Math and Science Solutions for Businesses/Math - Self Study.


  I am about 25 years or so since graduating with an MBA (BA in Philosophy, though started our engineering).  Myself and associated realized while helping our kids out with math homework (high school and college) that we had forgotten nearly everything. (We both took and passed Calc I & II in college ages ago.) So we decided to sit down and re-learn math from the ground up.  We are basing our self study program around the Chalk Dust & Great Courses video lectures and using the Demystified Series as a textbook.   We are also using Bagatrix to help as a tutor.
  My question is order of study.
  Here is what we are thinking and please tell me if we are in err.
  Thank you in advance.

  High School Algebra
  College Algebra
  Geometry (High School-College)

  We are figuring about 8 weeks per level with about 6-10hours of study a week individually and 4 hours a week together and making up tests for one another.
  Any input is appreciated.

I think I might put Geometry before College algebra since it contains more core math-related concepts (Definitions/Axioms -->Lemmas -->  Proofs) that will help condition your mathematical thinking. Geometry is also very visual and can be a little easier to use with abstract concepts. Although directly transitioning from Geometry to Trig may seem logical, Trig is used (IHMO) largely to support algebraic manipulations. So I think a good grounding in Geometry followed by advanced algebra is a more useful progression to Trig.

Good luck!

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Randy Patton


Questions regarding application of mathematical techniques and knowledge of physics and engineering principles to product and services design, optimization, prediction, feasibility and implementation. Examples include sales and product performance projections based on math/physics models in addition to standard regression; practical and cost effective sensor design and component configuration; optimal resource allocation using common tools (eg., MS Office); advanced data analysis techniques and implementation; simulation and "what if" analysis; and innovative applications of remote sensing.


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