In this series we have looked at the application of statistics in a few areas with the central theme that statistics deals with the representation of large volumes of historical data points in order to make predictions about the future and decisions about what path or road to take. We know where to go or are trying to figure it out. As individuals, the historical data gives us insight into probable outcomes if we choose product A or product B, invest in company A or company B, or change the car oil this week or next month. For the most part, however, we do not understand probability or even how to use it in calculations. How do you really assess the expected value of an electric fan when it is 95 degrees Fahrenheit outside? If you can afford it, you buy it.
In contrast, if you are in the sciences, medicine, banking, insurance, business or governance, statistics are critical to identifying future probabilities for both individuals and groups in order to make good decisions. In the first article of this series we looked at the cross section of the Uranium atom, a statistical value of a physical property that permits probabilistic calculation in the design of a nuclear reactor. Some other areas of science using statistics include astrostatistics; chemostatistics, environmental statistics, geostatistics, population ecology; and statistical mechanics, physics, thermodynamics and engineering. All these areas involve very large numbers of items where we are trying to understand what is going on so we can predict what will go on in the future. For example, an automobile consumes gasoline (or other fuel) with a certain efficiency to increase or decrease the kinetic energy with a variable accelerator while maintaining or changing direction and on and on. Statistics and probability is involved. Do you need to know the details or is it sufficient to intuitively know how much pressure to apply to the gas or brake pedal?
In the area of medicine, we can find biostatistics (including medical statistics), psychometrics, quantitative psychology, and epidemiology. These areas sound like they deal with health care, welfare and treatment of members of humanity. While one can clearly imagine and approve the appropriate level of testing before a new drug is authorized for prescription, mistakes are made – after all, it’s based on statistics. In biostatistics, how do you determine if DNA modification is safe? – not just for humans and animals, but plants also? Have the fruits and vegetables you consume been genetically modified by man or evolution? It’s in the statistics. How do you make your choice?
In a previous column we looked at life insurance and its absolute reliance on the statistics of actuarial science. The insurers are betting on you living, you driving safely, your whatever continuing to operate, your health remaining good. But what about banks and lenders? You apply for a credit card. Approval is correlated to your credit score, a statistical number the great majority of us do not understand. We are all evaluated statistically, but we are mainly concerned about our personal number.
Perhaps you are the lender as a stock or bond investor. You rely on statistics when making your choices, either calculated by you or your advisor. It deals with econometrics and statistical finance. Assume you buy or rent software to help you make stock choices. Do you understand the statistical calculations, analogs and algorithms involved? Or do you just trust the vendor? Or do you just say no, preferring to limiting your investments to just $2.00 a week in Powerball?
Moving on to business, what you as a customer experience is highly correlated to statistical data from business analytics, operations research, quality control and reliability engineering. While one can easily understand how statistics might correlate to the ads you see on Facebook, think about the enormity of statistical data being collected, shared, and exploited about you. But if it is not collected, will you ever find that perfect product that you “absolutely need?” And do you want a petroleum company engaged in geostatistics in order to find more oil and keep prices down? Or perhaps it is a need for environmental statistics related to energy consumption and efficiency.
Finally, there is the area of governance. But statistically speaking, it needs too many words for this part. So….
Till next time….