Math 7 Standards
... Expressions and Equations:
7.EE.1-Apply properties of operations as strategies to add, subtract, factor, and expand linear
7.EE.2-Understand that rewriting an expression in different forms can show how quantities are
7.EE.4-Use variables to represent quantities in a real-world ...
... Students will understand that the usefulness of a model can be tested
by comparing its predictions to actual observations in the real world.
But a close match does not necessarily mean that the model is the
only “true” model or the only one that would work.
... Derivation of explicit expressions
for the independent model parameters.
The system of
design algorithms for exceptions
based on the methods of computer algebra.
The software is developed.
... Use the inverse transform random variate generation technique together withthe Monte Carlo
simulation method to determine the reliability in a system consisting of three components,
1,2,3 with Weibull failure probability distribution functions given as follows:
F1 = 1 − exp(−t0.5 )
F2 = 1 − exp(−t)
... Math 103 or Math 104 with a grade C or above.
General Goals and Objective for the Course:
• Identify the basic graphs and properties of polynomial, rational, exponential, and
logarithmic functions. Apply the knowledge of functions to business applications
such as simple, compound or continuous comp ...
An inverse problem in science is the process of calculating from a set of observations the causal factors that produced them: for example, calculating an image in computer tomography, source reconstructing in acoustics, or calculating the density of the Earth from measurements of its gravity field.It is called an inverse problem because it starts with the results and then calculates the causes. This is the inverse of a forward problem, which starts with the causes and then calculates the results.Inverse problems are some of the most important mathematical problems in science and mathematics because they tell us about parameters that we cannot directly observe. They have wide application in optics, radar, acoustics, communication theory, signal processing, medical imaging, computer vision, geophysics, oceanography, astronomy, remote sensing, natural language processing, machine learning, nondestructive testing, and many other fields.