Maxiumum Likelihood Estimation

In statistics, maximum likelihood estimation is considering the maximum likelihood of different statistical models given that you’re observing certain results. This will not be about that topic. Instead, this is about productivity. Imagine that you have a goal you want to reach. During your waking hours you have the choice of doing nearly anything at all. For each available action you could take, imagine the probabilities of reaching your goal as a result of those actions. From this list, choose the one with the maximum likelihood of success. We define “success” as “reaching your goal”. As an example, take the goal of learning to code. When you wake up and you’re still in bed, imagine what actions you could take and their probability of helping you learn to code. You could either

  1. Stay in bed - 5%
  2. Get out of bed - 95%

What seems more likely to help you code? Most probably, the latter, 2. This is because at least when you’re out of bed, you’ll be more alert to code later on in the day, whereas staying in bed might make you more lethargic, physically and psychologically. After getting out of bed, what are the next choices and their likelihoods of success?

  1. Take a shower - 20%
  2. Go to the gym - 40%
  3. Eat breakfast - 30%

There are many choices after waking, but if we hypothetically consider the top three, we could come up with the choices above. In this case, it seems that all three choices lead to a successful outcome, but keep in mind that we want the one that creates the maximum likelihood of success. Therefore, we could say that going to the gym is better than taking a shower and eating breakfast immediately upon waking, as we could do these after going to the gym anyway, and that going to the gym first would spur both physical and mental acuity.

After coming from the gym, and presumably taking a shower and eating breakfast, we consider the next choices.

  1. Code - 80%
  2. Procrastinate - 5%

We can start coding now. There might be other choices that help with this, such as meditation, but we should again consider that we’re seeking the next immediate maximum likelihood of success. Meditation could potentially be done later after we’re done learning to code. One could say we should’ve started coding as well right after waking instead of going to the gym, and that’s also possible, as these are just suggestions.

One place I’ve seen this advice be very useful is in regards to startup founders. Many founders want to build the next biggest and brightest thing without considering that it might take a long time and might fail due to lack of feedback. Founders may also plan too much and not actually start constructing whatever it is they want to build, opting instead to procrastinate in the details. However, what they should consider instead is, what is the next immediate action they could take that would ensure the maximum likelihood of success? It is most likely, at least in the earliest stages, that they need to talk to their potential customers and garner feedback about what their problems are and how they solve them.

Similarly, many of us also procrastinate by planning, or by thinking that by starting that we need to become the next great star. We don’t want to consider that the best available action is to start, rather than thinking about starting. Sometimes, we may actually consider starting but we simply don’t want to. This method helps us in that it forces us to only consider our next actions rather than wondering about all of the future actions that may overwhelm us. In this way, by considering all of the immediate choices we have available to us, and how well they help us reach our goals, we can be more likely in doing so and eventually become successful in what we set our mind to.

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