I am senior industrial engineering student at Bogazici University and I am working at Intertech Information Technologies and Marketing Company as a part-time bussines analyst. In addition to my current job, I want to work as data scientist after graduation. Because of my this desire, I want to improve myself about data science during this lecture.
Stepanek’s team is interested in survival anylysis and its applications. The target variable in their analysis is two-dimensional,covering both the time of the event and whether the event or residents are introductory.The long-rank test and the proposed assumption-free method were compared by simulating pairs of random non-crossing curves that are not significantly different and calculating the first type errors. By combinatorial or exhaustive calculation of orthogonal paths in the grid of survival plot,they can get a ratio of the number of all pairs of the paths corresponding to the survival curves opposing the null. Based on the simulation,the proposed method proved to be of higher robustness(lower first type error rate) than the long-rank test. The assumption-free version of the long-rank test seems to be a valid alternative for the comparison of two time-event curves. Besides, the method could also be a topic for a new R package development.
useR! 2020: Robust alternatives for comparing time-event survival curves (L. Stepanek)
Linnart Felkl summarize key developments in Germany up until 2019`s stagnation and recession. Their period of analysis is 2000–2018.In particular, he found that:
— During 2000 to 2018 strong and stable gdp strong growth can be observed, except during 2009 to 2010.
— Growth in German household consumption expenditure was positive during all years.
— Gross capital formation was negative up until 2006 and has, except during 2009 to 2010 crisis, developed along path of rapid growth.
— Strong raises in wages and salaries can be observed up until 2018, which might have driven stable growth in consumption.
Their results suggest that positive trends in German consumption contributes to novel stabilization of previously primarily export-oriented German economy. Nevertheless, strong and steadily increasing growth rate in German salaries and wages poses risk for historically strong German exports but may contribute further to strong consumption growth.
During entire period from 2000 to 2018 Germany enjoyed strong GDP growth, except in 2009 (global crisis). Post 2009 crisis development was very positive, in fast surprisingly positive. German economy was performing beyond expectations and forecasts.
When it comes to transportation, people’s safety is and always will be our top priority. With the rise of self driving cars, we must re-examine our current safety measures and introduce new ones that will better match the future of driving.
While there were many car safety features introduced in the past decades, the airbag is often considered one of the most important piece of safety equipment. However, it is vital to study the situations when airbags are the most effective and what the drawbacks are. Despite the fact that this technology saved numerous lives, there were also accidents when it was a contributing factor to inguries and even fatalities.
This study will examine how airbags contribute to injuries and fatalities of people of different age groups. Rafal Decowski conducted a statistical analysis and answered the following hypothesis question:
H0: Age is not a contributing factor to the level of traffic accident induries when air bags are deployed. HA: Age is a contributing factor to the level of traffic accident induries when air bags are deployed.
The conditions for the each case were: 1. which there was a harmful event, people or property 2. At least one vehicle was towed.
This is an observational type of study as the data were recorded from real-life accidents by authorities that responded to the emergency. For this research, no experiments in a controlled environment were performed. Which means the causation between the age, airbags and ingury level should not be assumed.
This is a report generated as an example for Olmsted County Public Health Services (OCPHS) for an example Epidemiological Outbreak Report. The format is chosen:
— Report is interactive allowing the user to highlight and interact with text (can be recognized by speech readers).
— Report is generated fully in R/RStudio from the data that is ingested and analyzed.
— Report can be updated automatically as new data is inputted (narratives can also be coded to make conditional changes according to output results).
— This Report site stands alone - allowing updates to be visible in real-time for end-users - fully automated to generate tables/analyses from a google spreadsheet where data can be entered/updated.
Cases —> identified through routine laboratory surveillance and interviews with restaurant patrons identified through credit card receipts. Confirmed cases were defined as a person who tested positive for STEC at a clinical laboratory after eating at the restaurant.
Probable cases —> defined as a person with diarrhea (≥ 3 loose stools in a 24-hour period) that was either bloody or at least 3 days in duration after eating at the restaurant. All STEC cases reported to MDH are routinely interviewed about exposures and food consumption at home and at restaurants as part of the foodborne disease surveillance system in Minnesota. Restaurant patrons identified through credit card receipts were interviewed about food consumption and illness history.
Gastroenteritis Associated with Restaurant | Epidemiological Outbreak Report Example