Modern life bombards us with data, news, statistics and much more in an un-nerving deluge through seemingly never-ending channels of communication. We would all do well to filter for significance.
Significance is defined as the degree to which something is important and deserving of our attention. But with the constant flow of data it is often difficult to determine significance. Snippets and soundbites have become addictive and are a growing feature of how information is delivered to busy, gullible consumers. Nevertheless, if we try to sieve out the dross we will be rewarded with news that truly deserves our attention.
In truth, significance itself can be subjective and personal. An important life-changing event for teenagers (deprived of Snapchat) will be somewhat less important to an 80-year-old!
The sciences deal with significance in a slightly different, but nonetheless rewarding, way. The data, news and statistics under consideration are sampled. Naturally, a concern is that the sample material used might provide misleading results. Perhaps the sample size is too small or too concentrated; perhaps it contains a strong, yet inadvertent, bias; or maybe the sample is too widespread and captures eccentric data by chance or bad luck.
Statistical significance, which filters out distortions, is detected by mathematical logic. It calculates and eliminates the probability that the level of importance attaching to any data may have been arrived at merely by chance. A clever way for ordinary souls to check this is to determine whether or not a piece of news that we deem significant today is of equal importance to us tomorrow and the next day. If not then it was not statistically significant and should not carry a high order of importance.
If your GP told you that a study was conducted showing that energy levels could be markedly improved, without any adverse effects, by taking tablet A with juice instead of water, would you be convinced? If you could be assured that the results of the study were statistically significant and not some chance outcome that could not be repeated, then the findings deserve your attention.
In the investment world data, news and statistics abound. Consumers make financial decisions prompted by all kinds of factors but do they ever filter for significance? The objectives at the outset are clearly to secure a positive return but how is the financial decision made? Does anybody check the data for significance? In many instances investment decisions are knee-jerk reactions to whispers heard in dark places. This is wholly inappropriate – yet in some cases random chance may just prevail.
Appetite, aversion, preferences and tolerances are just some of the important risk classifications that need to be considered to ensure that investment decisions are not spontaneous and impulsive. In the long run this is the only way to approach financial decisions. Factors such as emergency funding and lifestyle upheavals do not sit comfortably with spontaneity. MMPI has traditionally been seen as a provider of expert financial advice. More aptly we just filter for significance!