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Growth and Accumulation
Authors: Bill Davis, Horacio Porta and Jerry Uhl © 1999
Producer: Bruce Carpenter
Publisher:
Distributor: ![[Graphics:Images/120syl_gr_3.gif]](http://cm.math.uiuc.edu/220syl_files/120syl_gr_3.gif)
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Line functions and polynomials. Interpolation of data. Compromise lines through data. Dominant terms in the global scale.
Reading plots. Linear models. Drinking and driving. Japanese economy cars versus American big cars. Data analysis and interpolation. Data analysis of U.S. national debt and U.S. population in historical context, including plots of yearly growth and the effect of immigration on the growth of the U.S. population. Cigarette smoking and lung cancer correlation. Global scale of quotients of functions studied by looking at dominant terms in the numerators and denominators.
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How to write exponential and logarithm functions in terms of the natural base
. While line functions post a constant growth rate, exponential functions post a constant percentage growth rate. How to construct a function with a prescribed percentage growth rate.
Recognition of exponential data, exponential data fit, carbon dating, credit cards, compound interest, effective interest rates, financial planning, decay of cocaine in the blood, underwater illumination, inflation.
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The instantaneous growth rate
as the limiting case of the average growth rates
. What it means when
is positive or negative. Calculation of
for functions
like
,
, ,
and
. Why
is the natural logarithm andwhy
is the natural base for exponentials. . Max-min.
Relating the plots of
and
. Using a plot of
to predict the plot of
. Visualizing the limiting process by plotting
and
on the same axes and seeing the plots coalesce as
closes in on
. Spread of disease model. Instantaneous growth rates in context.
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The derivative as the instantaneous growth rate. Chain rule. Product rule as a consequence of the chain rule. Instantaneous percentage growth rate of a function
.
Another look at why exponential growth dominates power growth and why power grow th dominates logarithmic growth. Logistic model of animal growth. The idea of li near dimension and using it to convert a model of animal height as a function of age to a model of animal weight as a function of age. Learning why the adololes cent growth spurt is probably a mathematical fact instead of a biological accide nt. Compound interest. Making functions with prescribed instantaneous percentage growth rate.
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What it means when
for .
Why
is not as big (or small) as it can be at
unless
.
Why a good representative plot of a given function
usually includes all
's at which
. Max-Min in one or two variables.. Using the derivative to get best least s quares fit of data by smooth curves. Fitting of Space shuttle O-ring failure dat a as a function of temperature and using the result to explain why the Challenge r disaster should have been predicted in advance. Data fit by lines a nd by Sine and Cosine waves. Optimal speed for salmon swimming up a river. Desig ning the least cost box to hold a given volume. Analysis of an oil slick at sea. How tall is the dog when it is growing the fastest? Analysis of what happens to ![]()
as
advances from
to
.
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The three differential equations
&nb sp;
,
&nb sp; ![]()
and t heir solutions.
The meaning of the parameters
and
in the three differen tial equations. Why it's often a good idea to view logistic growth as toned down exponential growth.
Models based on these differential equations. Why radio active decay is modeled by the differential equation
. Logistic versus exponential growth. Biological principles behind carbon dating. Growth of U.S. and world populations: Malthusian versus logistic models. Calculation of interest payments resulting from buying a car on time. Ma naging an inheritance. Wal-mart sales. Pollution elimination, data analysis, spe culating on why dogs and humans grow faster after their birth than they are at t he instant of of their birth, but horses grow fastest at the instant of their bi rth. Newton's law of cooling. Pressure altimeters.
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The race track principles:
If
and
for
, then
for
.
If
and
is approximately equal to
for
, then
is approximately equal to
for
.
If
and
for
, then
for
.
Eul er's method of faking the plot of a function with a given derivative explained i n terms of the race track principles.
Euler's me thod of faking the plot of a the solution of a differential equation explained i n terms of the race track principles.
Using the race track principle to explain why, as
advances from
, the plots of solutions of
& nbsp;
and
will run close together in the case th at
is small relative to . Why
for
and related inequalities. Estimating how many accurate decimals of
are needed to get
accurate decimals of
. The error function. Calculating accurate v alues of
and
.
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Plots of numerical approximations to solutions of first order differential equat ions. Qualitative analysis of first order differential equations and systems of first order differentitial equations.
Analysis of the predator-prey model. Cycles in the predator-prey model. Drinking and driving model. Variable interest rates. Michaelis-Menten Drug equation. War games based on Lanchester war model including a simulation of the Battle of Iwo Jima. Harvesting in the logistic model. SIR epidemic model. The idea of chaos.
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Parametric plotting of curves in two dimensions. Parametric plotting of curves a nd surfaces in three dimensions. Derivatives for curves given parametrically.
Circular parameterization (polar coordinates) and other parameterizations. Proje ctile motion. Cams designed by sine and cosine wave fit. Predator-prey plotting. Parametric plottting of circles and ellipses. Elliptical orbits of planets and asteroids. Plotting of circles, tubes and horns centered on curves in three dimensions. Equilibrium populations in the predator-prey model . Modifications of the predator-prey model. The effect of poisoning predators wi th application to spraying insecticides.
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Integrals defined as area measurement as done in E. Artin's MAA notes written in the 1950's. Approximations by trapezoids.
Integrals of functions given by data lists. Using known area formulas for triang les, trapezoids and circles to calculate integrals. Odd functions. Trying to bre ak the code of the integral by taking selected functions
, putting
& nbsp;
and plotting
and
.
on t he same axes for small
's. Plotting
and guessing a fo rmula for
. Plottingt and guessing a formula for
. Estimating the acr eage of farm field bordered by a river.
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If
is given by
then
.
The fundamental formula
.
Relating distance, velocity and acceleration through the fundamental formula. Ge tting the feel of the fundamental formula by using it to calculate integrals by hand. Relating
to the solution of the differential equa tion
with
.
Very brief look at the "indefinite integral,"
Measuring area between curves. T he error function,
, and other functions defined by integrals. Measurements of acculumulated g rowth. Coloring ceramic tiles.
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Measurements based on slicing and accumulating: Area and volume; density and mas s. Measurements based on approximating and measuring: Arc length. Measurements b ased on the fundamental formula: Accumulated growth.
Volumes of solids with no special emphasis on solids of rotation. Volume measure ments of curved tubes and horns. Eyeball and precise estimates of curve lengths. Filling water tanks. Harvesting corn. Voltage drop. Another look at linear dimension. Work. Present value of a profit-making scheme. Catf ish harvesting. Designing an 8 fluid ounce logarithmic champagne glass.
Mathematica] Math 285 has been fun,as well as a great help with other related classes (like ECE 210).
Techs support both the lab machines and the software used in this program.
In the event of a problem, send an e-mail to tech@cm.math.uiuc.edu.