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 * 1)  Numerical ODE solving in Excel:


 * 1) Fitting ODE parameters to data using Excel:
 * 2)  Temperature sensors
 * 3)  Pressure sensors
 * 4)  Level sensors
 * 5)  Flow sensors
 * 6)  Composition sensors
 * 7)  pH and viscosity sensors
 * 8)  Valves:
 * 9)  Valves:
 * 10)  P&ID standard notation
 * 11)  P&ID standard structures, location of features
 * 12)  P&ID standard pitfalls
 * 13)  Safety features in P&ID
 * 14)  Boolean models:
 * 15)  Logical control programs:
 * 16)  Surge tank model
 * 17)  Heated surge tank
 * 18)  Bacterial chemostat
 * 19)  ODE & Excel CSTR model w/ heat exchange
 * 20)  ODE & Excel model of a simple distillation column
 * 21)  ODE & Excel model of a heat exchanger
 * 22)  ODE & Excel model of an adiabatic PFR
 * 23)  P, I, D, PI, PD, and PID control
 * 24)  PID tuning via classical methods
 * 25)  PID tuning via optimization
 * 26)  PID downsides and solutions:
 * 27)  Finding fixed points in ODEs and Boolean models
 * 28)  Linearizing ODEs
 * 29)  Eigenvalues and Eigenvectors
 * 30)  Using eigenvalues and eigenvectors to find stability and solve ODEs
 * 31)  Phase plane analysis: attractors, spirals, limit cycles
 * 32)  Root locus plots: effect of tuning
 * 33)  Routh stability: ranges of parameter values that are stable
 * 34)  Feedback control: What is it?  When useful?  When not?  Common usage.
 * 35)  Feed forward control: What is it?  When useful?  When not?  Common usage.
 * 36)  Cascade control: What is it?  When useful?  When not?  Common usage.
 * 37)  Ratio control: What is it?  When useful?  When not?  Common usage.
 * 38)  Common control loops / model for liquid pressure and liquid level
 * 39)  Common control loops / model for temperature control
 * 40)  Common control architectures / model for reactors
 * 41)  MIMO control using RGA
 * 42)  MIMO using model predictive control
 * 43)  Determining if a system can be decoupled
 * 44)  Basic statistics: mean, median, average, standard deviation, z-scores, and p-value
 * 45)  Six Sigma: What is it and what does it mean?
 * 46)  Bayes Rule, conditional probability, independence
 * 47)  Occasionally dishonest casino?: Markov chains and hidden Markov models
 * 48)  Continuous Distributions: normal and exponential
 * 49)  Discrete Distributions: hypergeometric, binomial, and poisson
 * 50) [[Image:new.gif]] Multinomial distribution
 * 51)  Comparisons of two means
 * 52)  Factor analysis and ANOVA
 * 53)  Correlation and mutual information
 * 54)  Random sampling from a stationary Gaussian process
 * 55)  SPC: Basic Control Charts: Theory and Construction, Sample Size, X-Bar, R charts, S charts
 * 56)  Design of experiments via Taguchi methods: orthogonal arrays
 * 57)  Design of experiments via factorial designs
 * 58)  Bayesian network theory
 * 59)  Learning and analyzing Bayesian networks with Genie