Tenzing Sonam’s Career post

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Computers have changed our lives for the better in many ways but, we as human beings, haven not come close to exploring their full potential. I would like to contribute to this exploration. The field is very diverse and there are countless avenues to explore. According to college board data, students who the AP Computer Science exam earn higher AP Statistics scores relative to peers who previous performed at the similar level in math. Statistics is an essential instrument for Computer Science. Although, I am not certain on my career is or will be. But, I do know the importance of Statistics in Computer Science. A lot of artificial intelligence, machine learning, and data science rely on statistics for a foundation. Screen Shot 2015-10-15 at 10.12.51 PM

Without statistics, the creation of Apple’s Siri would not be possible because voice command mainly relies on the data that is provided. Therefore, in the future, I hope younger generations take statistics class because it connect with other subjects as well.

 

Statistics has become a greatly helpful scientific field for measuring and analyzing a lot of human measurements and biological processes. The notion of normal distribution and normal histogram with so known bell shape are known from 1840 that are highly used in different subfields of scientific world. Since my major is biomedical informatics, statistics is very helpful for me in studying of statistical genetics for analyzing DNA and protein sequence. Moreover, being admitted into emerging scholar program and doing research related to protein folding analysis and prediction, statistics is the main apparatus through with protein structure prediction is possible. For example Boltzmann principle and Kull-back-Leibler divergence are the basic milestones for estimating discrete probabilities and assembly of data sets for estimating these probabilities. Since it is known from Adolphe Quetelet (1940) hypothesis that most data sets related to normal distribution, it is taken the middle point of estimated probabilities as the most optimal way to describe information related to protein structure prediction as well as other DNA analysis.

Juliano’s Career Post.

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well, My name’s Juliano. At this point in my life, I can only see myself being one of two things; a broke musician or someone within the field of the gaming industry. Currently, i’m in the field of computer science in hopes to one day become a game developer, and program my own games(Or games in general). Statistics plays a major role in computer science and in gaming in specific.  The development team needs to manage what goes on in the environment and how the player interacts with it all. For example, there’s chances of obtaining loot from a boss, or the drop rate of a important item. (This could be similar to rolling a dice multiple times and only getting said item on a certain number.) It could also determine whether or not an effect is triggered; like something that explodes or unlocks if a sequence is met. Virtual gaming is becoming a thing and there are only more possibilities to consider.  In all fields, with each new possibility another problem could arise that needs to be solved. You can only continue to find solutions to those problems and continue the cycle of development.

~Math related photo~

Math related photo

Math related photo

My occupation at this moment is a Assistant Teacher. With that job, statistics and probability plays a major role throughout my day. While teaching math it is my job to teach the children intermediate strategies for solving probability questions. Some kids get it right away and some don’t. And with probability statistics comes along with it. With the results from the probability question the kids can then take the results and create an analysis of data to better understand the format.

 

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Hello,

My name is Anthony Serrano and my major is Biomedical Informatics!

As almost any other profession that you can think up of, Biomedical Informatics takes advantage of the mathematics field. Indeed, statistics can be a great tool to make sense of data and information. So what is data and information to a medical Informatician? Data is raw information, whereas information processed data.  Medical Informaticians usually derive their data and information from a health care system. By using statistics in certain ways, we can derive knowledge from information. And so we have the following: 1) Data is turned to information; 2) Information is then turned to knowledge.

By acquiring knowledge (i.e., to use for decision making) from the above process–using mathematics to make sense of the data and information–and using it effectively, health care organizations can cut down on their ever-increasing health care costs.  To address the ever-increasing cost of health care in the U.S., perhaps we can look to statistics to look for an alternative to Obama Care (PPACA 2010).

Anthony S.
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End of 2nd week update

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The math department now has posted its own tutoring (as opposed to what is available in the tutoring centers). Unfortunately, the sessions are in midway, but I encourage you to make the special effort to go there. These are run by nearly-graduated students in the applied math and  math ed programs and many have 2 or 3 statistics classes BEYOND the one you are taking and may know 10 times more advanced statistics than I do (although I have TAUGHT the introductory topics over and over, and so know them probably better than they do).

Welcome!

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Use of and chatter surrounding statistics is quite prevalent in the popular media as well as in many work and play situations (such as sports). However, a good understanding and proper use of statistics requires us basically to start from zero and slowly develop a set of vocabulary and tools that we need to grapple with the subject. While its roots are in math, statistics became a separate profession in the latter part of the 20th century. [Computer science underwent a similar split from math over the course of the last 40 years or so.]

Statistics can broadly be divided into 2 branches, descriptive and inferential. For most of us, statistics is descriptive, easily computed numbers such as mean and standard deviation and an array of graphs used to display the distribution of the data, such as pie charts, bar and line graphs. From science classes, many of us are familiar with scatter plots, which are used to display a relation (or lack of) between two variables such as force and the stretch of a spring. We will spend much of the first three weeks doing descriptive statistics, during which time, we will get a heavy dose of Microsoft Excel and an introduction to the programming language R. I encourage the full use of these 2 tools for in-class work as well as homework.  The more difficult, predictive aspect of statistics, inferential, requires us to first to learn some probability, which is a branch of math. We will study probability for about 6 weeks. With probability under our belt, we will then devote the last 4 weeks of class to inferential statistics.

A word about resources. A quick look on Amazon shows that the textbook retails for $80 new and $20 used. In the past, students have been able to find PDF’s of the book as well. Probability and Statistics are such standard topics that there are many free online resources, including videos and archived course materials. I have decided to focus on the Khan academy videos (which will be a bit at a low-level for us). In addition, I will make use of lecture notes (Orloff) from an MIT course, which is at slightly high level for us. There is an online statistics textbook/course at a level which is low for us, but those of you who like to work in an integrated online environment (text, video, exercises, immediate feedback, etc.) will like it. Exam questions will be heavily based on homework. There are 2 probability textbook pdf’s (grinstead and snell and ross) you can use to supplement the required one and from which I myself will make use of for additional materials and problems.