SlideShare ist ein Scribd-Unternehmen logo
1 von 56
Downloaden Sie, um offline zu lesen
Section	3.4
     Exponential	Growth	and	Decay

                  V63.0121.027, Calculus	I



                      October	27, 2009



Announcements
   Quiz	3	this	week	in	recitation

                                         .   .   .   .   .   .
Outline

  Recall

  The	equation y′ = ky

  Modeling	simple	population	growth

  Modeling	radioactive	decay
    Carbon-14	Dating

  Newton’s	Law	of	Cooling

  Continuously	Compounded	Interest



                                      .   .   .   .   .   .
Derivatives	of	exponential	and	logarithmic	functions




                       y        y′
                       ex       ex
                       ax    (ln a)ax
                                1
                       ln x
                                 x
                               1 1
                      loga x       ·
                             ln a x




                                        .   .   .   .   .   .
Outline

  Recall

  The	equation y′ = ky

  Modeling	simple	population	growth

  Modeling	radioactive	decay
    Carbon-14	Dating

  Newton’s	Law	of	Cooling

  Continuously	Compounded	Interest



                                      .   .   .   .   .   .
Definition
A differential	equation is	an	equation	for	an	unknown	function
which	includes	the	function	and	its	derivatives.




                                           .   .    .   .   .    .
Definition
A differential	equation is	an	equation	for	an	unknown	function
which	includes	the	function	and	its	derivatives.

Example
    Newton’s	Second	Law F = ma is	a	differential	equation,
    where a(t) = x′′ (t).




                                           .   .    .   .    .   .
Definition
A differential	equation is	an	equation	for	an	unknown	function
which	includes	the	function	and	its	derivatives.

Example
    Newton’s	Second	Law F = ma is	a	differential	equation,
    where a(t) = x′′ (t).
    In	a	spring, F(x) = −kx, where x is	displacement	from
    equilibrium	and k is	a	constant. So

                                         k
                   −kx = mx′′ =⇒ x′′ +     = 0.
                                         m




                                           .   .    .   .    .   .
Definition
A differential	equation is	an	equation	for	an	unknown	function
which	includes	the	function	and	its	derivatives.

Example
    Newton’s	Second	Law F = ma is	a	differential	equation,
    where a(t) = x′′ (t).
    In	a	spring, F(x) = −kx, where x is	displacement	from
    equilibrium	and k is	a	constant. So

                                            k
                    −kx = mx′′ =⇒ x′′ +       = 0.
                                            m


    The	most	general	solution	is x(t) = A sin ω t + B cos ω t, where
        √
    ω = k/m.


                                             .    .    .   .    .      .
The	equation y′ = ky



   Example
      Find a solution	to y′ (t) = y(t).
      Find	the most	general solution	to y′ (t) = y(t).




                                               .    .    .   .   .   .
The	equation y′ = ky



   Example
       Find a solution	to y′ (t) = y(t).
       Find	the most	general solution	to y′ (t) = y(t).

   Solution
       A solution	is y(t) = et .




                                                .    .    .   .   .   .
The	equation y′ = ky



   Example
       Find a solution	to y′ (t) = y(t).
       Find	the most	general solution	to y′ (t) = y(t).

   Solution
       A solution	is y(t) = et .
       The	general	solution	is y = Cet , not y = et + C.
   (check	this)




                                                .    .     .   .   .   .
In	general

   Example
      Find	a	solution	to y′ = ky.
      Find	the	general	solution	to y′ = ky.




                                              .   .   .   .   .   .
In	general

   Example
       Find	a	solution	to y′ = ky.
       Find	the	general	solution	to y′ = ky.

   Solution
       y = ekt
       y = Cekt




                                               .   .   .   .   .   .
In	general

   Example
        Find	a	solution	to y′ = ky.
        Find	the	general	solution	to y′ = ky.

   Solution
        y = ekt
        y = Cekt

   Remark
   What	is C? Plug	in t = 0:

                         y(0) = Cek·0 = C · 1 = C,

   so y(0) = y0 , the initial	value of y.
                                                .    .   .   .   .   .
Exponential	Growth


      It	means	the	rate	of	change	(derivative)	is	proportional	to	the
      current	value
      Examples: Natural	population	growth, compounded	interest,
      social	networks




                                               .   .    .    .    .     .
Outline

  Recall

  The	equation y′ = ky

  Modeling	simple	population	growth

  Modeling	radioactive	decay
    Carbon-14	Dating

  Newton’s	Law	of	Cooling

  Continuously	Compounded	Interest



                                      .   .   .   .   .   .
Bacteria



     Since	you	need	bacteria
     to	make	bacteria, the
     amount	of	new	bacteria
     at	any	moment	is
     proportional	to	the	total
     amount	of	bacteria.
     This	means	bacteria
     populations	grow
     exponentially.




                                 .   .   .   .   .   .
Bacteria	Example
  Example
  A colony	of	bacteria	is	grown	under	ideal	conditions	in	a
  laboratory. At	the	end	of	3	hours	there	are	10,000	bacteria. At
  the	end	of	5	hours	there	are	40,000. How	many	bacteria	were
  present	initially?




                                              .    .   .    .   .   .
Bacteria	Example
  Example
  A colony	of	bacteria	is	grown	under	ideal	conditions	in	a
  laboratory. At	the	end	of	3	hours	there	are	10,000	bacteria. At
  the	end	of	5	hours	there	are	40,000. How	many	bacteria	were
  present	initially?

  Solution
  Since y′ = ky for	bacteria, we	have y = y0 ekt . We	have

             10, 000 = y0 ek·3          40, 000 = y0 ek·5




                                               .   .    .    .   .   .
Bacteria	Example
  Example
  A colony	of	bacteria	is	grown	under	ideal	conditions	in	a
  laboratory. At	the	end	of	3	hours	there	are	10,000	bacteria. At
  the	end	of	5	hours	there	are	40,000. How	many	bacteria	were
  present	initially?

  Solution
  Since y′ = ky for	bacteria, we	have y = y0 ekt . We	have

             10, 000 = y0 ek·3           40, 000 = y0 ek·5

  Dividing	the	first	into	the	second	gives
  4 = e2k =⇒ 2k = ln 4 =⇒ k = ln 2. Now	we	have

                     10, 000 = y0 eln 2·3 = y0 · 8

            10, 000
  So y0 =           = 1250.
               8
                                               .     .   .   .   .   .
Could	you	do	that	again	please?

   We	have

                            10, 000 = y0 ek·3
                            40, 000 = y0 ek·5

   Dividing	the	first	into	the	second	gives

                40, 000  y e5k
                        = 0 3k
                10, 000  y0 e
                       4 = e2k
                    ln 4 = ln(e2k ) = 2k
                            ln 4   ln 22   2 ln 2
                       k=        =       =        = ln 2
                             2       2        2


                                                .   .      .   .   .   .
Outline

  Recall

  The	equation y′ = ky

  Modeling	simple	population	growth

  Modeling	radioactive	decay
    Carbon-14	Dating

  Newton’s	Law	of	Cooling

  Continuously	Compounded	Interest



                                      .   .   .   .   .   .
Modeling	radioactive	decay

   Radioactive	decay	occurs	because	many	large	atoms
   spontaneously	give	off	particles.




                                            .   .      .   .   .   .
Modeling	radioactive	decay

   Radioactive	decay	occurs	because	many	large	atoms
   spontaneously	give	off	particles.

  This	means	that	in	a	sample
  of	a	bunch	of	atoms, we	can
  assume	a	certain	percentage
  of	them	will	“go	off”	at	any
  point. (For	instance, if	all
  atom	of	a	certain	radioactive
  element	have	a	20%	chance
  of	decaying	at	any	point,
  then	we	can	expect	in	a
  sample	of	100	that	20	of
  them	will	be	decaying.)


                                            .   .      .   .   .   .
Thus	the	relative	rate	of	decay	is	constant:

                               y′
                                  =k
                               y

where k is negative.




                                               .   .   .   .   .   .
Thus	the	relative	rate	of	decay	is	constant:

                               y′
                                  =k
                               y

where k is negative. So

                      y′ = ky =⇒ y = y0 ekt

again!




                                               .   .   .   .   .   .
Thus	the	relative	rate	of	decay	is	constant:

                               y′
                                  =k
                               y

where k is negative. So

                      y′ = ky =⇒ y = y0 ekt

again!
It’s	customary	to	express	the	relative	rate	of	decay	in	the	units	of
half-life: the	amount	of	time	it	takes	a	pure	sample	to	decay	to
one	which	is	only	half	pure.




                                               .   .    .    .    .    .
Example
The	half-life	of	polonium-210	is	about	138	days. How	much	of	a
100	g	sample	remains	after t years?




                                          .   .   .    .   .     .
Example
The	half-life	of	polonium-210	is	about	138	days. How	much	of	a
100	g	sample	remains	after t years?

Solution
We	have y = y0 ekt , where y0 = y(0) = 100 grams. Then

                                                   365 · ln 2
            50 = 100ek·138/365 =⇒ k = −                       .
                                                     138
Therefore
                            365·ln 2
             y(t) = 100e−     138
                                     t
                                         = 100 · 2−365t/138 .




                                                    .    .      .   .   .   .
Carbon-14	Dating

                   The	ratio	of	carbon-14	to
                   carbon-12	in	an	organism
                   decays	exponentially:

                              p(t) = p0 e−kt .

                   The	half-life	of	carbon-14	is
                   about	5700	years. So	the
                   equation	for p(t) is
                                           ln2
                          p(t) = p0 e− 5700 t

                   Another	way	to	write	this
                   would	be

                         p(t) = p0 2−t/5700

                          .       .    .    .    .   .
Example
Suppose	a	fossil	is	found	where	the	ratio	of	carbon-14	to
carbon-12	is	10%	of	that	in	a	living	organism. How	old	is	the
fossil?




                                           .    .   .    .      .   .
Example
Suppose	a	fossil	is	found	where	the	ratio	of	carbon-14	to
carbon-12	is	10%	of	that	in	a	living	organism. How	old	is	the
fossil?

Solution
We	are	looking	for	the	value	of t for	which

                           p(t)
                                = 0.1
                           p(0)




                                              .   .   .   .     .   .
Example
Suppose	a	fossil	is	found	where	the	ratio	of	carbon-14	to
carbon-12	is	10%	of	that	in	a	living	organism. How	old	is	the
fossil?

Solution
We	are	looking	for	the	value	of t for	which

                           p(t)
                                = 0.1
                           p(0)

From	the	equation	we	have

                         2−t/5700 = 0.1
                          t
                      −        ln 2 = ln 0.1
                        5700
                      ln 0.1
                   t=        · 5700 ≈ 18, 940
                       ln 2

                                              .   .   .   .     .   .
Example
Suppose	a	fossil	is	found	where	the	ratio	of	carbon-14	to
carbon-12	is	10%	of	that	in	a	living	organism. How	old	is	the
fossil?

Solution
We	are	looking	for	the	value	of t for	which

                            p(t)
                                 = 0.1
                            p(0)

From	the	equation	we	have

                         2−t/5700 = 0.1
                          t
                      −        ln 2 = ln 0.1
                        5700
                      ln 0.1
                   t=        · 5700 ≈ 18, 940
                       ln 2
So	the	fossil	is	almost	19,000	years	old.
                                              .   .   .   .     .   .
Outline

  Recall

  The	equation y′ = ky

  Modeling	simple	population	growth

  Modeling	radioactive	decay
    Carbon-14	Dating

  Newton’s	Law	of	Cooling

  Continuously	Compounded	Interest



                                      .   .   .   .   .   .
Newton’s	Law	of	Cooling

     Newton’s	Law	of
     Cooling states	that	the
     rate	of	cooling	of	an
     object	is	proportional	to
     the	temperature
     difference	between	the
     object	and	its
     surroundings.




                                 .   .   .   .   .   .
Newton’s	Law	of	Cooling

     Newton’s	Law	of
     Cooling states	that	the
     rate	of	cooling	of	an
     object	is	proportional	to
     the	temperature
     difference	between	the
     object	and	its
     surroundings.
     This	gives	us	a
     differential	equation	of
     the	form
          dT
             = k (T − T s )
          dt
     (where k < 0 again).

                                 .   .   .   .   .   .
General	Solution	to	NLC problems


  To	solve	this, change	the	variable y(t) = T(t) − Ts . Then y′ = T′
  and k(T − Ts ) = ky. The	equation	now	looks	like

                                dy
                                   = ky
                                dt




                                                .   .    .    .   .    .
General	Solution	to	NLC problems


  To	solve	this, change	the	variable y(t) = T(t) − Ts . Then y′ = T′
  and k(T − Ts ) = ky. The	equation	now	looks	like

                                dy
                                   = ky
                                dt
  which	we	can	solve:

                                y = Cekt
                          T − Ts = Cekt
                          =⇒ T = Cekt + Ts




                                                .   .    .    .   .    .
General	Solution	to	NLC problems


  To	solve	this, change	the	variable y(t) = T(t) − Ts . Then y′ = T′
  and k(T − Ts ) = ky. The	equation	now	looks	like

                                dy
                                   = ky
                                dt
  which	we	can	solve:

                                y = Cekt
                            T − Ts = Cekt
                            =⇒ T = Cekt + Ts

  Here C = y0 = T0 − Ts .



                                                .   .    .    .   .    .
Example
A hard-boiled	egg	at 98◦ C is	put	in	a	sink	of 18◦ C water. After	5
minutes, the	egg’s	temperature	is 38◦ C. Assuming	the	water	has
not	warmed	appreciably, how	much	longer	will	it	take	the	egg	to
reach 20◦ C?




                                             .    .   .    .    .     .
Example
A hard-boiled	egg	at 98◦ C is	put	in	a	sink	of 18◦ C water. After	5
minutes, the	egg’s	temperature	is 38◦ C. Assuming	the	water	has
not	warmed	appreciably, how	much	longer	will	it	take	the	egg	to
reach 20◦ C?

Solution
We	know	that	the	temperature	function	takes	the	form

              T(t) = (T0 − Ts )ekt + Ts = 80ekt + 18

To	find k, plug	in t = 5:

                     38 = T(5) = 80e5k + 18

and	solve	for k.


                                             .    .    .   .    .     .
Finding k


                38 = T(5) = 80e5k + 18
                 20 = 80e5k
                  1
                    = e5k
               ( )4
                1
            ln      = 5k
                4
                        1
              =⇒ k = − ln 4.
                        5




                                   .     .   .   .   .   .
Finding k


                          38 = T(5) = 80e5k + 18
                        20 = 80e5k
                         1
                           = e5k
                      ( )4
                       1
                   ln      = 5k
                       4
                               1
                     =⇒ k = − ln 4.
                               5
   Now	we	need	to	solve
                                      t
                   20 = T(t) = 80e− 5 ln 4 + 18

   for t.
                                             .     .   .   .   .   .
Finding t



                            t
                20 = 80e− 5 ln 4 + 18
                            t
                  2 = 80e− 5 ln 4
                 1       t
                    = e− 5 ln 4
                40
                        t
            − ln 40 = − ln 4
                        5

                       ln 40    5 ln 40
             =⇒ t =    1
                              =         ≈ 13 min
                       5 ln 4     ln 4




                                         .   .     .   .   .   .
Example
A murder	victim	is
discovered	at	midnight	and
the	temperature	of	the	body
is	recorded	as 31 ◦ C. One
hour	later, the	temperature	of
the	body	is 29 ◦ C. Assume
that	the	surrounding	air
temperature	remains
constant	at 21 ◦ C. Calculate
the	victim’s	time	of	death.
(The	“normal”	temperature	of
a	living	human	being	is
approximately 37 ◦ C.)


                                 .   .   .   .   .   .
Solution
    Let	time 0 be	midnight. We	know T0 = 31, Ts = 21, and
    T(1) = 29. We	want	to	know	the t for	which T(t) = 37.




                                         .   .   .   .      .   .
Solution
    Let	time 0 be	midnight. We	know T0 = 31, Ts = 21, and
    T(1) = 29. We	want	to	know	the t for	which T(t) = 37.
    To	find k:

                29 = 10ek·1 + 21 =⇒ k = ln 0.8




                                         .   .   .   .      .   .
Solution
    Let	time 0 be	midnight. We	know T0 = 31, Ts = 21, and
    T(1) = 29. We	want	to	know	the t for	which T(t) = 37.
    To	find k:

                 29 = 10ek·1 + 21 =⇒ k = ln 0.8


    To	find t:

                     37 = 10et·ln(0.8) + 21
                     1.6 = et·ln(0.8)
                           ln(1.6)
                       t=             ≈ −2.10 hr
                           ln(0.8)

    So	the	time	of	death	was	just	before	10:00pm.

                                              .    .   .   .   .   .
Outline

  Recall

  The	equation y′ = ky

  Modeling	simple	population	growth

  Modeling	radioactive	decay
    Carbon-14	Dating

  Newton’s	Law	of	Cooling

  Continuously	Compounded	Interest



                                      .   .   .   .   .   .
Interest

       If	an	account	has	an	compound	interest	rate	of r per	year
       compounded n times, then	an	initial	deposit	of A0 dollars
       becomes                  (     r )nt
                              A0 1 +
                                     n
       after t years.




                                              .   .    .   .   .   .
Interest

       If	an	account	has	an	compound	interest	rate	of r per	year
       compounded n times, then	an	initial	deposit	of A0 dollars
       becomes                  (     r )nt
                              A0 1 +
                                     n
       after t years.
       For	different	amounts	of	compounding, this	will	change. As
       n → ∞, we	get continously	compounded	interest
                                 (    r )nt
                    A(t) = lim A0 1 +       = A0 ert .
                          n→∞         n




                                              .   .      .   .   .   .
Interest

       If	an	account	has	an	compound	interest	rate	of r per	year
       compounded n times, then	an	initial	deposit	of A0 dollars
       becomes                  (     r )nt
                              A0 1 +
                                     n
       after t years.
       For	different	amounts	of	compounding, this	will	change. As
       n → ∞, we	get continously	compounded	interest
                                 (    r )nt
                    A(t) = lim A0 1 +       = A0 ert .
                          n→∞         n


       Thus	dollars	are	like	bacteria.


                                              .   .      .   .   .   .
Example
How	long	does	it	take	an	initial	deposit	of	$100, compounded
continuously, to	double?




                                          .   .    .   .   .   .
Example
How	long	does	it	take	an	initial	deposit	of	$100, compounded
continuously, to	double?

Solution
We	need t such	that A(t) = 200. In	other	words

                                                         ln 2
    200 = 100ert =⇒ 2 = ert =⇒ ln 2 = rt =⇒ t =               .
                                                           r
For	instance, if r = 6% = 0.06, we	have

                  ln 2   0.69   69
             t=        ≈      =    = 11.5 years.
                  0.06   0.06   6




                                          .      .   .     .      .   .
I-banking	interview	tip	of	the	day

                  ln 2
     The	fraction      can
                    r
     also	be	approximated	as
     either	70	or	72	divided
     by	the	percentage	rate
     (as	a	number	between	0
     and	100, not	a	fraction
     between	0	and	1.)
     This	is	sometimes	called
     the rule	of	70 or rule	of
     72.
     72	has	lots	of	factors	so
     it’s	used	more	often.


                                     .   .   .   .   .   .

Weitere ähnliche Inhalte

Was ist angesagt?

FIRST ORDER DIFFERENTIAL EQUATION
 FIRST ORDER DIFFERENTIAL EQUATION FIRST ORDER DIFFERENTIAL EQUATION
FIRST ORDER DIFFERENTIAL EQUATIONAYESHA JAVED
 
First order linear differential equation
First order linear differential equationFirst order linear differential equation
First order linear differential equationNofal Umair
 
Linear differential equation
Linear differential equationLinear differential equation
Linear differential equationPratik Sudra
 
Lesson 11: Limits and Continuity
Lesson 11: Limits and ContinuityLesson 11: Limits and Continuity
Lesson 11: Limits and ContinuityMatthew Leingang
 
Lesson 25: Evaluating Definite Integrals (slides)
Lesson 25: Evaluating Definite Integrals (slides)Lesson 25: Evaluating Definite Integrals (slides)
Lesson 25: Evaluating Definite Integrals (slides)Matthew Leingang
 
APPLICATION OF DEFINITE INTEGRAL
APPLICATION OF DEFINITE INTEGRALAPPLICATION OF DEFINITE INTEGRAL
APPLICATION OF DEFINITE INTEGRALChayanPathak5
 
The chain rule
The chain ruleThe chain rule
The chain ruleJ M
 
3.1 derivative of a function
3.1 derivative of a function3.1 derivative of a function
3.1 derivative of a functionbtmathematics
 
Second derivative test ap calc
Second derivative test ap calcSecond derivative test ap calc
Second derivative test ap calcRon Eick
 
complex numbers 1
complex numbers 1complex numbers 1
complex numbers 1youmarks
 
Partial Differentiation
Partial DifferentiationPartial Differentiation
Partial DifferentiationDeep Dalsania
 

Was ist angesagt? (20)

FIRST ORDER DIFFERENTIAL EQUATION
 FIRST ORDER DIFFERENTIAL EQUATION FIRST ORDER DIFFERENTIAL EQUATION
FIRST ORDER DIFFERENTIAL EQUATION
 
First order linear differential equation
First order linear differential equationFirst order linear differential equation
First order linear differential equation
 
Linear differential equation
Linear differential equationLinear differential equation
Linear differential equation
 
Lesson 11: Limits and Continuity
Lesson 11: Limits and ContinuityLesson 11: Limits and Continuity
Lesson 11: Limits and Continuity
 
Types of function
Types of function Types of function
Types of function
 
Lesson 25: Evaluating Definite Integrals (slides)
Lesson 25: Evaluating Definite Integrals (slides)Lesson 25: Evaluating Definite Integrals (slides)
Lesson 25: Evaluating Definite Integrals (slides)
 
APPLICATION OF DEFINITE INTEGRAL
APPLICATION OF DEFINITE INTEGRALAPPLICATION OF DEFINITE INTEGRAL
APPLICATION OF DEFINITE INTEGRAL
 
Binomial expansion
Binomial expansionBinomial expansion
Binomial expansion
 
The chain rule
The chain ruleThe chain rule
The chain rule
 
3.1 derivative of a function
3.1 derivative of a function3.1 derivative of a function
3.1 derivative of a function
 
Second derivative test ap calc
Second derivative test ap calcSecond derivative test ap calc
Second derivative test ap calc
 
complex numbers 1
complex numbers 1complex numbers 1
complex numbers 1
 
DIFFERENTIATION
DIFFERENTIATIONDIFFERENTIATION
DIFFERENTIATION
 
DIFFERENTIATION
DIFFERENTIATIONDIFFERENTIATION
DIFFERENTIATION
 
Integration Ppt
Integration PptIntegration Ppt
Integration Ppt
 
Limits and continuity
Limits and continuityLimits and continuity
Limits and continuity
 
Partial Differentiation
Partial DifferentiationPartial Differentiation
Partial Differentiation
 
13 05-curl-and-divergence
13 05-curl-and-divergence13 05-curl-and-divergence
13 05-curl-and-divergence
 
Roll's theorem
Roll's theoremRoll's theorem
Roll's theorem
 
Integration by parts
Integration by partsIntegration by parts
Integration by parts
 

Andere mochten auch

Exponential growth and decay
Exponential growth and decayExponential growth and decay
Exponential growth and decayJessica Garcia
 
Exponential Growth & Decay
Exponential Growth & DecayExponential Growth & Decay
Exponential Growth & DecayBitsy Griffin
 
Lesson 15: Exponential Growth and Decay (Section 041 slides)
Lesson 15: Exponential Growth and Decay (Section 041 slides)Lesson 15: Exponential Growth and Decay (Section 041 slides)
Lesson 15: Exponential Growth and Decay (Section 041 slides)Matthew Leingang
 
Families of curves
Families of curvesFamilies of curves
Families of curvesTarun Gehlot
 
Exponential growth and decay
Exponential growth and decayExponential growth and decay
Exponential growth and decaySimon Borgert
 
4 5 Exponential Growth And Decay
4 5 Exponential Growth And Decay4 5 Exponential Growth And Decay
4 5 Exponential Growth And Decaysilvia
 
2) exponential growth and decay
2) exponential growth and decay2) exponential growth and decay
2) exponential growth and decayestelav
 
Lesson 12: Linear Approximation
Lesson 12: Linear ApproximationLesson 12: Linear Approximation
Lesson 12: Linear ApproximationMatthew Leingang
 
Lesson 9: The Product and Quotient Rules
Lesson 9: The Product and Quotient RulesLesson 9: The Product and Quotient Rules
Lesson 9: The Product and Quotient RulesMatthew Leingang
 
Lesson 6: Limits Involving Infinity
Lesson 6: Limits Involving InfinityLesson 6: Limits Involving Infinity
Lesson 6: Limits Involving InfinityMatthew Leingang
 
Lesson 11: Implicit Differentiation
Lesson 11: Implicit DifferentiationLesson 11: Implicit Differentiation
Lesson 11: Implicit DifferentiationMatthew Leingang
 
Lesson 4: Calculating Limits
Lesson 4: Calculating LimitsLesson 4: Calculating Limits
Lesson 4: Calculating LimitsMatthew Leingang
 
Lesson 16: Inverse Trigonometric Functions
Lesson 16: Inverse Trigonometric FunctionsLesson 16: Inverse Trigonometric Functions
Lesson 16: Inverse Trigonometric FunctionsMatthew Leingang
 
Lesson 16: Exponential Growth and Decay
Lesson 16: Exponential Growth and DecayLesson 16: Exponential Growth and Decay
Lesson 16: Exponential Growth and DecayMatthew Leingang
 
Lesson 18: Indeterminate Forms and L'Hôpital's Rule
Lesson 18: Indeterminate Forms and L'Hôpital's RuleLesson 18: Indeterminate Forms and L'Hôpital's Rule
Lesson 18: Indeterminate Forms and L'Hôpital's RuleMatthew Leingang
 
Lesson 16: Derivatives of Logarithmic and Exponential Functions
Lesson 16: Derivatives of Logarithmic and Exponential FunctionsLesson 16: Derivatives of Logarithmic and Exponential Functions
Lesson 16: Derivatives of Logarithmic and Exponential FunctionsMatthew Leingang
 
Lesson 15: Inverse Functions and Logarithms
Lesson 15: Inverse Functions and LogarithmsLesson 15: Inverse Functions and Logarithms
Lesson 15: Inverse Functions and LogarithmsMatthew Leingang
 
Lesson 16: Derivatives of Logarithmic and Exponential Functions
Lesson 16: Derivatives of Logarithmic and Exponential FunctionsLesson 16: Derivatives of Logarithmic and Exponential Functions
Lesson 16: Derivatives of Logarithmic and Exponential FunctionsMatthew Leingang
 

Andere mochten auch (20)

Exponential growth and decay
Exponential growth and decayExponential growth and decay
Exponential growth and decay
 
Exponential Growth & Decay
Exponential Growth & DecayExponential Growth & Decay
Exponential Growth & Decay
 
Lesson 15: Exponential Growth and Decay (Section 041 slides)
Lesson 15: Exponential Growth and Decay (Section 041 slides)Lesson 15: Exponential Growth and Decay (Section 041 slides)
Lesson 15: Exponential Growth and Decay (Section 041 slides)
 
Families of curves
Families of curvesFamilies of curves
Families of curves
 
Exponential growth and decay
Exponential growth and decayExponential growth and decay
Exponential growth and decay
 
4 5 Exponential Growth And Decay
4 5 Exponential Growth And Decay4 5 Exponential Growth And Decay
4 5 Exponential Growth And Decay
 
2) exponential growth and decay
2) exponential growth and decay2) exponential growth and decay
2) exponential growth and decay
 
Lesson 12: Linear Approximation
Lesson 12: Linear ApproximationLesson 12: Linear Approximation
Lesson 12: Linear Approximation
 
Lesson 9: The Product and Quotient Rules
Lesson 9: The Product and Quotient RulesLesson 9: The Product and Quotient Rules
Lesson 9: The Product and Quotient Rules
 
Lesson 6: Limits Involving Infinity
Lesson 6: Limits Involving InfinityLesson 6: Limits Involving Infinity
Lesson 6: Limits Involving Infinity
 
Lesson 5: Continuity
Lesson 5: ContinuityLesson 5: Continuity
Lesson 5: Continuity
 
Lesson 11: Implicit Differentiation
Lesson 11: Implicit DifferentiationLesson 11: Implicit Differentiation
Lesson 11: Implicit Differentiation
 
Lesson 10: The Chain Rule
Lesson 10: The Chain RuleLesson 10: The Chain Rule
Lesson 10: The Chain Rule
 
Lesson 4: Calculating Limits
Lesson 4: Calculating LimitsLesson 4: Calculating Limits
Lesson 4: Calculating Limits
 
Lesson 16: Inverse Trigonometric Functions
Lesson 16: Inverse Trigonometric FunctionsLesson 16: Inverse Trigonometric Functions
Lesson 16: Inverse Trigonometric Functions
 
Lesson 16: Exponential Growth and Decay
Lesson 16: Exponential Growth and DecayLesson 16: Exponential Growth and Decay
Lesson 16: Exponential Growth and Decay
 
Lesson 18: Indeterminate Forms and L'Hôpital's Rule
Lesson 18: Indeterminate Forms and L'Hôpital's RuleLesson 18: Indeterminate Forms and L'Hôpital's Rule
Lesson 18: Indeterminate Forms and L'Hôpital's Rule
 
Lesson 16: Derivatives of Logarithmic and Exponential Functions
Lesson 16: Derivatives of Logarithmic and Exponential FunctionsLesson 16: Derivatives of Logarithmic and Exponential Functions
Lesson 16: Derivatives of Logarithmic and Exponential Functions
 
Lesson 15: Inverse Functions and Logarithms
Lesson 15: Inverse Functions and LogarithmsLesson 15: Inverse Functions and Logarithms
Lesson 15: Inverse Functions and Logarithms
 
Lesson 16: Derivatives of Logarithmic and Exponential Functions
Lesson 16: Derivatives of Logarithmic and Exponential FunctionsLesson 16: Derivatives of Logarithmic and Exponential Functions
Lesson 16: Derivatives of Logarithmic and Exponential Functions
 

Ähnlich wie Lesson 16: Exponential Growth and Decay

Lesson 14: Exponential Growth and Decay
Lesson 14: Exponential Growth and DecayLesson 14: Exponential Growth and Decay
Lesson 14: Exponential Growth and DecayMatthew Leingang
 
Lesson 15: Exponential Growth and Decay (slides)
Lesson 15: Exponential Growth and Decay (slides)Lesson 15: Exponential Growth and Decay (slides)
Lesson 15: Exponential Growth and Decay (slides)Matthew Leingang
 
Lesson 15: Exponential Growth and Decay (slides)
Lesson 15: Exponential Growth and Decay (slides)Lesson 15: Exponential Growth and Decay (slides)
Lesson 15: Exponential Growth and Decay (slides)Mel Anthony Pepito
 
Lesson 15: Exponential Growth and Decay (handout)
Lesson 15: Exponential Growth and Decay (handout)Lesson 15: Exponential Growth and Decay (handout)
Lesson 15: Exponential Growth and Decay (handout)Matthew Leingang
 
Lesson 15: Exponential Growth and Decay (Section 041 slides)
Lesson 15: Exponential Growth and Decay (Section 041 slides)Lesson 15: Exponential Growth and Decay (Section 041 slides)
Lesson 15: Exponential Growth and Decay (Section 041 slides)Mel Anthony Pepito
 
Lesson15 -exponential_growth_and_decay_021_slides
Lesson15  -exponential_growth_and_decay_021_slidesLesson15  -exponential_growth_and_decay_021_slides
Lesson15 -exponential_growth_and_decay_021_slidesMatthew Leingang
 
Lesson 15: Exponential Growth and Decay (Section 021 slides)
Lesson 15: Exponential Growth and Decay (Section 021 slides)Lesson 15: Exponential Growth and Decay (Section 021 slides)
Lesson 15: Exponential Growth and Decay (Section 021 slides)Mel Anthony Pepito
 
Lesson15 -exponential_growth_and_decay_021_slides
Lesson15 -exponential_growth_and_decay_021_slidesLesson15 -exponential_growth_and_decay_021_slides
Lesson15 -exponential_growth_and_decay_021_slidesMel Anthony Pepito
 
Bath_IMI_Summer_Project
Bath_IMI_Summer_ProjectBath_IMI_Summer_Project
Bath_IMI_Summer_ProjectJosh Young
 
Lesson 31: Evaluating Definite Integrals
Lesson 31: Evaluating Definite IntegralsLesson 31: Evaluating Definite Integrals
Lesson 31: Evaluating Definite IntegralsMatthew Leingang
 
NMR Spectroscopy
NMR SpectroscopyNMR Spectroscopy
NMR Spectroscopyclayqn88
 
Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)
Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)
Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)Matthew Leingang
 
Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)
Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)
Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)Mel Anthony Pepito
 
5.8 Modeling Using Variation
5.8 Modeling Using Variation5.8 Modeling Using Variation
5.8 Modeling Using Variationsmiller5
 
Advanced Algebra 2.1&2.2
Advanced Algebra 2.1&2.2Advanced Algebra 2.1&2.2
Advanced Algebra 2.1&2.2sfulkerson
 
Lesson 16 The Spectral Theorem and Applications
Lesson 16  The Spectral Theorem and ApplicationsLesson 16  The Spectral Theorem and Applications
Lesson 16 The Spectral Theorem and ApplicationsMatthew Leingang
 
Lesson 27: Integration by Substitution (Section 4 version)
Lesson 27: Integration by Substitution (Section 4 version)Lesson 27: Integration by Substitution (Section 4 version)
Lesson 27: Integration by Substitution (Section 4 version)Matthew Leingang
 

Ähnlich wie Lesson 16: Exponential Growth and Decay (20)

Lesson 14: Exponential Growth and Decay
Lesson 14: Exponential Growth and DecayLesson 14: Exponential Growth and Decay
Lesson 14: Exponential Growth and Decay
 
Lesson 15: Exponential Growth and Decay (slides)
Lesson 15: Exponential Growth and Decay (slides)Lesson 15: Exponential Growth and Decay (slides)
Lesson 15: Exponential Growth and Decay (slides)
 
Lesson 15: Exponential Growth and Decay (slides)
Lesson 15: Exponential Growth and Decay (slides)Lesson 15: Exponential Growth and Decay (slides)
Lesson 15: Exponential Growth and Decay (slides)
 
Lesson 15: Exponential Growth and Decay (handout)
Lesson 15: Exponential Growth and Decay (handout)Lesson 15: Exponential Growth and Decay (handout)
Lesson 15: Exponential Growth and Decay (handout)
 
Newton
NewtonNewton
Newton
 
Lesson 15: Exponential Growth and Decay (Section 041 slides)
Lesson 15: Exponential Growth and Decay (Section 041 slides)Lesson 15: Exponential Growth and Decay (Section 041 slides)
Lesson 15: Exponential Growth and Decay (Section 041 slides)
 
Lesson15 -exponential_growth_and_decay_021_slides
Lesson15  -exponential_growth_and_decay_021_slidesLesson15  -exponential_growth_and_decay_021_slides
Lesson15 -exponential_growth_and_decay_021_slides
 
Lesson 15: Exponential Growth and Decay (Section 021 slides)
Lesson 15: Exponential Growth and Decay (Section 021 slides)Lesson 15: Exponential Growth and Decay (Section 021 slides)
Lesson 15: Exponential Growth and Decay (Section 021 slides)
 
Lesson15 -exponential_growth_and_decay_021_slides
Lesson15 -exponential_growth_and_decay_021_slidesLesson15 -exponential_growth_and_decay_021_slides
Lesson15 -exponential_growth_and_decay_021_slides
 
Chapter 3 (maths 3)
Chapter 3 (maths 3)Chapter 3 (maths 3)
Chapter 3 (maths 3)
 
Bath_IMI_Summer_Project
Bath_IMI_Summer_ProjectBath_IMI_Summer_Project
Bath_IMI_Summer_Project
 
Lesson 31: Evaluating Definite Integrals
Lesson 31: Evaluating Definite IntegralsLesson 31: Evaluating Definite Integrals
Lesson 31: Evaluating Definite Integrals
 
NMR Spectroscopy
NMR SpectroscopyNMR Spectroscopy
NMR Spectroscopy
 
Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)
Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)
Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)
 
Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)
Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)
Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)
 
5.8 Modeling Using Variation
5.8 Modeling Using Variation5.8 Modeling Using Variation
5.8 Modeling Using Variation
 
Advanced Algebra 2.1&2.2
Advanced Algebra 2.1&2.2Advanced Algebra 2.1&2.2
Advanced Algebra 2.1&2.2
 
Lesson 16 The Spectral Theorem and Applications
Lesson 16  The Spectral Theorem and ApplicationsLesson 16  The Spectral Theorem and Applications
Lesson 16 The Spectral Theorem and Applications
 
Direct variation
Direct variationDirect variation
Direct variation
 
Lesson 27: Integration by Substitution (Section 4 version)
Lesson 27: Integration by Substitution (Section 4 version)Lesson 27: Integration by Substitution (Section 4 version)
Lesson 27: Integration by Substitution (Section 4 version)
 

Mehr von Matthew Leingang

Streamlining assessment, feedback, and archival with auto-multiple-choice
Streamlining assessment, feedback, and archival with auto-multiple-choiceStreamlining assessment, feedback, and archival with auto-multiple-choice
Streamlining assessment, feedback, and archival with auto-multiple-choiceMatthew Leingang
 
Electronic Grading of Paper Assessments
Electronic Grading of Paper AssessmentsElectronic Grading of Paper Assessments
Electronic Grading of Paper AssessmentsMatthew Leingang
 
Lesson 27: Integration by Substitution (slides)
Lesson 27: Integration by Substitution (slides)Lesson 27: Integration by Substitution (slides)
Lesson 27: Integration by Substitution (slides)Matthew Leingang
 
Lesson 26: The Fundamental Theorem of Calculus (slides)
Lesson 26: The Fundamental Theorem of Calculus (slides)Lesson 26: The Fundamental Theorem of Calculus (slides)
Lesson 26: The Fundamental Theorem of Calculus (slides)Matthew Leingang
 
Lesson 26: The Fundamental Theorem of Calculus (slides)
Lesson 26: The Fundamental Theorem of Calculus (slides)Lesson 26: The Fundamental Theorem of Calculus (slides)
Lesson 26: The Fundamental Theorem of Calculus (slides)Matthew Leingang
 
Lesson 27: Integration by Substitution (handout)
Lesson 27: Integration by Substitution (handout)Lesson 27: Integration by Substitution (handout)
Lesson 27: Integration by Substitution (handout)Matthew Leingang
 
Lesson 26: The Fundamental Theorem of Calculus (handout)
Lesson 26: The Fundamental Theorem of Calculus (handout)Lesson 26: The Fundamental Theorem of Calculus (handout)
Lesson 26: The Fundamental Theorem of Calculus (handout)Matthew Leingang
 
Lesson 25: Evaluating Definite Integrals (handout)
Lesson 25: Evaluating Definite Integrals (handout)Lesson 25: Evaluating Definite Integrals (handout)
Lesson 25: Evaluating Definite Integrals (handout)Matthew Leingang
 
Lesson 24: Areas and Distances, The Definite Integral (handout)
Lesson 24: Areas and Distances, The Definite Integral (handout)Lesson 24: Areas and Distances, The Definite Integral (handout)
Lesson 24: Areas and Distances, The Definite Integral (handout)Matthew Leingang
 
Lesson 24: Areas and Distances, The Definite Integral (slides)
Lesson 24: Areas and Distances, The Definite Integral (slides)Lesson 24: Areas and Distances, The Definite Integral (slides)
Lesson 24: Areas and Distances, The Definite Integral (slides)Matthew Leingang
 
Lesson 23: Antiderivatives (slides)
Lesson 23: Antiderivatives (slides)Lesson 23: Antiderivatives (slides)
Lesson 23: Antiderivatives (slides)Matthew Leingang
 
Lesson 23: Antiderivatives (slides)
Lesson 23: Antiderivatives (slides)Lesson 23: Antiderivatives (slides)
Lesson 23: Antiderivatives (slides)Matthew Leingang
 
Lesson 22: Optimization Problems (slides)
Lesson 22: Optimization Problems (slides)Lesson 22: Optimization Problems (slides)
Lesson 22: Optimization Problems (slides)Matthew Leingang
 
Lesson 22: Optimization Problems (handout)
Lesson 22: Optimization Problems (handout)Lesson 22: Optimization Problems (handout)
Lesson 22: Optimization Problems (handout)Matthew Leingang
 
Lesson 21: Curve Sketching (slides)
Lesson 21: Curve Sketching (slides)Lesson 21: Curve Sketching (slides)
Lesson 21: Curve Sketching (slides)Matthew Leingang
 
Lesson 21: Curve Sketching (handout)
Lesson 21: Curve Sketching (handout)Lesson 21: Curve Sketching (handout)
Lesson 21: Curve Sketching (handout)Matthew Leingang
 
Lesson 20: Derivatives and the Shapes of Curves (slides)
Lesson 20: Derivatives and the Shapes of Curves (slides)Lesson 20: Derivatives and the Shapes of Curves (slides)
Lesson 20: Derivatives and the Shapes of Curves (slides)Matthew Leingang
 
Lesson 20: Derivatives and the Shapes of Curves (handout)
Lesson 20: Derivatives and the Shapes of Curves (handout)Lesson 20: Derivatives and the Shapes of Curves (handout)
Lesson 20: Derivatives and the Shapes of Curves (handout)Matthew Leingang
 
Lesson 19: The Mean Value Theorem (slides)
Lesson 19: The Mean Value Theorem (slides)Lesson 19: The Mean Value Theorem (slides)
Lesson 19: The Mean Value Theorem (slides)Matthew Leingang
 

Mehr von Matthew Leingang (20)

Making Lesson Plans
Making Lesson PlansMaking Lesson Plans
Making Lesson Plans
 
Streamlining assessment, feedback, and archival with auto-multiple-choice
Streamlining assessment, feedback, and archival with auto-multiple-choiceStreamlining assessment, feedback, and archival with auto-multiple-choice
Streamlining assessment, feedback, and archival with auto-multiple-choice
 
Electronic Grading of Paper Assessments
Electronic Grading of Paper AssessmentsElectronic Grading of Paper Assessments
Electronic Grading of Paper Assessments
 
Lesson 27: Integration by Substitution (slides)
Lesson 27: Integration by Substitution (slides)Lesson 27: Integration by Substitution (slides)
Lesson 27: Integration by Substitution (slides)
 
Lesson 26: The Fundamental Theorem of Calculus (slides)
Lesson 26: The Fundamental Theorem of Calculus (slides)Lesson 26: The Fundamental Theorem of Calculus (slides)
Lesson 26: The Fundamental Theorem of Calculus (slides)
 
Lesson 26: The Fundamental Theorem of Calculus (slides)
Lesson 26: The Fundamental Theorem of Calculus (slides)Lesson 26: The Fundamental Theorem of Calculus (slides)
Lesson 26: The Fundamental Theorem of Calculus (slides)
 
Lesson 27: Integration by Substitution (handout)
Lesson 27: Integration by Substitution (handout)Lesson 27: Integration by Substitution (handout)
Lesson 27: Integration by Substitution (handout)
 
Lesson 26: The Fundamental Theorem of Calculus (handout)
Lesson 26: The Fundamental Theorem of Calculus (handout)Lesson 26: The Fundamental Theorem of Calculus (handout)
Lesson 26: The Fundamental Theorem of Calculus (handout)
 
Lesson 25: Evaluating Definite Integrals (handout)
Lesson 25: Evaluating Definite Integrals (handout)Lesson 25: Evaluating Definite Integrals (handout)
Lesson 25: Evaluating Definite Integrals (handout)
 
Lesson 24: Areas and Distances, The Definite Integral (handout)
Lesson 24: Areas and Distances, The Definite Integral (handout)Lesson 24: Areas and Distances, The Definite Integral (handout)
Lesson 24: Areas and Distances, The Definite Integral (handout)
 
Lesson 24: Areas and Distances, The Definite Integral (slides)
Lesson 24: Areas and Distances, The Definite Integral (slides)Lesson 24: Areas and Distances, The Definite Integral (slides)
Lesson 24: Areas and Distances, The Definite Integral (slides)
 
Lesson 23: Antiderivatives (slides)
Lesson 23: Antiderivatives (slides)Lesson 23: Antiderivatives (slides)
Lesson 23: Antiderivatives (slides)
 
Lesson 23: Antiderivatives (slides)
Lesson 23: Antiderivatives (slides)Lesson 23: Antiderivatives (slides)
Lesson 23: Antiderivatives (slides)
 
Lesson 22: Optimization Problems (slides)
Lesson 22: Optimization Problems (slides)Lesson 22: Optimization Problems (slides)
Lesson 22: Optimization Problems (slides)
 
Lesson 22: Optimization Problems (handout)
Lesson 22: Optimization Problems (handout)Lesson 22: Optimization Problems (handout)
Lesson 22: Optimization Problems (handout)
 
Lesson 21: Curve Sketching (slides)
Lesson 21: Curve Sketching (slides)Lesson 21: Curve Sketching (slides)
Lesson 21: Curve Sketching (slides)
 
Lesson 21: Curve Sketching (handout)
Lesson 21: Curve Sketching (handout)Lesson 21: Curve Sketching (handout)
Lesson 21: Curve Sketching (handout)
 
Lesson 20: Derivatives and the Shapes of Curves (slides)
Lesson 20: Derivatives and the Shapes of Curves (slides)Lesson 20: Derivatives and the Shapes of Curves (slides)
Lesson 20: Derivatives and the Shapes of Curves (slides)
 
Lesson 20: Derivatives and the Shapes of Curves (handout)
Lesson 20: Derivatives and the Shapes of Curves (handout)Lesson 20: Derivatives and the Shapes of Curves (handout)
Lesson 20: Derivatives and the Shapes of Curves (handout)
 
Lesson 19: The Mean Value Theorem (slides)
Lesson 19: The Mean Value Theorem (slides)Lesson 19: The Mean Value Theorem (slides)
Lesson 19: The Mean Value Theorem (slides)
 

Kürzlich hochgeladen

Choosing the Right CBSE School A Comprehensive Guide for Parents
Choosing the Right CBSE School A Comprehensive Guide for ParentsChoosing the Right CBSE School A Comprehensive Guide for Parents
Choosing the Right CBSE School A Comprehensive Guide for Parentsnavabharathschool99
 
Dust Of Snow By Robert Frost Class-X English CBSE
Dust Of Snow By Robert Frost Class-X English CBSEDust Of Snow By Robert Frost Class-X English CBSE
Dust Of Snow By Robert Frost Class-X English CBSEaurabinda banchhor
 
Influencing policy (training slides from Fast Track Impact)
Influencing policy (training slides from Fast Track Impact)Influencing policy (training slides from Fast Track Impact)
Influencing policy (training slides from Fast Track Impact)Mark Reed
 
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17Celine George
 
4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptx4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptxmary850239
 
Congestive Cardiac Failure..presentation
Congestive Cardiac Failure..presentationCongestive Cardiac Failure..presentation
Congestive Cardiac Failure..presentationdeepaannamalai16
 
Daily Lesson Plan in Mathematics Quarter 4
Daily Lesson Plan in Mathematics Quarter 4Daily Lesson Plan in Mathematics Quarter 4
Daily Lesson Plan in Mathematics Quarter 4JOYLYNSAMANIEGO
 
4.16.24 21st Century Movements for Black Lives.pptx
4.16.24 21st Century Movements for Black Lives.pptx4.16.24 21st Century Movements for Black Lives.pptx
4.16.24 21st Century Movements for Black Lives.pptxmary850239
 
How to do quick user assign in kanban in Odoo 17 ERP
How to do quick user assign in kanban in Odoo 17 ERPHow to do quick user assign in kanban in Odoo 17 ERP
How to do quick user assign in kanban in Odoo 17 ERPCeline George
 
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptxMULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptxAnupkumar Sharma
 
ENG 5 Q4 WEEk 1 DAY 1 Restate sentences heard in one’s own words. Use appropr...
ENG 5 Q4 WEEk 1 DAY 1 Restate sentences heard in one’s own words. Use appropr...ENG 5 Q4 WEEk 1 DAY 1 Restate sentences heard in one’s own words. Use appropr...
ENG 5 Q4 WEEk 1 DAY 1 Restate sentences heard in one’s own words. Use appropr...JojoEDelaCruz
 
AUDIENCE THEORY -CULTIVATION THEORY - GERBNER.pptx
AUDIENCE THEORY -CULTIVATION THEORY -  GERBNER.pptxAUDIENCE THEORY -CULTIVATION THEORY -  GERBNER.pptx
AUDIENCE THEORY -CULTIVATION THEORY - GERBNER.pptxiammrhaywood
 
Expanded definition: technical and operational
Expanded definition: technical and operationalExpanded definition: technical and operational
Expanded definition: technical and operationalssuser3e220a
 
Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Celine George
 
Oppenheimer Film Discussion for Philosophy and Film
Oppenheimer Film Discussion for Philosophy and FilmOppenheimer Film Discussion for Philosophy and Film
Oppenheimer Film Discussion for Philosophy and FilmStan Meyer
 
Concurrency Control in Database Management system
Concurrency Control in Database Management systemConcurrency Control in Database Management system
Concurrency Control in Database Management systemChristalin Nelson
 

Kürzlich hochgeladen (20)

Choosing the Right CBSE School A Comprehensive Guide for Parents
Choosing the Right CBSE School A Comprehensive Guide for ParentsChoosing the Right CBSE School A Comprehensive Guide for Parents
Choosing the Right CBSE School A Comprehensive Guide for Parents
 
Dust Of Snow By Robert Frost Class-X English CBSE
Dust Of Snow By Robert Frost Class-X English CBSEDust Of Snow By Robert Frost Class-X English CBSE
Dust Of Snow By Robert Frost Class-X English CBSE
 
Influencing policy (training slides from Fast Track Impact)
Influencing policy (training slides from Fast Track Impact)Influencing policy (training slides from Fast Track Impact)
Influencing policy (training slides from Fast Track Impact)
 
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
 
LEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptx
LEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptxLEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptx
LEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptx
 
4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptx4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptx
 
Congestive Cardiac Failure..presentation
Congestive Cardiac Failure..presentationCongestive Cardiac Failure..presentation
Congestive Cardiac Failure..presentation
 
YOUVE_GOT_EMAIL_PRELIMS_EL_DORADO_2024.pptx
YOUVE_GOT_EMAIL_PRELIMS_EL_DORADO_2024.pptxYOUVE_GOT_EMAIL_PRELIMS_EL_DORADO_2024.pptx
YOUVE_GOT_EMAIL_PRELIMS_EL_DORADO_2024.pptx
 
INCLUSIVE EDUCATION PRACTICES FOR TEACHERS AND TRAINERS.pptx
INCLUSIVE EDUCATION PRACTICES FOR TEACHERS AND TRAINERS.pptxINCLUSIVE EDUCATION PRACTICES FOR TEACHERS AND TRAINERS.pptx
INCLUSIVE EDUCATION PRACTICES FOR TEACHERS AND TRAINERS.pptx
 
Daily Lesson Plan in Mathematics Quarter 4
Daily Lesson Plan in Mathematics Quarter 4Daily Lesson Plan in Mathematics Quarter 4
Daily Lesson Plan in Mathematics Quarter 4
 
4.16.24 21st Century Movements for Black Lives.pptx
4.16.24 21st Century Movements for Black Lives.pptx4.16.24 21st Century Movements for Black Lives.pptx
4.16.24 21st Century Movements for Black Lives.pptx
 
How to do quick user assign in kanban in Odoo 17 ERP
How to do quick user assign in kanban in Odoo 17 ERPHow to do quick user assign in kanban in Odoo 17 ERP
How to do quick user assign in kanban in Odoo 17 ERP
 
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptxMULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
 
ENG 5 Q4 WEEk 1 DAY 1 Restate sentences heard in one’s own words. Use appropr...
ENG 5 Q4 WEEk 1 DAY 1 Restate sentences heard in one’s own words. Use appropr...ENG 5 Q4 WEEk 1 DAY 1 Restate sentences heard in one’s own words. Use appropr...
ENG 5 Q4 WEEk 1 DAY 1 Restate sentences heard in one’s own words. Use appropr...
 
AUDIENCE THEORY -CULTIVATION THEORY - GERBNER.pptx
AUDIENCE THEORY -CULTIVATION THEORY -  GERBNER.pptxAUDIENCE THEORY -CULTIVATION THEORY -  GERBNER.pptx
AUDIENCE THEORY -CULTIVATION THEORY - GERBNER.pptx
 
Expanded definition: technical and operational
Expanded definition: technical and operationalExpanded definition: technical and operational
Expanded definition: technical and operational
 
Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17
 
Oppenheimer Film Discussion for Philosophy and Film
Oppenheimer Film Discussion for Philosophy and FilmOppenheimer Film Discussion for Philosophy and Film
Oppenheimer Film Discussion for Philosophy and Film
 
Concurrency Control in Database Management system
Concurrency Control in Database Management systemConcurrency Control in Database Management system
Concurrency Control in Database Management system
 
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptxYOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
 

Lesson 16: Exponential Growth and Decay