Fili Tekle
IS 330 Final Paper
Book review
Today, number crunching affects our lives in ways we may never have imagined. Ian Ayres book, Super Crunchers, shows how today 's best and brightest organizations are analyzing massive databases at lightning speed to provide greater insights into human behavior. They are the “Super Crunchers”. From Internet sites like Google and Amazon that knows you better than you do yourself, to a physician 's diagnosis and your child 's education, to boardrooms and government agencies, this new breed of decision makers are calling the shots. And they are delivering staggeringly accurate results. Want to know whether the price of an airline ticket will go up or down before you buy? How can a formula out predict wine experts in determining the best vintages? Super crunchers have the answers. Ayres shows us the benefits and risks, and how super crunching can be used to help, not
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It will also be important for us to learn how we can restate other people’s super crunching results in terms which make intuitive sense within our organization. To be competent in number crunching, we need to feel comfortable about using two quantitative tools: 2SD Rule and Bayes Theorem.
The 2SD Rule, to use this rule, you start by estimating what the mean or average value is and what the standard deviation is. The 2SD Rule then gives you a way to translate those statistics into numbers people will relate to.
Bayes Theorem, allows you to combine two or more probabilities into a single number. To come up with a combined probability, multiply the initial probability by a single number which represents the “likelihood ratio”. That ratio will either inflate or deflate the original probability estimate. The Bayes Theorem allows you to update your predictions over time as new and ideally better information comes to
After covering 262 pages of Raising Adults: A Humane Guide for Parenting in the New World, the reader would read four chapters, with plenty of subtopics, that enlightens him or her concerning teenagers and how to approach them. The author, Jim Hancock, fulfills his purpose within this book: to cultivate “people determined to be more intentional, more skillful, more realistic, more effective” concerning their relationships with teenagers. He successfully fulfilled his purpose by structurally discussing the current cultural composition of teenagers, and previous generations; strong relational skills that may aid an adult into becoming an effective parent; and practical strategies to raise adults. Although this book is extremely beneficial for any parent, it does have a con for me: it is too verbose. Namely, it could state what it attempts to convey in fewer words. After
...will fall within the first standard deviation, 95% within the first two standard deviations, and 99.7% will fall within the first three standard deviations of the mean. The Empirical Rule is used in statistics for showing final outcomes. After a standard deviation is found, and before exact data can be collected, this rule can be used as an estimate to the outcome of the new data. This probability can be used for gathering data that may be time consuming, or even impossible to found. When the mean equals the median and the values cluster around the mean and median, producing a bell-shaped distribution, then we can use the empirical rule to examine the variability. In this bell-shaped data set, we can calculate the mean and the standard deviation. The mean means the average value of the set of data. The standard deviation means the average scatter around the mean.
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.
Society seems to be divided between the idea if science is more harmful than helpful. We live in a world where humans depend on science and technology to improve important aspects of society, such as medical machinery, which supports the fact that science is more of a friend than a foe. Science is advancing every day. The United States has come a long way with its ongoing developments, giving individuals a chance to improve society as a whole. Not only does the United States benefit from such growth, but every modernized country does so as well. Through science and technology, individuals learn from past endeavors and apply it to present and future projects, paving the way for new discoveries and efficient enhancements
First we are going to talk about probability theory, which has to do with mathematics and analysis of random phenomena. You are probably used to putting the number of outcomes over the total amount of the object or total amount what you have. An example is, if you have a normal dice and you want the probability of rolling an odd number, you would take the total amount of odd numbers (3) and put that over the total (6) amount of numbers on the dice like so 3/6 which you can also reduce it to ½ because 3 is half of 6. This theory has been around since the sixteenth century and started off as the outcome you would get in a game, which was created by Pierre de Fermat, Blaise Pascal and Gerolamo Cardano. Later on in the seventeenth century Christiaan Huygens published a book on the subject.
I am investigating the impact of math in the various parts of baseball. I have collected data from the various aspects of baseball such as hitting statistics and pitching statistics that are from the MLB. With this collection of data that I have, I used a number of mathematical processes to analyze this data and get to the final statistic. Such as the pitcher's statistics of how many runs they allowed in a certain amount of innings and applying the mathematical formulas to figure out the end statistic which is their ERA and that tells us overall how good that pitcher is performing. Some of this data is shown in graphs throughout the paper and another big formula used in baseball is the projectile motion formula used to calculate how far home runs travel. In the end these calculations will prove how math is so important to baseball and how these formulas contribute to that by figuring out the end statistics of various parts of important baseball data such as hitting and
Bennett, J., Briggs, W., & Triola, M. (2014). Statistical reasoning: For everyday life (14th ed.). Boston: Pearson Education, Inc.
In Lee Ann Fisher Baron’s “Junk Science,” she claims that the “food industry with the help of federal regulators” sometimes use “[a science that] bypasses [the] system of peer review. Presented directly to the public by…‘experts’ or ‘activists,’ often with little or no supporting evidence, this ‘junk science’ undermines the ability…[for] everyday consumers to make rational decisions” (921). Yet Americans still have a lot of faith in the U.S. Food and Drug Administration (FDA). According to a 2013 Pew Research study, 65% of Americans are “very favorable” or “mostly favorable” of the FDA. When it comes to what people put in their bodies, the FDA has a moral obligation to be truthful and transparent. The bottom line of the FDA’s myriad of responsibilities is to help protect the health of Americans. Deciding what to eat is a critical part of living healthily, and consumers must be able to trust that this massive government agency is informing them properly of the contents of food. While the FDA does an excellent job in many areas, it has flaws in other areas. One of its flaws is allowing the food industry to print food labels that are deceptive, unclear, or simply not true (known as misbranding). This is quite the hot topic because a Google search for “Should I trust food labels” returns well over 20 million results, many of which are blog posts from online writers begging their readers not to trust food labels. HowStuffWorks, a division of Discovery Communications, published an online article whose author claims that “[the food industry] will put what they want on labels. They know the game….” While the food industry is partially at blame for misbranding, the FDA is allowing it to happen. If a mother tells her children that it is oka...
Big Data is being widely utilized by large corporations and the government for many practical uses, tracking crime, finding terrorists, redefining shopping, and changing how we go about everyday life. Price says that big data is leading to large advances in medicine, social sciences, astrophysics, business, and crime fighting. According to IBM, 90% of the worlds Big Data...
how much there is, and numbers tell you how many there are. This is cause for
A very difficult mathematical quiz has been put in place by scientists, said Cowan, to investigate the true limit on people’s working memories. This study has been built upon existing research, but includes a mathematical equation. This team of researchers accepted that humans have a certain number of empty spaces available for their working memories. This study suggests that once the working memory is filled, then the subject will start guessing. This equation was able to predict the outcomes with remarkable accuracy.
Prior to the start of the Information Age in the late 20th century, businesses had to collect data from non-automated sources. Businesses then lacked the computing resources necessary to properly analyze the data, and as a result, companies often made business d...
Last year, my all-out efforts to explore ‘data analytics’ were abruptly interrupted as a dream, predominantly, due to a life threatening surgery. On my way to a healthy recovery,