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Math 3B: Lecture 2 Noah White September 26, 2016 Last time Last - PowerPoint PPT Presentation

Math 3B: Lecture 2 Noah White September 26, 2016 Last time Last time, we spoke about The syllabus Last time Last time, we spoke about The syllabus Problem sets, homework, and quizzes Last time Last time, we spoke about The


  1. Math 3B: Lecture 2 Noah White September 26, 2016

  2. Last time Last time, we spoke about • The syllabus

  3. Last time Last time, we spoke about • The syllabus • Problem sets, homework, and quizzes

  4. Last time Last time, we spoke about • The syllabus • Problem sets, homework, and quizzes • Piazza

  5. Last time Last time, we spoke about • The syllabus • Problem sets, homework, and quizzes • Piazza • Differentiation of common functions

  6. Last time Last time, we spoke about • The syllabus • Problem sets, homework, and quizzes • Piazza • Differentiation of common functions • Product rule

  7. Last time Last time, we spoke about • The syllabus • Problem sets, homework, and quizzes • Piazza • Differentiation of common functions • Product rule • Chain rule

  8. Quiz tomorrow • First quiz tomorrow and Thursday.

  9. Quiz tomorrow • First quiz tomorrow and Thursday. • Have a look at the graphing questions!

  10. Graphing using calculus: Why? I think this is a common (and fair) question students have when they see this topic. Why learn to sketch graphs when we have computers that do it so well?

  11. Graphing using calculus: Why? I think this is a common (and fair) question students have when they see this topic. Why learn to sketch graphs when we have computers that do it so well? • Building intuition

  12. Graphing using calculus: Why? I think this is a common (and fair) question students have when they see this topic. Why learn to sketch graphs when we have computers that do it so well? • Building intuition • Understand functions qualitatively

  13. Graphing using calculus: Why? I think this is a common (and fair) question students have when they see this topic. Why learn to sketch graphs when we have computers that do it so well? • Building intuition • Understand functions qualitatively • Better understanding of derivatives

  14. Building intuition Here is an example where a good understanding of a functions behaviour is useful:

  15. Building intuition Here is an example where a good understanding of a functions behaviour is useful: You are a biologist studying the population of a species of fish recently introduced to a new ecosystem. Currently they exist in small number, but you want to model their poputation over time. You know the population should increase quickly and then stabalise. What functions would make good candidates for a population model?

  16. Building intuition Here is an example where a good understanding of a functions behaviour is useful: You are a biologist studying the population of a species of fish recently introduced to a new ecosystem. Currently they exist in small number, but you want to model their poputation over time. You know the population should increase quickly and then stabalise. What functions would make good candidates for a population model? • P ( t ) = t ln t t − 1

  17. Building intuition Here is an example where a good understanding of a functions behaviour is useful: You are a biologist studying the population of a species of fish recently introduced to a new ecosystem. Currently they exist in small number, but you want to model their poputation over time. You know the population should increase quickly and then stabalise. What functions would make good candidates for a population model? • P ( t ) = t ln t t − 1 • P ( t ) = Mt t + 1 for some large number M

  18. Building intuition Here is an example where a good understanding of a functions behaviour is useful: You are a biologist studying the population of a species of fish recently introduced to a new ecosystem. Currently they exist in small number, but you want to model their poputation over time. You know the population should increase quickly and then stabalise. What functions would make good candidates for a population model? • P ( t ) = t ln t t − 1 • P ( t ) = Mt t + 1 for some large number M Mt • P ( t ) = t + e t

  19. The ingredients In order to sketch a function accurately we need a few ingredients

  20. The ingredients In order to sketch a function accurately we need a few ingredients • The x and y intercepts

  21. The ingredients In order to sketch a function accurately we need a few ingredients • The x and y intercepts • Horizontal asymptotes

  22. The ingredients In order to sketch a function accurately we need a few ingredients • The x and y intercepts • Horizontal asymptotes • Vertical asymptotes

  23. The ingredients In order to sketch a function accurately we need a few ingredients • The x and y intercepts • Horizontal asymptotes • Vertical asymptotes • Slanted asymptotes

  24. The ingredients In order to sketch a function accurately we need a few ingredients • The x and y intercepts • Horizontal asymptotes • Vertical asymptotes • Slanted asymptotes • The regions of increase/decrease of the first derivative

  25. The ingredients In order to sketch a function accurately we need a few ingredients • The x and y intercepts • Horizontal asymptotes • Vertical asymptotes • Slanted asymptotes • The regions of increase/decrease of the first derivative • The regions of increase/decrease of the second derivative

  26. Asymptotes An asmptote is a line which the function approches. Some examples:

  27. Asymptotes

  28. Asymptotes

  29. Finding horizontal asymptotes These are the easiest asymptotes to find. Suppose you have a function f ( x )

  30. Finding horizontal asymptotes These are the easiest asymptotes to find. Suppose you have a function f ( x ) • Calculate lim x →∞ f ( x )

  31. Finding horizontal asymptotes These are the easiest asymptotes to find. Suppose you have a function f ( x ) • Calculate lim x →∞ f ( x ) • Calculate x →−∞ f ( x ) lim

  32. Finding horizontal asymptotes These are the easiest asymptotes to find. Suppose you have a function f ( x ) • Calculate lim x →∞ f ( x ) • Calculate x →−∞ f ( x ) lim Example Say f ( x ) = x − 1 1 + x . In this case x − 1 lim x + 1 = 1 x →±∞

  33. Finding horizontal asymptotes

  34. Finding verticle asymptotes Verticle asymptotes happen when a function "blows up", or goes to infinity as it approches a finite number. I.e. Is there a real number a so that x → a + f ( x ) = ±∞ lim or x → a − f ( x ) = ±∞ lim

  35. Finding verticle asymptotes Verticle asymptotes happen when a function "blows up", or goes to infinity as it approches a finite number. I.e. Is there a real number a so that x → a + f ( x ) = ±∞ lim or x → a − f ( x ) = ±∞ lim Example f ( x ) = x − 1 1 + x , we have x − 1 x − 1 lim 1 + x = −∞ and lim 1 + x = ∞ x →− 1 + x →− 1 −

  36. Finding verticle asymptotes

  37. Finding slanted asymptotes Lets come back to this. . .

  38. The first derivative The first derivative tells us is the function going up or down? y x f ′ ( x ) + + −

  39. The second derivative The second derivative tells us is the function concave up or down? y x f ′′ ( x ) + +

  40. Example time . . . On the board.

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