
“Apple stock price on January 1 correlates” with “Worldwide commercial space launches” with r=0.945948
“Apple iPhone sales” correlates with “Per capita consumption of american cheese (US)” with r=0.999421
“UK: Military defense spending” correlates with “Number of people killed by hornets, wasps and bees in US” with r=0.999436
Needless to say, there are apparently no cause-and-effect relationship between these variables!