Introduction American Statistical Association published Leveraging Statistics with Computer Science to Transform Science and Society in 2014. The primary author, Cynthia Rudin, explains how statistical analysis benefits different scientific fields using computers to collect Big Data, gathering large amounts of data pertaining to the specific topic, and do computations on the gathered data. This analysis helps the research of all disciplines such as biological sciences, healthcare, and civic infrastructure. Rudin focuses not only on statistical analysis but also by enticing the next generation to consider being a statistician, a very important job that helps all fields grow. Rudin saw that statistical analysis has positively impacted many fields and sees the possibility for it to continue changing the world.
Summary
Rudin begins by mentioning many cases where Big Data analysis had a large impact on a field. Genetics used to be very limited but is now centered around data. Genes used to be expressed as dots but now they are known to have massive amounts of information within them. Healthcare is very similar and
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Rudin also helped other fields ponder the possible changes Big Data could make for them. Rudin 's field has already helped explore DNA much more in biological sciences and help organize and make decisions with doctors giving healthcare. Statistical analysis is the backbone for business analytics, search engines, and recommendation systems. Search engines use it to determine what information is most likely to please the user based on what he searched for and what information has been used the most often. All of these examples prove that statistical analysis can be used in all fields which is the exact message Rudin is trying to get across to encourage more future students to pursue statistical
The final chapter of this book encourages people to be critical when taking in statistics. Someone taking a critical approach to statistics tries assessing statistics by asking questions and researching the origins of a statistic when that information is not provided. The book ends by encouraging readers to know the limitations of statistics and understand how statistics are
According to Lisa Arthur, big data is as powerful as a tsunami, but it’s a deluge that can be controlled. In a positive way it provides business insights and value. Big data is data that exceeds the processing capacity of conventional database systems. It is a collection of data from traditional and digital sources inside and outside a company that represents a source of ongoing discovery and analysis. The data is too big, moves to fast, or doesn’t fit the structures of the database architecture. Daily, we create 2.5 quintillion bytes of data. In the last couple years we have created 90% of data we have in the world. This data comes from many places like climate information, social media sites, pictures or videos, purchase transaction records, cell phone GPS signals, and many more places. From the beginning of recorded time through 2003 users created 5 billion gigabytes of data. 2011, the same amount was created every couple days. 2013, we created that same amount every ten minutes. Some users prefer to constrain big data into digital inputs like web behavior and social network interactions. The data doesn’t exclude traditional data that is from product transaction information, financial records and interaction channels.
This paper is a critique of an article written by McKinney and Jones (1993) entitled: “Effects of a Children’s Book and a Traditional Textbook on Fifth-grade Students’ Achievement and Attitudes toward Social Studies”. In their research the authors examined the effects of a children’s book and a traditional social studies textbook on knowledge acquisition and attitudes toward social studies and the textbook in a sample of 57 fifth-graders. It is the intention of the present paper to develop analytical discussion and the holistic interpretation of the McKinney and Jones’s quantitative study (1993).
Quantitative methods in the social sciences are an effective tool for understanding patterns and variation in social data. They are the systematic, numeric collection and objective analysis of data that can be generalized to a larger population and seek to find cause in variance (Matthews and Ross 2010, p.141; Henn et al. 2009, p.134). These methods are often debated, but quantitative measurement is important to the social sciences because of the numeric evidence that can be used to drive more in depth qualitative research and to focus regional policy, to name a few (Johnston et al. 2014). Basic quantitative methods, such as descriptive and inferential statistics, are used regularly to identify and explain large social trends that can then
Klosterman, Chuck. "Can Data Be Evil?" New York Times Magazine 5 Jan. 2014: 14. Academic OneFile. Web. 7 May 2014.
This paper addresses a currently relevant topic of detection of associations of copy number polymorphism with traits and will be of interest to readers of Genetics Research.
If auditors can look at a complete population, they may not have a great defense if they missed a “smoking gun” since they looked at all the data (Alles and Glen). However, this data may not be valid which raises the importance of the auditor understanding where the data came from and how reliable it is. Not only this, it will be interesting to see how standards consider big data evidence. While it most likely will not be as reliable as confirmations, it would be a challenge to figure out how much the auditors could rely on it. Furthermore, higher education would most likely play a role in helping their graduates understand data and how to use technology to be not only more efficient but also ensure they are able to use sound professional judgement while using big data.
You may ask what big data analytics is. Well according to SAS, the leading company in business analytics software and services describes big data analytics as “the process of examining big data to uncover hidden patterns, unknown correlations and other useful information that can be used to make better decisions.” As the goal of many companies which is to seek insights into the massive amount of structured, unstructured, and binary data at their disposal to improve business decisions and outcomes, it is evident why big data analytics is a big deal. “Big data differs from traditional data gathering due to that it captures, manages, and processes the data with low-latency. It also one or more of the listed characteristics: high volume, high velocity, or high variety. Big data comes from sensors, devices, video/audio, networks, log files, web, and social media which much of it is generated in real time and in a very large scale.”(IBM) In other words, companies moving towards big data analytics are able to see faster results but it continues to reach exceptional levels moving faster than the average person can maintain.
The quantitative research article that I chose to review was a study completed by Dougherty and Thompson (2009), found in Research in Nursing & Health. Very few researchers have focused their study on the impact of cardiac arrest and ICD implantation on a patient’s intimate partner. What little is known about caregiving responsibilities and caregiver burden after a cardiac illness or event has previously been focused on the spousal experiences following an acute myocardial infarction or coronary artery bypass graft surgery (Dougherty & Thompson, 2009). The researchers in this article chose to study the physical and mental health effects of the intimate partners of persons after sudden cardiac arrest and receipt of an implantable cardioverter defibrillator (ICD). Intimate partners were defined as being the spouse, lover, or significant other living in the same household as the patient during the study enrollment. Complete data collection was obtained from 100 intimate partners that participated in the study. Subjects were recruited from 10 Pacific Northwest hospitals after patient’s received an ICD after cardiac arrest. Data were collected by the researchers between 1999 and 2002.
Supporting inspiration with data - making extensive, aggressive use of data and testing to support ideas according to a Harvard case study people aren't allowed to say 'I think' but instead must say 'The data suggest...'
...e point of critical mass. Information is everywhere. A big challenge to business and society is their ability to process these large amounts of information into something relevant to their business and government models. While there are clearly advantages to the use of big data, there are also potential disadvantages that can have huge negative effects on society as a whole, particularly in the way people govern and police each other. It is important that people across all spectrums of society understand and realize the ways in which big data is affecting the world around them. Thus, the potential of big data, like all great forces that come to realization through technology, lies not in the nature of what it can or cannot do, nor in its inherent advantages and disadvantages, but in society’s ability to correctly resource and utilize the power that is big data.
...ch Reips. ““Big Data”: Big Gaps of Knowledge in the Field of Internet Science.” International Journal of Internet Science 7.1 (2012): n. pag. Web. 16 Mar. 2014.
Statistical mechanics is a very broad subject with many other concepts under its umbrella. This topic has entire classes dedicated to it, with hundreds of theories and equations, so instead of unrealistically trying to master a whole course I instead sought to get a general understanding of the topic to the point that I could apply what I learned to future courses featuring statistical mechanics. However, to understand the topic I obviously had to go in depth into the main points of the field, and examine the contributions that pushed the field forward. After my initial research I found that the topic of statistical mechanics is like the label on a tool box with dozens of other topics, or tools, inside of it. At the same time, statistical mechanics is just one of the many branches under the broad tree of mechanics that defines the field of physics. So my goal is to illustrate the relationship between statistical mechanics and its tools, and how they work and what they all try to answer.
Whether or not people notice the importance of statistics, people is using them in their everyday life. Statistics have been more and more important for different cohorts of people from a farmer to an academician and a politician. For example, Cambodian famers produce an average of three tons or rice per hectare, about eighty per cent of Cambodian population is a farmer, at least two million people support party A, and so on. According to the University of Melbourne, statistics are about to make conclusive estimates about the present or to predict the future (The University of Melbourne, 2009). Because of their significance, statistics are used for different purposes. Statistics are not always trustable, yet they depend on their reliable factors such as sample, data collection methods and sources of data. This essay will discuss how people can use statistics to present facts or to delude others. Then, it will discuss some of the criteria for a reliable statistic interpretation.
The Importance and Appropriateness of Utilizing Different Methodologies for Research. Introduction The process of research entails the logical as well as systematic search for useful data and information with regard to a specific topic (Jha, 2008). It is also comprised of the investigation of the best, most cost effective and appropriate solutions to both social and scientific issues, following an objective and logical analysis. Jha, (2008) defines research as the search for knowledge and the discovery of the truth. During this process, the data can be gathered from a wide pool of sources among them interviews, books, nature among others.The data can then be analyzed with the appropriate data analysis tools, so as to report the findings