I found many FE programs have Pre-Requisites in calculus-based probability & statistics. I only took an engineering probability & statistics in my undergraduate study, so I didn't really meet this requirement. Do any of you know if there is any school offer this class online? Or are there any schools in LA offering this course in their extension?
online calculus-based probablity & statistics course
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You probably need to take in class courses to provide proof that you meet requirement. Almost any math dept provides this kind of courses. And you have to get good grades (A). Taking the course and getting C,D is not gonna help.
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take night or weekend class. If you don't have time for undergrad courses now, how would you find time to study for heavy course in MFE program later ?
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MIT Open courseware may be nice. I believe there are also Podcasts for some classes.
http://ocw.mit.edu/OcwWeb/web/courses/courses/index.htm#Mathematics
http://ocw.mit.edu/OcwWeb/web/courses/courses/index.htm#Mathematics
programmes
I'm a business student, and i recently got my MBA in finance in which i specialized in derivatives, and im thinking to take an FE masters. what are my chances to get accepted in a good FE programme? i know i would have to take pre-courses.
I'm a business student, and i recently got my MBA in finance in which i specialized in derivatives, and im thinking to take an FE masters. what are my chances to get accepted in a good FE programme? i know i would have to take pre-courses.
Stevens Inst of Technology offers a webcampus course in calculus-based probability theory; its a pre-requisite for their financial engineering program. Its an online class but meets weekly, so its not self-study. It may be a good option for you. They typically "meet" at 7pm on some weeknight, for about 2 hours. The prof does a live class and you participate via headset and microphone. You usually get the class notes posted a few weeks before the class, and the prof spends the session reviewing important areas and doing a lot of sample problems. I'm not going to get into the benefits and downfalls of the webcampus courses; there are some threads on that already. Bottom line--its an accessible course for people who need flexibility; its fully accredited; taught by real professors; and you have graded homework and exams that result in a grade (hopefully, an "A"). Good luck. If you want more specific info I'm happy to help, or check out WebCampus.Stevens-tech.edu.
I took Statistics 101 and 102 in college. Don't have a description but you can assume those are the first two stats classes in the progression. I have never heard of this calculus-based probability and I'm not even sure if what I learned in my two stats classes have covered some of that material.
Question to anyone who might know: I found this online course available at an extension program of a university near me.
Would this be considered a calc-based probability/stats course that would make the MFE adcom happy to see?
Advanced Statistics and Quantitative Methods
This is an advanced course in inferential statistics with an emphasis on the practical application of statistical analysis. Instruction includes an examination of the role of statistics in research; understanding statistical terminology; use of appropriate statistical techniques; and interpretation of findings in the fields of economics, business, nursing, and medical research. Specific topics include graphing and tabulation of data, hypothesis testing for small and large samples, chi-squared, statistical quality control, analysis of variance (ANOVA), regression, correlation, and decision making under uncertainty.
Question to anyone who might know: I found this online course available at an extension program of a university near me.
Would this be considered a calc-based probability/stats course that would make the MFE adcom happy to see?
Advanced Statistics and Quantitative Methods
This is an advanced course in inferential statistics with an emphasis on the practical application of statistical analysis. Instruction includes an examination of the role of statistics in research; understanding statistical terminology; use of appropriate statistical techniques; and interpretation of findings in the fields of economics, business, nursing, and medical research. Specific topics include graphing and tabulation of data, hypothesis testing for small and large samples, chi-squared, statistical quality control, analysis of variance (ANOVA), regression, correlation, and decision making under uncertainty.
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I don't think so. It's stats for dummies. It won't hurt you to know all this -- even without calc-based probability -- but this isn't what is meant by a calc-based course. I think it's meant for business and life science majors.
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Nope. There's another version of probability, based on measure theory, a quantum jump above calc-based probability, that serves as the bedrock of stochastic calculus.
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Working exclusively in the discrete setting, and the foundation for which is combinatorics. For example, I toss a coin seven times. What's the probability I get at least three heads? Or I have an urn with five green balls and seven red balls. I pick up two balls simultaneously. What are the odds both are red? This is the kind of material usually taught in European and Asian high schools and in the first year of US college courses (e.g., "College algebra and Probability"). If you have access to a university library, look for the book, "Elementary Probability with Applications," by Larry Rabinowitz (A K Peters, 2005); this covers non-calc probability. Of course, the moment one introduces a continuous setting, calc comes in.
Are you also asking what's the difference between calc-based probability and measure-theoretic probability?
Stats for dummies! :wall
I can't seem to find any classes under 1000 dollars that I can take that is a calc-based stats/probability class. Surely, you will never find a class like this a jr. college.
I am not even sure what most math departments would officially call a calc-based stats/probability course.
USC MMF's prerequisite considers this class in their math department as a prerequisite to their program and call it "Probability Theory" which will fulfill the calc-based stats/prob requirement.
407 Probability Theory (4, FaSp) Probability spaces, discrete and continuous distributions, moments, characteristic functions, sequences of random variables, laws of large numbers, central limit theorem, special probability laws. Prerequisite: MATH 226.
Of course the USC course costs like 5000 dollars.
Do you think this course taught at Statistics.com (not a college but like an online Stat reference and education site that does give grades if you sign up through a school-cost around 700 dollars total) would be considered calc-based probability? Bayesian Statistics. I learned some of this stuff already even in my GMAT study guides as well as in my Stats classes. This is conditional probability. NOt overly difficult stuff.
Introduction to Bayesian Statistics
Dr. William M. Bolstad Aim of Course:
This course will introduce you to the basic ideas of Bayesian Statistics. In Bayesian statistics, population parameters are considered random variables having probability distributions. These probabilities measure "degree of belief". The rules of probability (Bayes' theorem) are used to revise our belief, given the observed data. You will learn how to perform Bayesian analysis for a binomial proportion, a normal mean, the difference between normal means, the difference between proportions, and for a simple linear regression model. Bayesian methods will be contrasted with the comparable frequentist methods, demonstrating the advantages this approach offers. These include:
- Bayesian statistics uses both prior and sample information. Usually something is known about possible parameter values before the experiment is performed, and it is wasteful not to use this prior information.
- The Bayesian approach allows direct probability interpretations of the parameters, given the observed data. All probability statements in the frequentist approach are about possible data that could have been observed, but were not. These statements aren't of much scientific use.
- Bayesian statistics uses a single tool, Bayes' theorem. Frequentist procedures require many different tools.
- Bayesian methods often out perform the corresponding frequentist methods even when evaluated using frequentist criteria.
- Bayesian statistics has a straightforward method for dealing with nuisance parameters. It integrates them out of the joint posterior distribution. There is no single corresponding method in frequentist statistics, and nuisance parameters are harder to deal with.
- Bayes' theorem gives the general way to find the predictive distribution of future observations. There is no such general method in frequentist statistics, only a collection of methods that sometimes work.
Biostatisticians, those designing and analyzing clinical trials, social science statisticians, environmental and geophysical scientists; nearly all fields of statistical analysis are amenable to a Bayesian approach.For those enrolled in Professional Advancement Programs, this is a required or elective course in the following Programs:
- Biostatistics (epidemiology) - elective
- Biostatistics (controlled trials) - elective
The course is structured as follows
SESSION 1: Introduction
- Logic probability & uncertainty
- Discrete random variables
- Bayesian inference for discrete random variables
- Continuous random variables
- Bayesian inference for binomial proportion
- Comparing Bayesian and frequentist inferences for proportion
- Bayesian inference for normal mean
- Comparing Bayesian and Frequentist inferences for mean
- Bayesian inference for difference between means
- Bayesian Inference for Simple Linear Regression Model
- (Additional Material: Simple Logistic Regression Model)
- Robust Bayesian methods
- (Additional material: Bayesian inference for normal standard deviation)
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Junior college = colossal waste of time. Don't bother. The courses are a joke.
Yep, this is the real McCoy.
Nope, it's irrelevant to what you need. Where exactly are you? If you're in a civilised city like NYC, there are the CUNY colleges where you could take the required course (e.g., Baruch, CCNY, Queens, Hunter, and so on). If you're in the middle of nowhere (which is most of the US), it's more problematic.
I'm in way uncivilized LA. :D I had to look to the Jr. colleges to fulfill my MV Calc and Linear Algebra and C++ programming.
I guess I need to take this kind of probability theory class. Honestly, I feel like I learned some of that already in my two stats courses in college. I'm hearing I need to take this calc-based stats/prob class too many times and now I am hearing I also need to take a number theory/numerical analysis class. Jeez so many **** barriers just to apply to these **** programs. I wonder if I"m missing anything else. Oh yeah ODE/PDE have to take those too. Jeez, maybe I should just reapply to college once again and go for a math major. :-\"
I guess I need to take this kind of probability theory class. Honestly, I feel like I learned some of that already in my two stats courses in college. I'm hearing I need to take this calc-based stats/prob class too many times and now I am hearing I also need to take a number theory/numerical analysis class. Jeez so many **** barriers just to apply to these **** programs. I wonder if I"m missing anything else. Oh yeah ODE/PDE have to take those too. Jeez, maybe I should just reapply to college once again and go for a math major. :-\"
-- I am having exactly same thoughts... I am taking Adv Calc, PDE, Stat in fall.So, what is the probability & statistics path should be:
Basic prob & stat - > Calc based prob & medium level stat - > Stochastic Calc ?
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Numerical analysis. From your comments, you would benefit from the kind of math degree Baruch offers. Even if a program accepts you, you're likely to be in over your head very fast. Less haste, more speed.
For probability, find the title of the text and ask the instructor about the level of the course. You want to hear the magic words "continuous distributions," "central limit theorem," "law of large numbers," "moment-generating function," and "characteristic function."
For probability, find the title of the text and ask the instructor about the level of the course. You want to hear the magic words "continuous distributions," "central limit theorem," "law of large numbers," "moment-generating function," and "characteristic function."
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