This article highlights data sets that collected information on a long-term change in nutrition and health on social and economic levels. The articles use of variations in types of data sets used to understand the deviations in the data collected helped me to understand the importance of each set. The advertised types of data collectively allowed the article to understand the information collected to discern the change in nutrition and health on an economic and social level. The information used within the article was useful and overall productive in the grasp of data sets and their uses.

Trends in data, collected by the National Corrections Reporting Program, revolving around reoffending convicted criminals has been analyzed by looking at the data sets of prison admissions and releases. The federal Bureau of Justice Statistics (BJS) collects their data submitted by state corrections and parole departments. I find it interesting how there are only some small differences in Pew’s and the BJS’s return-to-prison data in 2005. I would have expected more apparent differences based on the different measurements of data collection. For example, the BJS includes data on 70k out of 400k rearrested prisoners, strategically selecting based on their access to fingerprints that link records to prisoners. They could also remove prisoners in their data sets who have died, which is necessary because dead prisoner data could skew the whole data set. Pew could not access this sort of information, or enough information to the degree that BJS could which makes me question how BJS’s and Pew’s numbers only show small differences.

One point I found interesting in Engerman and Fogel’s “Guest Editors’ Forward” is how they reference an analysis of data for Trinidad and seem to claim those results have significance on the global scale. I find this very misleading because Trinidad is a small island likely with it’s own unique population, healthcare systems, diets, and cultural traditions which have their own specific effects on their specific population. The island is not at all a representative sample. How could the authors lay claim that the trends found in the Trinidad population could have any significance or be at all representative on the trends of the global population? I found this point invalid, and even if it’s population trends are true, I find it unconvincing because of the insignificance of the sample.

I thought that this article was interesting because it delved into the process of creating datasets to answer the following research topic: the influence of physical height to analyse the impact of long-term changes in nutrition and health on social and economic behaviour. I found it compelling because it was concerned with some ethical values on how to collect the data. The DAE program wants to collect data that also investigates intergenerationally linked families to account for the cultural factors that may influence the variables. Other values they want to consider is representation and time scale, to account for the different actors in the decision-making process of economic policies. I found that this article was very mindful of the different ways to approach the question, and consider the different views that could influence the outcome.  Only reading the introduction, I would be even more interested in reading the obstacles they faced when collecting the data and how feasible it was.

Everyone knows the term the strong will survive. However how accurate do those words  truly mean when put into the context and backed up behind data. When looking at the scenario of comparing different groups  nutrition from different backgrounds and how it affects morality rates,  fertility rates,  level of income, and productivity data is the most profound tool that enables people to comprehend how having the correct diet and nutrients inhibits a better environment for people and can be seen from a macro and micro analysis. For example, from an individual perspective people who had a well balanced diet and got a decent amount of sleep correlated to living longer and were more productive. From a macro level analysis this study and data sets has enabled to look at this from more a cultural standpoint and acknowledge how nutrition effects economic cycles and entry of females into the work place. I found this article to be very relevant to our class discussions because it connected to how data allows society to have a conversation and recognize about cultural norms how they should be changed in order to better the overall quality of people’s lives.

In exploring catapult and WordPress, I just wanted to introduce my website by writing a very short post on my prior experience with R. The winter semester of my freshman year,  a classmate and I initiated and designed an independent study in data analytics with one of our professors. For the first six weeks, we audited a high-level economics course in programming and statistical machine learning methods and used this knowledge to create a self-designed final project. We examined NBA analytics and conducted regression models using R, a programming language to draw conclusions about the changing landscape of the game. Unfortunately,  I forgot most of this R knowledge, but I am confident I will be able to pick it back up pretty quickly.

Chapter four of Isaac Asimovs “The Psychohistorians”, contains a discussion of modeling that is applicable to the creation and reception of current models. The character Seldon reveals to his new acquaintance Gaal that Gaal is being followed. This is due to both of their involvement with the usage of a type of model, called psychohistory, that predicts the collapse of their dystopian government. The most important take away is that Seldon recognizes the power of his model, the value of Gaal’s (though its error is decently large), and the implications of the data yielded by both. Modelers must be conscious of the type of data and parameters they are using, so they may be conscious of their outputs. In Seldon’s case, their conclusions clash with the government’s hope to keep the public in the dark. A parallel in our world could be the models of climate change. The scientists in our world have warned us of the repercussions for ignoring their model’s finding, but many still chose to ignore them due to conflicts of interest.

This reading so far has been the most interesting. It appears to tell a story of the encounter between a young man, Gaal and future telling mathematician, Seldon. Their interaction is confidential due to the fact that Gaal has been followed by agents prior to this meeting. I am fascinated by this article because of the science fiction and mystical atmosphere that it creates. My heart lives and flourishes in the realm of imagination. It seems that Seldom is trying to explain to Gaal that he knows of the impending doom of something that now seems sacred and magnificent. It takes a while for Gaal to fully comprehend but once he does, he is stunned. This information appears to be top secret and as a result is something that could get Seldon killed, but he does not fear and chooses to continue in his endeavors. I do not completely understand the connection to our topic of data with this reading but I think Seldon’s onlooking eye could be how we view technology and the use of data. Now it is something that is marvelous and contemporary but with time will come to its impending doom.

https://via.hypothes.is/https://www.dropbox.com/s/j6oj2rw64bwhaab/Asimov%20%5BPsychohistory%5D.pdf?dl=0

Welcome to WordPress. This is your first post. Edit or delete it, then start blogging!

Welcome to WordPress. This is your first post. Edit or delete it, then start blogging!