rgoddard

When my 5 year old was recently asked what was his favorite chip, his response was "chocolate chip". So that shortage may be just around the corner.

Any sort of bias present in the training data will be replicated in the model. If the police are biased in whom they target, that group will naturally show a higher crime rate. Which would easily be picked up in any sort of statistical model. Leading to a biased model.

The drop in crime happened nationwide during this same time in places which did not include NYC. [1] The timing of this seemed to have been more coincidental with the drop in crime.

[1] https://www.npr.org/2016/11/01/500104506/broken-windows-poli...

I have worked as a health actuary for the past 6 six years with degrees in both math and computer science. I am happy with my career choice. Prior to this I did work several years as a programmer and decided while I enjoy programming it is not something I want to do all day every day.

My current position allows me to make use of some of those skills along with learning a wide variety of other skills. Although from the sounds of other people's posts I might be lucky in my current position, where I do have variety and challenges and more than only routine work.

But from an education stand point I am glad that I went the route that I did given the additional skills rather than an actuarial science degree. The one downside is that it has made the exam process a little longer.

The cost of insurance is largely driven by the underlying cost of what you are insuring. Unless they are able to lower the cost of care significantly, the price difference between a non-profit and for-profit is marginal.

The measure by itself is not sufficient. Which is why all the additional analysis was needed.

1. Using the current district map the last set of elections show that Wisconsin had a large gap.

2. Compared to other state's the gap is an outlier.

3. By creating a large number of alternate maps within the state satisfying all the other requirements that gap was still an outlier.

4. Calculating the gap under different voting outcomes showed the result to be robust even under a 5 point swing to the democrates. (This is where the discontinuity would show up if there results were not robust.)

I am familiar with NY medicaid. They do publish a way to calculate the Medicaid default rate. Insurers do not have to pay exactly this but it provides a decent base line. Here is a basic description of how inpatient pricing works.

Each year the state publishes the set of hospital rates and intensity weights for each DRG (Diagnosis-Related Group) and severity combo (currently using weights developed in 2014). So a DRG of 460 (Renal Failure) with a severity 2 has a weight of 0.7393. Now the actual cost will depend on which hospital you go to since each hospital has a different base rate. For example each Mount Sinai hospital has a base rate of $8,743.45 while Niagara Falls memorial hospital has a base rate of $5,558.99. Each hospital also has a per discharge rate. To calculate the default rate take the hospital base rate x DRG intensity weight + per discharge rate.

https://www.health.ny.gov/facilities/hospital/reimbursement/...

https://www.health.ny.gov/facilities/hospital/reimbursement/...

Mostly due to all of the variables that go into pricing a claim. And that logic on lives in the insurer's claim processing system.

Pieces that can impact the price. Your insurer and what product you have. These will affect who is considered in-network and the fee schedule to use. Different insures will have different arrangements. Depending on the product if you have a narrow network product they may or may not be in-network. It could also depend on the location. A provider can be in-network in one location but not in another.

Also the procedure that is actually performed may be slightly different from what was planned due to unforeseen circumstances.

This is assuming the provider is aware of what the actual costs are. In many cases they don't even know the ballpark price since that is not the portion that they deal with.

Given the many different features this is not surprising. My approach was to focus on learning one set of features at a time. I used http://doc.norang.ca/org-mode.html as a guide. The order I went in was: Creating / editing / manipulating trees - Being able to easily organize everything in a hierarchy TODOs - how to customize my own list of TODO states to fit my workflow Habits - I created a habit for learning more about org-mode each day Agendas - I found this to be one of the most useful features especially being able to create a custom agenda to see exactly what I wanted - a section of scheduled todos/habits and list of TODO items organized by todo state, sorted by category Capture Mode - makes adding new todo items easy

I used org-mode to help me learn org-mode, using everything I learned prior to help bootstrap learning the next piece. At the same time I integrated the pomodoro technique into my work flow. So my habit item for learning org-mode was to spend one 25 minute period a day learning. Do this for a couple of weeks, making sure to spend some time customizing everything to suit your process and you should be all set.

One possible place to check is your local university. I know the one by me has a good clinical psych program and they run a clinic that is open to the public. They charge on a sliding scale based on your income so it may be more affordable.

A couple additional pieces to keep in mind. Insurance companies are essentially capped at how much profit they can make on average per subscriber. For large groups 85% of every dollar collected has to be spent on medical expenses, and for small group / individual 80% has to be spent on medical expenses. If they don't meet those standards, the companies need to refund the premium to make up the difference.

In the linked article most of their profit would be coming from the large group market. The individual exchange is a separate segment and where they would be suffering those loses. So the desire to not remain in an unprofitable segment is not really negated by being profitable in a completely different segment.

Realize that it is a skill that can be trained. The current environment does encourages short attention spans. Working on your attention span needs to be deliberately. First understand your current ability. What is the longest show you can watch without feeling the need to engage in a different activity? How many pages you can read in a book before becoming distracted?

Work on engaging in those activities a little bit longer then you currently can, and slowly increase the duration. Use a timer to set a limit. This would need to be done with regularity and focus.

Being risk-adverse with retirement spending is perfectly rational. Most people will have to take into minimum expense amounts. Pursuing a strategy which will have the more likely outcome of not being able to pay your minimum expenses would not make sense for many people. Comparing only the expected values without including the volatility is an incomplete comparison.

The critique is aimed at the assumption that your risk aversion is scale invariant. i.e. you behave the same when the values are in the 10s of dollars, or the 10,000s of dollars. I might be perfectly fine with taking the coin flip when the outcomes are either $10 or $15, but if the outcomes are $10,000 or $15,000 I might rather take a lower guaranteed amount of $12,000 because that will meet my expenses but the $10,000 won't.

One issue which is neglected when this topic comes up is confusing the method of teaching vs what you are trying to teach. What you are trying to teach is the value of working hard and not only relying on being smart. The mechanism that is being used to teach this is praise. But praise is an external motivation. We know that people work best when they have an intrinsic motivation. That is not to say that external rewards cannot be used. But they should be used with other forms of reinforcement. With our daughter when working with her we focus on encouraging her to keep on trying when encountering some difficulty. And also having her focus on the sense of satisfaction from having completed a difficult task. Personally I know I feel a greater sense of satisfaction after having actually worked for something compared to being able to do something based more on intelligence.

The electrons in the graphene take on a special shape where they behave as if they had no mass. This means they can travel at a high speed and gives graphene its high electrical conductivity. That coupled with the superconductivity make the prospect of a tiny high speed computer possible. The other piece of importance was the manufacturing process used which will make it easier to manufacture and study graphene hopefully increasing the rate of understanding.

I would highly recommend learning some of agenda mode. I originally started with only using the tree editing features. But one of the coolest features is the agenda mode and the fact that you can create custom views which pull in all the details you want. Here is the view I use all the time:

  (setq org-agenda-custom-commands
      '(("w" "Agenda and Next todos"
         ((agenda "" ((org-agenda-ndays 1))) ;show anything scheduled for today including habits
          (todo "NEXT|IN PROGRESS"
                ((org-agenda-overriding-header "Working On"))) ;things that I am currently working on
          (todo "TODO"
                ((org-agenda-overriding-header "Check Todo's"))) ;Todo items to check on periodically
          (todo "WAITING"
                ((org-agenda-overriding-header "Waiting On"))))))) ;things I am blocking on

I also find that it tends to be more concise which lends to denser code. The density can be a bit off putting until you become accustom to reading it. The other part that is weird is having all of the closing parenthesis on a the last line. Consider the idiomatic way:

  (defn do_stuff
    [coll]
    (filter #(> % 10) (map Math/sqrt coll)))

  (defn do_stuff
    [coll]
    (filter #(> % 10) 
            (map Math/sqrt coll)
    )
  )

I think this is related to the fact that our own internal parsers that have been trained upon c-style code falls about when trying to read list code. So the dislike is not due to the number of parenthesis, but rather our own internal discord when trying to apply our existing mental parsers.

The only way to get around this is to spend enough time using the language so that you can build a new mental parser.

Basically re-balancing a tree. In this case it required adding a new root now to maintain the optimal branching factor.

When talking about a diet you want to break it down into several dimensions. 1) Does this diet lead to weight loss? This boils down to burning more calories then consumed. As mentioned in a different comment you can lose weight eating only twinkies. 2) Sustainability of diet - can the diet be maintained over the long term, and this plays in to the psychological challenge you mentioned. 3) Long term health effects - does the diet promote overall long term health or have potential negative consequences. Something like the twinkie diet most likely does not. i.e. does a twinkie have enough vitamin c to prevent scurvy 4) Interactions with personal health conditions - how does the diet affect your own current health condition. I am sure a diabetic would not fare well on the twinkie diet

Another cause of this is that services are generally not priced on a case by case basis. Hospital inpatient claims are priced based off of DRGs (Diagnostic-related group). An insurance company is not charged on a line-by-line basis. Rather the entire claim is submitted to the insurance company, who will process the claim and assign a DRG to that claim based off of the procedure codes, diagnoses and other factors. It might also assign a severity level. Based off of the DRG and severity level and the negotiated fee schedule a price will be assigned. This price might be a per day amount or a price to cover the entire span.

So you have an added layer of abstraction between what the service is costing and what the hospital is being paid. This system was put in place to simplify the pricing procedure so that it did not have to be done on a case by case basis. But it limits most hospitals to only really caring to this higher level of detail.

One of the difficulties of improving the overall healthcare system is there are very few ways of making systematic improvements. This article talks about a single hospital. They demonstrated a method which works, but this only improves one hospital. For a real change to occur this would need to be repeated at a large number of hospitals on a hospital by hospital basis. The US healthcare system is incredibly fractured with large regional variances. The question is how to improve the system as a whole not on a piece by piece basis.

I am currently working as an Actuarial Analyst, but I have also worked several years as a programmer.

As an analyst the tools I use are excel, access, SAS Enterprise guide and Oracle SQL developer. One of the big problems I face is that we have no good way to abstract away a process and really make it reusable.

My general work flow is using SAS to pull data from multiple sources, combine and run the data through some series of logic/calculations. Then take the resulting data, copy to excel for some additional analysis or report. This might be for a monthly/quarterly report or an analysis that needs to be update with the additional runout of data.

But these steps are all tightly coupled together. If I want to rerun the same logic on a different data set, or an updated data set I will copy and paste all of the files, update the queries. I have no way to bundle them together so that I can easily reuse with different data sources, or refreshed data.

Really want I want is someway to encapsulate different sets of data transformations/calculations into to functions to reuse them in different contexts and among different people.

Clojure is an interesting model where you have the company Cognitect built around the language. You have the product arm with Datomic, the consulting arm creating client projects in clojure and finally paid clojure/datomic training. All three feed into each other while helping to improve the language ecosystem at the same time.

Data scientist - Here is a metric ton of data, find something useful from it

Scientific Programmer - Here is a set of physical laws and differential equations which govern this chemical reaction, write a simulation for it

Mathematician - This looks like a fun theorem to prove

Scientist - This looks like a fun hypothesis to test

It is like interrupting a step in a chain reaction. The sooner you can identify and acknowledge one of the steps the sooner you halt or slow the reaction. So you may not be able to stop the initial emotion or thought, but by acknowledging it you may help stop the reaction to that emotion.

   I agree. The simplicity comes from the fact that you are focusing on different aspects at different times. I find that I will start off with defining my data structure and only focusing on the data structure. What information do I need, what is the best way to organize the data. Those sorts of issues. Once I have the data structure then I focus on what I want to do with it. This may result in some functions attached to the data structure using the object oriented features and sometimes the functions live apart from the data structure. The benefit comes from mentally decoupling the data from the functions.

If I am donating to a charity which funnels money to research, how is this all that different? I think you can tap into a similar set of population and motivations for the donations. One of the upsides with this sort of approach is that you have a great opportunity to involve the donors in the overall process. The experiment can be used to provide a view into the nitty gritty of the scientific process and more specifically drug research. Of course to do this well will take a significant effort to communicate everything effectively. On the other hand, as you mentioned, you don't want to create false hope. To mitigate this you would want to work on managing expectations on the potential results and consequences of those results are. Either way you should be able to gather useful information/experience on both the scientific experiment and the social experiment.

Also related is differentiating between the things you want to happen or change vs things you want to change your self.

We are surrounded by problems and it can be easy to become bogged down trying/wanting to solve them all yourselves. Realize you are not alone, that many other people are also working to solve those problems. Try to focus on finding the problems that you can solve and that you want to solve.

This is talked about near the end of the article. Having self-control is an important component but the other portion is having a "burning goal" as Dr. Mischel puts it. This matches exactly with what you are saying.