Advanced Precalculus Notes 4.9 Building Exponential, Logarithmic, and Logistic Models.

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Presentation transcript:

Advanced Precalculus Notes 4.9 Building Exponential, Logarithmic, and Logistic Models

Exponential Model Year (x) Price (y) 1986 t= t= t= t= t= t= t= t= t= Year (x) Price (y) 1995 t= t= t= t= t= t= t= t= t= The above data represents the closing price of Harley Davidson stock at the end of each year. a) Using a scatter plot, graph the data.

b) Use the regression capabilities of the calculator to fit an exponential function to the data. c) Express the equation in the form d) Graph the equation in (c) and use it to predict the price of the stock in actual price: $31.62 e) What does k represent in the equation?

Logarithmic Model Pressure (p) mm. Mercury Height (h) kilometers That above data represents the relation between the height of a weather balloon. a) Using a scatter plot, graph the data. b) Use the regression capabilities of the calculator to fit a logarithmic function to the data. c) Express the equation in the form d) Graph the equation in (c) and use it to predict the height of the balloon if the atmospheric pressure is 560 mm.

Logistic Model Time Hours Yeast Biomass Time Hours Yeast Biomass

The given data represents the amount of yeast biomass in a culture after t hours. a) Using a scatter plot, graph the data. b) Use the regression capabilities of the calculator to fit a logistic function to the data. c) Express the equation in the form d) Graph the equation in (c) and use it to predict the population of the culture at t = 19 hours.

Assignment: page 342: 1, 7, 9