PPT-Linear Algebra

vectors and matrices A vector is a bunch of numbers A matrix is a bunch of vectors A vector in space In space a vector can be shown as an arrow starting point is the origin ending point are the values of the vector. Calculus Functions of single variable Limit con tinuity and differentiability Mean value theorems Evaluation of definite and improper integrals Partial derivatives Total derivative Maxima and minima Gradient Divergence and Cu rl Vector identities D Arithmetic Operations The real numbers have the following properties Commutative Law Associative Law Distributive law In particular putting in the Distributive Law we get and so EXAMPLE 1 a b c If we use the Distributive Law three times we get This Calculus Mean value theorems Theorems of integral calculus Evaluation of definite and improper integrals Partial Derivatives Maxima and minima Multiple integrals Fourier series Vector identities Directional derivatives Line Surface and Volume integ Calculus Functions of single variable Limit con tinuity and differentiability Mean value theorems Evaluation of definite and improper integrals Partial derivatives Total derivative Maxima and minima Gradient Divergence and Curl Vector identities Di e Ax where is vector is a linear function of ie By where is then is a linear function of and By BA so matrix multiplication corresponds to composition of linear functions ie linear functions of linear functions of some variables Linear Equations Calculus Mean value theorems Theorems of integral calculus Evaluation of definite and improper integrals Partial Derivatives Maxima and mini ma Multiple integrals Fourier series Vector identities Directional derivatives Line Surface and Volume integ Calculus Mean value theorems Theorems of integral calculus Evaluation of definite and improper integrals Partial Derivatives Maxima and minima Multiple integrals Fourier series Vector identities Directional derivatives Line Surface and Volume integ Calculus Functions of single variable Limit continuity and differentiability Mean value theorems Evaluation of definite and improper integrals Partial derivatives Total derivative Maxima and minima Gradient Divergence and Cu rl Vector identities Di Calculus Functions of single variable limit continuity and differentiability mean value theorems evaluation of definite and improper integrals partia l derivatives total derivative maxima and minima gradient divergence and curl vector identities dir Abstraction . and Recursions in . Process . Algebra . Suzana Andova. Outline of the lecture. Combining silent steps with recursion. Fairness rules. Some examples . Fairness: is this what it is really about?. How can we use it?. PEC. . 2015. What topics can we use it for?. by . Chizuko. Matsumoto & Sweeny Term. Chapter-Lesson . Topic. 2-1. Model One-Step Equations. 2-4. Model Equations with Variables on Both Sides. Introduction. This chapter focuses on basic manipulation of Algebra. It also goes over rules of Surds and Indices. It is essential that you understand this whole chapter as it links into most of the others!. is a set . B. of values together with: . - two binary operations, commonly denoted by and ∙ , . - a unary operation, usually denoted by . ˉ or ~ or . ’. ,. - two elements usually called . Test Design. Performance Level Indicators. Algebra 1 . Keystones. Eligible Content – Test Design – Performance Level Indicators. Ms. Clarkson. Ms. . Hetrick. Ms. Sirio. Eligible Content. Eligible .