Final answer:
The models used for modeling chemical concentration in well water over time can include Linear Regression, Exponential Regression, and Polynomial Regression, each with distinct equations and applications.
Step-by-step explanation:
The regression population models that would be used for modeling the concentration of various chemicals in well water over time are:
- Linear Regression: This model would fit a line to the data points, with the equation typically written as y = mx + b, where y represents the chemical concentration, m is the slope of the line, x represents time, and b is the y-intercept.
- Exponential Regression: This model is appropriate if the change in chemical concentration grows or decreases at a rate proportional to its current value, which can be written as y = abx, where a is the initial amount, b represents the growth factor, and x is time. It is represented graphically by a 'J-shaped' curve.
- Polynomial Regression: This model might be used if the relationship between time and chemical concentration is more complex than a straight line or simple exponential curve. The equation for a polynomial regression of degree n is y = a0 + a1x + a2x2 + ... + anxn.
In the context of population growth, exponential growth describes scenarios where a population increases without limits, while logistic growth adds constraints to growth reflecting environmental limitations.