1/20/2016 Integrated Math 10 - Santowski 1 Lesson 13 Introducing Exponential Equations Integrated Math 10 - Santowski
Comparing Linear & Exponential Models Data set #1 – Can this data be modeled with a linear relation? Why/why not? How do you know? Data set #2 - Can this data be modeled with a linear relation? Why/why not? How do you know? 1/20/2016 Integrated Math 10 - Santowski 2 x y x y
HINT Any obvious number patterns in the data?? 1/20/2016 Integrated Math 10 - Santowski 3
Comparing Linear & Exponential Models Data set #3 – Can this data be modeled with a linear relation? Why/why not? How do you know? Data set #4 - Can this data be modeled with a linear relation? Why/why not? How do you know? 1/20/2016 Integrated Math 10 - Santowski 4 x y x y
Comparing Linear & Exponential Models Data set #5 – Can this financial data be modeled with a linear relation? Why/why not? How do you know? What equation summarizes the data relationship and what do the #’s in the eqn represent? Data set #6 - Can this financial data be modeled with a linear relation? Why/why not? How do you know? What equation summarizes the data relationship and what do the #’s in the eqn represent? 1/20/2016 Integrated Math 10 - Santowski 5 x y x y
Summary What NEW pattern/relationships have you seen in the data sets? How can we write equations for our data that reflect our new patterns/relationships? 1/20/2016 Integrated Math 10 - Santowski 6
Summary How can we write equations for our data that reflect our new patterns/relationships? If you have correctly answered this question, go to slides # How can we write equations for our data that reflect our new patterns/relationships? If you have NOT correctly answered this question, go to slides #9 - #11 1/20/2016 Integrated Math 10 - Santowski 7
1/20/2016 Integrated Math 10 - Santowski 8 Additional data sets (if needed)
Exploring Exponential Equations Data set #A – This data can be modeled with a exponential relation. How do you know? What “equation” summarizes the data relationship? Data set #B - This data can be modeled with a exponential relation. How do you know? What “equation” summarizes the data relationship? 1/20/2016 Integrated Math 10 - Santowski 9 x y x y
Exploring Exponential Equations Data set #C – This data can be modeled with a exponential relation. How do you know? What “equation” summarizes the data relationship? Data set #D - This data can be modeled with a exponential relation. How do you know? What “equation” summarizes the data relationship? 1/20/2016 Integrated Math 10 - Santowski 10 x y x y
Exploring Exponential Equations Data set #E – This data can be modeled with a exponential relation. How do you know? What “equation” summarizes the data relationship? Data set #F - This data can be modeled with a exponential relation. How do you know? What “equation” summarizes the data relationship? 1/20/2016 Integrated Math 10 - Santowski 11 x y x y
1/20/2016 Integrated Math 10 - Santowski 12 Application of Exponential Models
Modeling Example #1 Investment data – Mr. S has invested some money for Andrew’s post- secondary education (not too hopeful for an athletic scholarship for my son!!!!) (a) How can you analyze the numeric data (no graphs) to conclude that the data is exponential i.e how do you know the data is exponential rather than linear? (b) Graph the data on a scatter plot (c) Write an equation to model the data. Define your variables carefully. 1/20/2016 Integrated Math 10 - Santowski 13 Time (years) Value of investment (000’s $)
Modeling Example #2 The following data table shows the relationship between the time (in hours after a rain storm in Manila) and the number of bacteria (#/mL of water) in water samples from the Pasig River: (a) How can you analyze the numeric data (no graphs) to conclude that the data is exponential i.e how do you know the data is exponential rather than linear? (b) Graph the data on a scatter plot (c) Write an equation to model the data. Define your variables carefully. 1/20/2016 Integrated Math 10 - Santowski 14 Time (hrs) # of Bacteria
Modeling Example #3 The value of Mr. S’s car is depreciating over time. I bought the car new in 2002 and the value of my car (in thousands) over the years has been tabulated below: (a) How can you analyze the numeric data (no graphs) to conclude that the data is exponential i.e how do you know the data is exponential rather than linear? (b) Graph the data on a scatter plot (c) Write an equation to model the data. Define your variables carefully. 1/20/2016 Integrated Math 10 - Santowski 15 Year Value
Modeling Example #4 The following data table shows the historic world population since 1950: (a) How can you analyze the numeric data (no graphs) to conclude that the data is exponential i.e how do you know the data is exponential rather than linear? (b) Graph the data on a scatter plot (c) Write an equation to model the data. Define your variables carefully. 1/20/2016 Integrated Math 10 - Santowski 16 Year Pop (in millions)
SUMMARY Write a SINGLE equation that summarizes the data relationships you have investigated this lesson. 1/20/2016 Integrated Math 10 - Santowski 17
1/20/2016 Integrated Math 10 - Santowski 18 SUMMARY Exponential Growth Equations In general, the algebraic model for exponential growth is y = c(a) x where a is referred to as the growth rate (provided that a > 1) and c is the initial amount present and x is the number of increases given the growth rate conditions. All equations in this section are also written in the form y = c(1 + r) x where c is a constant, r is a positive rate of change and 1 + r > 1, and x is the number of increases given the growth rate conditions.
1/20/2016 Integrated Math 10 - Santowski 19 SUMMARY Exponential Decay Equations In general, the algebraic model for exponential decay is y = c(a) x where a is referred to as the decay rate (and a is < 1) and c is the initial amount present. All equations in this section are in the form y = c(1 + r) x or y = ca x, where c is a constant, r is a rate of change (this time negative as we have a decrease so 1 + r < 1), and x is the number of increases given the rate conditions