Podcast #1 : Joie, Espi, Sydne and Cameron

During the this podcast we discussed chapter's 1-3. We discussed the topics from each chapter and related them back to real life situations. Esperanza also read out some discussion questions that she came up with herself while she did her reading which allowed us to get other different opinions and commonalities that we shared while reading on our own as well. It was very easy to have a conversation with 4 people because there was more opinions involved and ideas that were shared. Having a nice lay out of the conversation also helps because there's very few pausing moments which makes the podcast a much richer material. 


Alex Wroblewski Capstone

​Abstract

Using openly available data provided by SEPTA, I developed a program in order to track buses and predict their arrival time at the next scheduled stop. This project was inspired by the lack of a solution to receive accurate data as to the actual headway (Time between arrivals) of the bus. How can SEPTA passengers receive more accurate information about their commute? How can they get a more dynamic schedule? In November 2016, an anonymous survey was put out, wherein the data gathered represented a need of tools for a more accessible commute. This inspired me to engineer a solution to improve commuting in Philadelphia Using provided discrete data points from the SEPTA TransitView API (Application Programming Interface), the average velocity of the vehicle over the tracked interval can be found and used to predict arrival time. A lack of 100% data coverage does not allow for this method to be completely accurate, an implementation of the Monte Carlo method for headways is discussed in order to potentially provide probability. The time difference between the arrival time and the actual time is calculated and a simulation from the data is run many times over in order to generate the probability for each possible arrival window. A simulation from the data is run many times over in order to generate the probability for each possible arrival window. Applications of this solution include a multi platform phone app, a prototype of which has been developed. While the final version of the program is not one hundred percent complete, the process to run such a simulation has been thoroughly researched and documented, and will be used to continue development through the coming summer.


Deliverables

Over the past year, I have learned how to develop multiplatform (iPhone, Android, and Web) compatible apps, as well as the basics of predictive data analytics. I have gained proficiency in the Python programming language, as well as its unique capacities for handling large amounts of data.

https://github.com/mediocrelogic/septa-dispatch - is where the code for my ever developing simulator, written in Python, lives. It is still non functional, because of ever evolving implementation ideas and research. The next actions for this project are to implement a system to load the SEPTA data with an SQL database, and to evolve the trip class to a point where it can track active trips (and disable those that are not active).

https://github.com/mediocrelogic/accusepta-app - This is a multiplatform app I developed at the ExCITe Center at Drexel University during an internship. The primary goal was to investigate how I could make the information gained during data analysis useful to regular commuters. Currently, it is barebones, but it taught me how to to present information, make a multi platform app, and focus on simple, accessible design. (page will be updated with screenshots)

https://goo.gl/photos/4j77SQFz89aGvPqH9  - This link shows documentation of the research and design I embarked on over the year.

`Cohen, G., and K. M. Crawford. "A Problem in Estimating Bus Stop Times." Applied Statistics 27.2 (1978): 139. JSTOR. Web. 3 Feb. 2016.

This journal by The Royal Statistical Society demonstrates a linear regression for the time a bus spends at a stop, as dependent on the amount of passengers boarding and alighting. Other models provide algorithms to determine whether a boarding/alighting event is definite, improbable, or unlikely. The amount of time a bus would spend not actually moving isn’t something usually taken into account when models of tracking based on actual vehicle location are made, however the creation of such a linear regression based on typical SEPTA data, or gathered by users, would highly increase the accuracy of the tracking by adding another layer of adaptation to only getting new data every 3-5 minutes.


Forbes, M. A., J. N. Holt, P. J. Kilby, and A. M. Watts. "BUDI: A Software System for Bus Dispatching." J Oper Res Soc Journal of the Operational Research Society 45.5 (1994): 497-508. JSTOR. Web. 3 Feb. 2016.

A software system known as BUDI is described for the dispatching of buses operated by a public transport organization in Austrailia. Organization of transit terminology is an early focus, defining routes and the difference between a route and a timetabled instance of one, for example. Definitions and rostering of the BCC depots mentioned will provide a theoretical model for database construction of similar data received from the aforecited SEPTA API. While BUDI’s focus is on sorting and dispatching, the concepts behind it’s design, especially in terms of the database it relies on, is universally applicable to any analysis of transit data.


Golshani, Forouzan. "System Regularity and Overtaking Rules in Bus Services." J Oper Res Soc Journal of the Operational Research Society 34.7 (1983): 591-97. JSTOR. Web. 3 Feb. 2016.

To passengers, the most important part of a service is its reliability. The authors of this study analyzed average waiting time and under what circumstances would it be appropriate for one bus to overtake another. A simulation was run to determine the average headways and overtaking during a typical day of bus service. Though the original simulation is unavailable and outdated (written in fortran for a mainframe), the mathematics are available in this research journal. There are many different models used to simulate service, and each will have to be evaluated as to it’s potential accuracy. A theoretical application to Accusepta would be to create a new simulation for every time new data is received, allowing for more accurate estimates of headways over time.


Jansson, Jan Owen. "A Simple Bus Line Model for Optimisation of Service Frequency and Bus Size." Journal of Transport Economics and Policy 14.1 (1980): 53-80. JSTOR. Web. 3 Feb. 2016.

This analysis of Swedish buses in the 1980’s shows a model of total trip time as dependent on the time taken to travel the distance plus the total time spent boarding and alighting. This algorithm was originally used for economical reasons, determining the most profitable optimized frequency of bus travel. However, this model is relevant as it can be used to provide a “larger picture” estimation of total travel time for a run of a SEPTA bus.


Jennings, Norman H., and Justin H. Dickins. "Computer Simulation of Peak Hour Operations in a Bus Terminal." Management Science 5.1 (1958): 106-20. JSTOR. Web. 3 Feb. 2016.

The Monte Carlo method is a statistical simulation built upon the principle of thousands of random estimations within a set of constraints. This method is most often used to replace costly real world trial and error with a computer simulation. In 1958, Port Authority employees built a simulation to build a histogram of the distribution of the bus arrival times to be used when organizing dispatch for the day. This algorithm was used in the original Accusepta design, and is applicable to, say, estimating the probability of making a connection depending on the estimated travel time from the vehicle’s last known location.  


Mcleod, F. "Estimating Bus Passenger Waiting times from Incomplete Bus Arrivals Data." J Oper Res Soc Journal of the Operational Research Society 58.11 (2006): 1518-525. JSTOR. Web. 3 Feb. 2016.

Operations Researchers in Southhampton UK have built a model to determine average waiting time based on bus headways, the time between busses at a stop using an AVL, an automatic vehicle location system akin to that used and provided by SEPTA. The main problem with using an AVL is that missing data is almost a guarantee. SEPTA only provides locations every three to five minutes, for example. A lack of total data coverage creates gaps that have to be worked with. The authors main goal is to contribute to the theory of estimating headway variance, the difference between the frequency of busses, with incomplete data. Various methods are tested on different data sets. Previous research on AVL based models is hard to find, and adapting to the gaps, where the bus could potentially make multiple stops or travel a significant distance, is hard to manage while striving for accuracy.


Pratelli, A., and F. Schoen. "A Mathematical Programming Model for the Bus Deviation Route Problem." J Oper Res Soc Journal of the Operational Research Society 52.5 (2001): 494-502. JSTOR. Web. 3 Feb. 2016.

Researchers at The University of Piza and the University of Firanze in Italy have contributed to the creation of a mathematical model of a deviated bus route. While SEPTA does not operate on a deviated bus route. Such a route supports the main route along a corridor, while collecting and distributing passengers from neighboring blocks. The increased route flexibility causes an increase in both travel time and wait time. Despite the fact that SEPTA does not possess a deviated bus route system, the modeling is applicable in terms of analyzing theoretical inconvenience to passengers as well as tracking busses that do not follow their schedules due to traffic or other factors. Thus, this discrepancy between the schedules and the effects of real life can be equivalent to a deviated stop in terms of analyzing inconvenience to passengers. Pratelli. A, has proposed a mixed integer linear programming problem that highlights “many-to-many”, where it takes into account that passengers alight and board at every stop on the route. Other elements it proposes include the concept of net inconvenience for passengers, based off of travel time, waiting time, and any increases to that, alongside delay.

Pratelli. A and F. Schoen both created analytical models of the feasibility of a transit system based on deviation, and a core notation is the usage of arcs between two points. Arcs are used as an efficient and inclusionary way in Italy to capture most every location the bus could have passed in the interim between the last location signaled to central command, deviated stop or not.


"Public Transport, Walking and Cycling Directions - Citymapper." Citymapper. Web. 04 Feb. 2016. <https://citymapper.com/philadelphia>.

Citymapper is a Web/iOS/Android app that implements transit data from cities all over the world, including Philadelphia and implements the SEPTA API, however does not provide real time tracking. Citymapper does provide a transit focused view that services such as, say, Google Maps, do not provide as clearly. This aggregation of all available transit services provides an interesting perspective on user interface. Citymapper also provides a directions and travel time interface capable of being used in one’s own applications.


"SEPTA API Documentation." SEPTA API. SEPTA DEV. Web. 03 Feb. 2016. <http://www3.septa.org/hackathon/>.

SEPTA provides documentation on their API (Application Programming Interface). SEPTA provides http links with the ability to make specific requests for data depending on route or location. Features include the TransitView API, a specific system to make requests as to the location of either a specific bus or all buses currently active in the SEPTA network. TransitView will be the crux of the ACCUSEPTA model, as it can provide active tracking of every bus on duty, sending data every 3-5 minutes. Other documentation focuses on interfacing with raw schedule data for other SEPTA services. This framework will be used to build custom route objects for every bus in Philadelphia.


"Septadev/SEPTA-Android." GitHub. SEPTA/Github. Web. 03 Feb. 2016. <https://github.com/septadev/SEPTA-Android>.

SEPTA makes all source code for both their iOS and Android apps available online on Github. This allows for a resource as to the implementation of access to the SEPTA database, alongside typical ways it is accessed. The official SEPTA app offers some features that are useful, however the transitview is lackluster and only provides a general location as was last received. Not much analysis is done, as is the goal with Accusepta. However, the base of real time tracking is there for both buses and regional rail, thus providing a theoretical base on which to build up important Accusepta features based on the official SEPTA implementation of their API.


The Gay Gene?

  • Science:

  • Science has been able to find some genetic differences between gay men and straight men.While their is not an exact "gay gene" that dominates ones disposition. However some of the differences that have been found include physical differences and sizes, 9 small genetic regions were found to have differences within the bloodstream and gay men share some similarities in a part of the X chromosome- Xq28.

However these are not definite ways to tell if someone is gay or not. Many factors from environment and family can all have ways of effecting whether someone is gay or not. Also sexuality is a fairly fluid thing, so its very difficult, if impossible to have an exact determination what makes someone gay or not. 

  • Society

There's a large societal misconception as to whether being gay is a choice or not, and the science shows that it clearly isn't. It is a genetic fact that we are born like this. However we want to be careful with this science with so many homophobic regions and households in the world we kinda don't want to have a single way to single out gay people, that could lead to some disastrous societal consequences.

  • Self
As a gay man, I have sometimes been asked if its a choice or not, and I always knew it wasn't but was curious to the scientific reasons for it.  I was pleased to see some of the science for it, I hope that scientists proceed with caution while pursuing this further so that the future can remain safe for myself and people like me. 


https://docs.google.com/a/scienceleadership.org/presentation/d/1s_vgszqJSFJ_4Cz8tz5XSA41dT2eWXTeN3DOcz8Wd_M/edit?usp=sharing

Anna Sugrue Capstone

students vote philly skyline
students vote philly skyline

Millennials have the potential to be the largest voting bloc in the United States, but are voting at a fraction of their size. Only one young person votes for every three voters ages 65 and over. This has to change. So for for my capstone, I registered SLA seniors to vote and developed several ways to get as many seniors - SLA and otherwise - to the polls as possible. I began by developing an “organization” that I named Students Vote Philly. I started a Facebook page for Students Vote Philly that I used about twice a week to send out information about primary election news and voting information. As Students Vote Philly, I did a presentation to the senior class about the primary election and gave instructions on how to register. I helped fill out online forms and I mailed physical forms. I wrote a follow-up set of instructions for voter registration that I posted on Facebook (both as my page and as myself). I also wrote an email to all of the principals of Philadelphia School District High Schools with the instruction google doc linked. Next, I layed out my strategy for actually getting seniors to the polls. As my mentor, political consultant Jefrey Pollock, told me: anyone can get a bunch of people registered, getting people to the polls is the real challenge. Based on my research, I did two things to get high schoolers to the polls. 1, Information. I sent out emails, made posts, and gave instructions about when, where, and how to vote. 2. Incentive. On voting day, I ran a photo sweepstakes. Send a photo of yourself voting to the Students Vote Philly Facebook page, and you were entered to a win a weeks worth of pizza. It worked! I announced a winner, and I gave her her prize. I finished with an “exit poll” of the SLA senior class to assess how many students registered and voted, and what they found helpful. The results spreadsheet is linked below.

I will have another registration presentation before the end of the quarter to register new voters for the primary and advise students about how to vote in college.


Here links to my capstone materials:

Below, I have a screenshot of an example information email, a screenshot of the email I sent to the Philadelphia School District principals, and the winning election day photo.
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jackie voting pic
jackie voting pic

Super Freakonomics Podcast Part 1 - Ava Olsen and Michelle Friedman

This is our first installment of our Super Freakonomics podcast series. We intended for the podcast to be a lot shorter, but we couldn't help but get more in depth into the extremely interesting topics that this book has to offer. Although this is only the introduction segment that summarizes and discusses the introduction of the book, for our future podcasts, we plan on cutting down our speaking time if this poses a problem. This prologue chapter (introduction to the book) highlighted a plethora of issues involving statistics and a necessity for a deep understanding of math and how these situations relate to it. Each subject/category that was introduced is pretty much completely unrelated, but each is tied together with statistical comparisons and economics that make the topics alluring and hard to believe. We examined many of the key stories that we think were important to take apart and really understand. Our intended audience should be interested in math and how it relates to things happening over time and what they mean for the populations that are involved.

Art in the Open Performances, 5/13/16

SLA 11th graders have been ​creating site specific dance pieces for the Art in the Open Festival. We began with an intro workshop with the Leah Stein Dance Company where students learned the process for creating this type of site specific work. Then student groups chose sites. Each day we begin class with a short meeting in the classroom to go over the tasks and goals for the day. Then students are on-site where dancers visit them to consult and see their progress. The process is scary, challenging, quirky, and so much fun!

Performances will be on Friday, 5/13/16 between 1:00-3:00. Here is a schedule with sites and times. Schedules also will be available at the front door of SLA. This is a link to the photo gallery of the project. This is a link to a short documentary on the process from 2012.
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Metabolic Syndrome

Science:
  • Name representing group of risk factors that raise a person's risk of various diseases
  • Also known as: 
  • Dysmetabolic Syndrome
  • Hypertriglyceridemic Waist
  • Insulin Resistance Syndrome
  • Syndrome X
  • Symptoms/Risk Factors
  • Large Waistline
  • High levels of Triglyceride
  • Low levels of HDL cholesterol
  • High Blood Pressure
  • High Blood Sugar
  • Mainly occurs when a person has 3 or more of the risk factors
  • People who have Metabolic Syndrome have a greater risk of having cardiovascular diseases later on in life
  • Also can lead to diabetes, stroke(s), and/or diseases related to a buildup of fat
Society:
  • Very common
  • Around 3 million cases of people with Metabolic Syndrome every year
  • Around 32% of the US population has it
  • 85% of people with Type 2 Diabetes have it
  • 25% of all Adults in Europe or Latin American countries have it
  • 40% of people ages 60 and up have it
  • People who have Metabolic Syndrome can cure it with things like, losing weight, and/or change in diet
Me:
  • I don't have any of the diseases or suffer from Metabolic Syndrome
  • However, my Father suffered from Metabolic Syndrome when he was young and now has Diabetes
Sources:

Podcast 1 // Bella, Andrew, Kristina, Kevin

All of our group members were present for this podcast. During this podcast we discussed the first four chapters of the book and the introduction section. We just basically discussed each chapter and talked about the key points. We also talked about the writing style of this book and said that maybe we should of read this book in the first week of class. We did this by having a pre discussion and writing things a white board. By doing this we got all of our thoughts out and were able to have a smoother conversation. We didn't have any points of conflict or disagreement during this discussion. The only real question that came up was the question "is there a such thing as a good sample?" We hope you enjoy.

Stats Podcast 1

E1U6 Mini Proyecto, Brendan


Person - ¡Hola! ¿Qué pasa?


Brendan - Yo vistar Malaga, Spain


Person - En serio? Qué tiempo hace en Málaga


Brendan - Tiempo es muy lluvioso


Person - Qué hiciste allí


Brendan - Yo fuimos la playa y yo cenamos en El Meson de Cervantes.

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Person - ¿Puedo ir la próxima vez


Brendan - Si, si tu tener el dinero, nosotros visitar Museo Picasso Málaga


Person - Yo amor meseo!


Brendan - Nosotros poder  jugamos golf en Costa del Sol.Image result for Costa del sol


Person - Yo no haga golf, but yo querer aprender cómo jugar.


Brendan - Golf es no el solamente cosa tu poder hacer.


Brendan - Tu puedo ir la playa, museo, turismo, bicicleta gira, y compras


De Verdad yo aun no ha ese tu puedo hacer todo lo que.


Person - Adiós, bonito hablando a tu.


Brendan - Vale


Cartagena, Colombia

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E1U6 Mini-Proyecto: Andora, Leah, Turbo, and Ashton

Leah: ¡Hola!

Andora: ¡Hola!

Turbo: ¡Hola!

Leah: ¿De dónde esta?

Turbo: Esta en Madrid.

Andora: Esta en Trinidad.

Leah: ¿En serio? ¿Trinidad, Cuba? ¿Madrid? Esta en mi casa.

Andora: ¡Ay, díos mío! !Tú casa es muy aburrido!

Leah: Tú muy suerte Andora.

Turbo: ¿Que es especial en Trinidad?

Andora: ¿Què? Muy es especial en Trinidad.

Andora: Trinidad hay nueve centro comercials.

Leah: ¿¡Hay nueve?! *desmayos*

Andora: Sí.

Turbo: Ok. Madrid es todavía mayor

Andora: ¡Mentira! Trinidad hay cinco playas.

Turbo: ¿Así? Trinidad no hay supermercados.

Leah: ¿En serio? No hay supermercados.

Andora: Espera. Hay muy restaurantes almorzar y cenar.

Turbo: Trinidad no hay hoteles.

Andora: ¡Mentira! Hay dieciocho hoteles en Trinidad.

Leah: ¡No me digas!

Andora: Sí. Ven aquí por favor en pasear la calle.

Leah: ¡Qué chévere!

Turbo: ¿Cómo?

Leah: Me gusta pasear la calle y visitar a el teatro.

Andora: ¡Mira!

Turbo: Jajaja La casa menor.

Andora: Los edificios muy antiguo y intrigante.

Leah: Sí. Muy intrigante.

Ashton: ¡Hola! Y Cálmate Turbo. Trinidad es hermoso.

Turbo: ¿Por qué?

Ashton: Me gusta sacar fotos y probar la comida.

Leah: Espera. ¿Dónde estás?

Ashton: Estoy en Trinidad.

Andora: ¿En serio?

Leah: ¿En serio?

Turbo: ¿En serio?

Ashton: Sí. Jajajaja

Ashton: ¿Qué vas a hacer mañana?

Leah:  Voy a Trinidad.

Andora: Debes visitar nosotros.

Ashton: Sí.

Turbo: Ugf

"How To Lie With Statistics" PODCAST #1

​Here is our first podcast discussing our observations and opinions on the first three chapters of Darrell Huff's How To Lie With Statistics. 

Speakers: Eamon Kelly and William Derry

The topics that we tackled in this first podcast include...
- Examples of lies with Statistics
- Reasons why people choose to deceive / history
- Structure of the text

No big arguments were started in the discussion, but we did ask for each other's opinions on the topics we were talking about. Two main questions came up toward the end of the podcast:

1) Are we or will we be guilty of using the same tactics used in the book for our personal careers?

2) How will Huff continue to keep us engaged for the rest of the book?


ENJOY :)
StatsPodcast1

Science Of Laughter

For my 5 minutes of science, I decided to focus on laughter. Laughter is commonly associated with the frontal lobe and other unspecified regions of the brain that control emotional, cognitive, and motor responses. Laughter unlike talking or breathing, causes the body to lose air instead of bringing it in at timed intervals, hence the praise, "Dying of Laughter." There are not a lot of studies done on laughter. It is known to be something that is common in most mammals such as primates, rats, and famously hyenas, and is thought of as primitive and mating call-like. In the social aspect of laughter, you are more likely to laugh in a group of friends than you are by yourself. This doesn't mean it is all good laughter. There are two kinds of laughter known as Posed and Real laughter. Posed laughter is known more in social situations as a sign of understanding and engagement, while real laughter, also known as "helpless" laughter, is commonly associated with the response from tickling. This brings us to the stress relief part of laughter. Tickling is one of the most stressful physical acts that can be exerted on the body by another person; laughter is the only way to cause the body to not go into complete panic mode. Robert Levenson did a study at Berkeley College that involved couples being asked stressful questions. It was found that couples who laughed more during the experiment controlled their stress levels more than the couples that did not. 
The reason I chose this topic is because I am someone who laughs way more than I should and I wanted to know why. I found that I do to tend to laugh more when I'm trying to rid myself of a stressful situation. Also as a kid I would have long fits of erratic laughter where I couldn't stop, and didn't know what I was particularly laughing at. Maybe I was a very stressed 7 year old or maybe my frontal lobe was very active, either way it would being a satisfying solution. 

SLA Poetry Team Wins East Division!

By Otter Jung-Allen

​Congratulations to SLA's Slam League poetry team for winning the East Division this past Friday! After five weeks of competition, SLA has beaten teams such as Strawberry Mansion, Mastery Lenfest, and Cristo Rey. SLA has earned the right to skip semifinals and the first round of Championships! We are on our way to another citywide championship! Props to all of the poets who touched stage this season and have worked hard to create a safe space for all Philadelphia's youth writers.

Make sure to save the date for March 27, our final showcase before Slam League Championships. More details to come! 

And remember: you can't spell SLAY without S-L-A!

E1 U6 Spanish assignment

(Text conversation)​

Sean : Hola charles! Que tal!

Charles : Hola Sean! Asi asi y tu?

Sean : Mas y menos. Donde esta tú hoy?

Charles : Soy Ecuador!

Charles : me puedo esta fin de semana

Sean : Bien! A donde vas en Ecuador?

Charles: Soy Manta, Manta Ecuador

Sean: es basante?

Charles : Mucho

Sean: es Calor?

Charles: Mucho

Sean : Poder los fotos?

Charles : Si! Un  momento.

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Sean: MUCHO BASANTE!

Charles: Sé justo!

Sean: visito los museos o attraciones?

Charles : Si, quieres ver?

Sean: Si!

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Sean: el edificio es muy alto!

Charles : Si! Ecuador es muy divertido!

Sean : mas?

Charles: Si, uno mas!

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Sean: Que es eso?

Charles: Es el resturante!

Sean: Como es la comida?

Charles: muy delisioso!

Sean: mmmm Tengo hambre!!!

Charles: jajaja

Sean: mi telefono es uno percento!

Charles: Tu tengo el Cargador?

Sean: Si, estoy casi alli!

Charles: Sean?

Charles: Sean?

Charles: mucho comida for me jajaja!

Madrid

My group and I decided to choose Madrid, Spain!

Meymey Seng (its_me_mey) posted pictures of where she visited while in Madrid. She posted pictures of a beach and a museum where her two friends Tyreek Speedwell (reek.__) and Salsabeel Elbakhadaoui (_bell_14) has a conversation. 
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