Two common examples of such statistics are the mean and standard deviation. Statisticians use these statistics for several different purposes. The intersections of those fields mean a lot of things. Data science emphasizes the data problems of the 21st Century, like accessing information from large databases, writing code to manipulate data, and visualizing data. Most do not consider AP Computer Science 'math' enough for it to play that role, hence the surge in AP Statistics. Interested in finding and patching vulnerabilities in computing systems? Both degrees focus on developing skills pertaining to data analysis, and both have courses designed to develop strong computer skills. Data science vs. computer science: Common job duties . Data science is based on the collection, preparation, analysis, management, visualization, and storage of large volumes of information. studying algorithm design/analysis vs programming languages). Statistics is a mathematically-based field which seeks to collect and interpret quantitative data. Computer science involves more independent work creating computer programs and applications, using algorithms and writing code. One is that computer science deals with the science behind the interaction between hardware and software systems and computational … CS set the stage for data science in that it provided the programming languages necessary to process big data. It's hard to describe all of computer science units as a whole, since they can be very different (e.g. A GPA of 3.25 is required for Distinction, 3.5 for High Distinction, and 3.75 for Highest Distinction. According to Wikipedia, a pivotal article called Data Science: An Action Plan for Expanding the Technical Areas of the Field of Statisticswritten by William Cleveland gave it a name in 2001, well after CS was on the scene. When considering a data science degree vs. statistics degree, it’s important to understand the underlying similarities. This post will show you the key facts about each major and help you to decide which would be a better degree for you.

Actually most "computational" type programs are "applied" versions of the more broad major. Nowadays, both machine learning and statistics techniques are used in pattern recognition, knowledge discovery and data mining. The computer science approach, on the other hand, leans more to algorithmic models without prior knowledge of the data. If you’ve been looking into data science you probably have some questions. There is no reason to think lesser of yourself or even to compare yourself to your classmates. If you want to be a data scientist, get a BSc in computer science and do a minor in math and if you can fit it in do a 2nd minor in statistics. Computer Science VS statistics 05:09 read (words) Print Email. 14. Applied Math vs. Computer Science vs. Statistics Thread starter avant-garde; Start date Apr 8, 2009; Apr 8, 2009 #1 avant-garde. Data science use tools, techniques, and principles to sift and categorize large data volumes of data into proper data sets or models. “And it kinda makes sense,” Brad continues. Computer scientists are taught to design real-world algorithms that will be used as part of software packages, while statisticians are trained to provide the mathematical foundation for scientific research. Statistics is another broad subject which deals with the study of data and is widely applied in numerous fields. About 1/4 of my Statistics courses are computer science based (C programming, SAS programming, Discrete Mathematics, Numerical Calculus, and some upper level Stats classes that require programming skills).

I can't give you much detail into what CS students do on the upper levels, but Statistics gives into a lot of methods and analysis classes. Statisticians are heavily focused on the use of a special type of metric called a statistic. 189 0. "Computer Science" : "Statistics");

Eh, there's kind of a big difference. Computer Science Salaries. Careers common among computer science degree-holders often lead to lucrative salaries, according to data from the Bureau of Labor Statistics. And at a tech company like Twitch, it’s clear that applying those learnings requires a deep understanding of computer science. Mathematical modeling through regression analysis is a big part.

Most of the math prerequisites between the two degrees are similar, Calc 1-3, Linear Algebra, Proof classes.

Both are classified as "Quantitative Degrees" when you start looking for jobs, so they both open up a lot of doors in similar industries.

IMO, the difference (in the real world) between a CS major and a Stats major is the CS major wants to create programs and solve problems through computer development, and could be more of a "techie" person. Try your hand at both and maybe you could even double major.

I'm going to add more and see what you guys think.

I originally applied to college as an English major due to my double 5s on the AP tests. Both terms have similarity, but there is a significant difference between the two. There are a number of ways the roles of statisticians and computer scientists merge; consider the development of models and data mining. In this post, I’ll tell you the rest of the story, as I see it, viewing events as a statistician, computer scientist and R activist. An unchanged top five universities lead this year’s ranking of the best places to study computer science & information systems, with Massachusetts Institute of Technology (MIT) continuing to perform particularly well in our employer reputation survey. vs. Statistics? ALL RIGHTS RESERVED. Students studying programs in Computer Science, Mathematics, and Statistics gain insights from all three disciplines, making them a v… Whichever one you are more passionate about will likely be easier. And maybe, statistics + coding = data science. A data scientist is an individual with adequate domain knowledge relevant to the question addressed. Berkeley's overall acceptance rate is 17%, but its Computer Science acceptance rate is only 8.5%. Use the interactive table below to filter the rankings by location, and click on individual universities for more information. See what you like better.

The prerequisites for both classes should be really similar at least until sophomore year with the exception of maybe one or two extra classes which might fill some other graduation requirements. Hadoop, Data Science, Statistics & others. Marketing + coding = growth hacking. Data scientists use methods from many disciplines, including statistics. Close. Are you fascinated by the possibilities of machine learning in data science?

Computer science vs statistics major If you are deciding between majoring in statistics or computer science, you might want to know more about what each major has to offer. On top of that, AP Computer Science is perceived as being much harder than AP Statistics. Administered by the School of Computer Science and Engineering, this is a full Computer Science degree plus a Science degree. Data Science is the combination three fields’ data engineering, maths, and statistics. If you like computers and statistics, there is a huge demand for people who can write computational and simulational models, physical and non-physical. Computer Science vs. Computer Engineering; Cyber Security vs Computer Science; Data Analyst vs Data Scientist; Data Analytics vs. Business Analytics; Data Science vs. Machine Learning ; Resources; About 2U; Data Science vs. Machine Learning. We are aware that, big data is mostly available in unstructured formats and contains non-numeric data. A wide discipline which involves programming, understanding of business models, trends, and so on. There are even a few schools with Computational Statistics programs.

My school offers computational economics, geography, and economics majors, but they're B.A.s. In other words, computer science deals with programming software and hardware where data science deals with analytics, programming, and statistics. vs. Computer Science? CS vs. Statistics. It appears that formal university training in Data Science evolves as a hybrid between Computer Science and Statistics, … for the degree of Bachelor of Science in Liberal Arts & Sciences Major in Statistics & Computer Science. Data science is a specialized skill and can be understood as: Therefore, it is apparent that data science is an interdisciplinary area and needs varied skill sets to gain mastery in this domain. Computer science is the study of algorithmic processes, computational machines and computation itself. Stats is boring. According to Larry Wasserman: In his blog, he states how the same concepts have different names in the two fields: Robert Tibshirani, a statistician and machine learning expert at Stanford, calls machine learning “glorified statistics." I am, … Engineering Majors. One common way of dividing the field is into the areas of descriptive and inf… Computer Science (Online MCIT UPenn) vs Statistics (Online MS @ Texas A&M) Question. Also, you'll likely find that a lot of people in college talk themself up because they have inferiority complexes and are usually doing worse than you.

IMO, a degree in Statistics (which is rarer) can separate you from those with degrees in Computer Science (which is more common).

There is a lot of crossover between the two degrees. Data science is one of the most attractive career options of the past couple of years, with people from all walks of life transitioning into positions that combine analysis, statistics, machine learning, programming, and computer science to draw insights out of numbers.. Data science in simple terms can be understood as having strong connections with databases including big data and computer science. Data science combines the application of subjects namely computer science, software engineering, mathematics and statistics, programming, economics, and business management. Studying Computer Science (CS) at UC Berkeley. Many computational mathematics programs are called "applied and computational mathematics". The two fields are converging more and more even though the below fi… Also to note, all statisticians cannot become data scientists and vice-versa. There is no "data science" scientific field, there are no "data science" professors. If you want to be a data scientist, get a BSc in computer science and do a minor in math and if you can fit it in do a 2nd minor in statistics. Statistics is the field of mathematics which deals with the understanding and interpretation of data. Data science emphasizes the data problems of the 21st Century, like accessing information from large … To clarify Developing the perspectives on a few analysts, this paper supports a major tent perspective on data study. This is opposed to statistics which focuses on analysis using standard techniques involving mathematical formulas and methods. Do you want to build robots and develop autonomous systems? The outlook in terms of career prospects is positive. I know that in the long run it won't matter that my CS degree was in Science or Arts, but I fear that a computational route might mean that I'd miss out on some of the more theoretical classes which could help me stay competitive in the job market.

That's why theory is important right? Both data science and computer science occupations require postsecondary education, but let’s take a … You might want to figure out if you like more proof-based 'pure' math or if you like ...well, statistics. The following list, from payscale.com, shows average computer science … Both Statistics and Machine Learning create models from data, but for different purposes. Computer science deals with scientific ways of finding a solution for a problem. Machine learning is generally taught as part of the computer science curriculum, and statistics is taught either by a dedicated department or as part of the math department. Statistics was primarily developed to help people deal with pre-computer data problems like testing the impact of fertilizer in agriculture, or figuring out the accuracy of an estimate from a small sample. Data science also includes things like data wrangling and preprocessing, and thus involves some level of computer science since it involves coding, setting up connections and pipelines between databases, web servers, etc. That alone is basically the prerequisites to take serious (ie not big picture/toy stuff "for everyone!" Statistics is highly significant in data related studies because it helps in. Another important aspect to consider when deciding between Data Science and Computer Science for your education is the type of work you’d like to be doing. The QS World University Rankings by Subject are based upon academic reputation, employer reputation and research impact (click here to read the full methodology). Computer science degree recipients not only work for technology companies, but also frequently enter the finance sector and the retail industry, experts say. I'm guessing your university doesn't have a business school.

In all seriousness you sound like a smart guy. By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to our Privacy Policy, New Year Offer - All in One Data Science Bundle (360+ Courses, 50+ projects) Learn More, 360+ Online Courses | 1500+ Hours | Verifiable Certificates | Lifetime Access, Data Scientist Training (76 Courses, 60+ Projects), Tableau Training (4 Courses, 6+ Projects), Azure Training (5 Courses, 4 Projects, 4 Quizzes), Hadoop Training Program (20 Courses, 14+ Projects, 4 Quizzes), Data Visualization Training (15 Courses, 5+ Projects), Data Scientist vs Data Engineer vs Statistician, Business Analytics Vs Predictive Analytics, Artificial Intelligence vs Business Intelligence, Artificial Intelligence vs Human Intelligence, Business Intelligence vs Business Analytics, Business Intelligence vs Machine Learning, Data Visualization vs Business Intelligence, Machine Learning vs Artificial Intelligence, Predictive Analytics vs Descriptive Analytics, Predictive Modeling vs Predictive Analytics, Supervised Learning vs Reinforcement Learning, Supervised Learning vs Unsupervised Learning, Text Mining vs Natural Language Processing, Design and implementation in 4A’s – Data Architecture, Acquisition, Analysis and Archival, Applying advanced techniques in mathematics and statistics to model data for deep analysis, Adequate programming and development skills, algorithm development skills, Deciding the type of data required to address a given problem, Analysis to be done to draw conclusions from data, Assessing the effectiveness of results and to evaluate uncertainties, Design for planning and conducting research, Descriptions which implies exploring and summarizing data, Making predictions and inference using the phenomena represented by data. There is a lot of crossover between the two degrees. All this data is just noise unless it is analyzed and useful information is extracted from them. Data science has developed recently with big data and will continue to grow in the coming years as data growth seems to be never-ending. I make a mental note to get back on those Udemy classes I’ve been neglecting. There are some things, but the majority will not be statistics related in a traditional sense. The Obama White House predicted that by 2020, there would be 1.4 million computer-science-related jobs available, and only about 400,000 computer science graduates who … I think that there is a fundamental difference between statistics and much of current computer science type machine learning. Data science is more oriented to the field of big data which seeks to provide insight information from huge volumes of complex data. Which one will have the most job opportunities in the near future (10 years approx)? Computer science, the study of computers and computing, including their theoretical and algorithmic foundations, hardware and software, and their uses for processing information.The discipline of computer science includes the study of algorithms and data structures, computer and network design, modeling data and information processes, and artificial intelligence. [quote] Prospective Students Undergraduate Postgraduate International PhD Programme Research News.