15 - What is a Logarithm (Log x) Function? (Calculate Logs, Applications, Log Bases) - By Math and Science
Transcript
00:00 | Hello . Welcome back . The title of this lesson | |
00:02 | is called . What is a law algorithm ? Or | |
00:05 | I could re title this thing , logarithms explained or | |
00:08 | understanding algorithms . This is part one of several lessons | |
00:11 | only algorithms . A law algorithm is one of the | |
00:14 | most important functions in all of science in all of | |
00:17 | math . And I know I say this a lot | |
00:18 | but really I'm trying to emphasize when I'm really trying | |
00:21 | to tell you things that are extremely important . And | |
00:23 | you'll run into logarithms in your chemistry classes . You'll | |
00:26 | run into logarithms and all of your physics classes . | |
00:28 | Any engineering class , any math class , you're going | |
00:31 | to run into algorithms . So it's not every day | |
00:33 | I can teach you about a function that's important . | |
00:35 | I remember the very first time I got introduced to | |
00:38 | using algorithm in a chemistry class , I went up | |
00:41 | to the teacher because the ph scale you've probably heard | |
00:44 | of ph and chemistry has long algorithm in its definition | |
00:47 | . It's the negative log a rhythm of hydrogen ions | |
00:50 | in a solution . That's a crazy , complicated sounding | |
00:52 | thing . But basically it's the law algorithm of a | |
00:54 | number . Right ? And so I went to the | |
00:56 | teacher and I said , what does this mean ? | |
00:57 | Law algorithm of hydrogen ? What does log log mean | |
01:00 | ? Right . And she said , well that's a | |
01:01 | button on your calculator . And I love this teacher | |
01:04 | . She's a fantastic teacher . But she didn't understand | |
01:07 | at a fundamental detailed level what algorithm was for her | |
01:10 | ? It was just a button on the calculator to | |
01:12 | calculate things . I want to go beyond that with | |
01:14 | you . I want you to understand what algorithm is | |
01:17 | . I want you to know intuitively why we have | |
01:19 | algorithms and why they naturally fall out of math because | |
01:23 | the knowledge that you gain in this lesson will be | |
01:25 | applied to many , many , many courses down the | |
01:27 | road . All right . So before I get into | |
01:30 | what algorithm is I want to give you a little | |
01:31 | motivation . Just two examples I already mentioned the first | |
01:34 | one . The famous ph scale , acids and bases | |
01:37 | is so fundamental to chemistry . It's a log arrhythmic | |
01:40 | scale . So long algorithms come into play anytime you | |
01:42 | calculate anything to do with ph concentrations in chemistry . | |
01:46 | Right . Another very famous example Is the Richter scale | |
01:50 | of earthquake energy . You know , you have uh | |
01:53 | we say earthquake was a 6.2 on the Richter scale | |
01:56 | , earthquake was a 7.3 on the Richter scale , | |
01:58 | earthquake was 1.2 on the Richter scale . What does | |
02:01 | that mean ? Well , a Richter scale is a | |
02:03 | log arrhythmic scale . So by the end of this | |
02:05 | lesson , I want you to understand what a log | |
02:07 | is , but also why do we use them for | |
02:08 | these scales ? Why don't we just use numbers ? | |
02:10 | Why do we have to use logs ? So by | |
02:12 | the end of this , you're gonna understand all of | |
02:13 | that . There are many other examples of logarithms . | |
02:17 | I could go on and on an electrical engineering . | |
02:19 | We use them to plot frequency response of amplifiers and | |
02:23 | mechanical systems . There's tons of of uses for logs | |
02:26 | . But for now we want to go and learn | |
02:28 | what a log actually is . So , in a | |
02:30 | nutshell , this is what a log rhythm is . | |
02:33 | A law algorithm is the inverse function of the exponential | |
02:37 | function of an exponential function that we've already learned about | |
02:40 | already told you exponentially are so incredibly important . And | |
02:43 | they are . So , the inverse of those functions | |
02:45 | , which we've already learned in verses in the last | |
02:47 | lessons . The inverse of exponential functions is what we | |
02:50 | call a long algorithm . That's why logs are so | |
02:53 | important because exponential are also so important . And they | |
02:56 | go together like peanut butter and jelly basically . All | |
02:59 | right , So that's so important . I actually want | |
03:00 | to write that down . If you pull anything out | |
03:02 | of this , I want you to pull this a | |
03:04 | log rhythm . Yeah . Is the in verse the | |
03:13 | universe function of an exponential function . I don't always | |
03:25 | write definitions out , but this one is extremely important | |
03:27 | . So I'm gonna keep that in the top . | |
03:29 | It's the inverse function . And if you remember what | |
03:31 | is an inverse function . We already talked about that | |
03:33 | in the last lesson , inverse functions go together like | |
03:36 | peanut butter and jelly because inverse functions can undo each | |
03:39 | other . If I have function number one and function | |
03:42 | number two . And we know that they're in verses | |
03:43 | of each other . If I run a number through | |
03:46 | the function , calculate the answer , take that answer | |
03:49 | and put it through the next function and calculate that | |
03:51 | answer . The number I get out is going to | |
03:53 | be exactly the same as what I started with because | |
03:56 | the inverse function kind of undid or did the opposite | |
03:58 | calculation of what the first function did . So if | |
04:01 | I stick a one onto the input function , get | |
04:04 | the intermediate , run it through the second function , | |
04:06 | I'm going to get a one on the output . | |
04:08 | If I put a two on the input I'll get | |
04:10 | a two on the output of the inverse . If | |
04:12 | I put a negative five on the input and run | |
04:14 | it through both functions , I'll get a negative five | |
04:16 | on the output . Whatever I put it on the | |
04:17 | on the input , I'm going to get it on | |
04:18 | the output because the inverse undies it . And that's | |
04:22 | not a technical word , it's my word but it's | |
04:24 | a good word to use . So we know that | |
04:26 | a log . So you can use the full word | |
04:29 | log rhythm or you could just use the word log | |
04:32 | , can quote undo an exponential . So remember when | |
04:43 | an exponential function as like two to the power of | |
04:45 | X . Or three to the power of X . | |
04:47 | Right ? If we run the number through that exponential | |
04:50 | function take the output and then stick it through the | |
04:52 | same similar longer than the inverse function , we'll get | |
04:55 | exactly the same thing as we started with because it | |
04:57 | does or does the opposite of that exponential function . | |
05:01 | Right ? One of the biggest biggest biggest uses of | |
05:04 | logarithms is we can use to solve exponential what's equations | |
05:18 | . I hate it whenever you look in a book | |
05:20 | and it explains what something is , but you have | |
05:21 | no idea why it's useful or even if it's very | |
05:23 | important , this one's super important because we can use | |
05:27 | logarithms to solve equations that have exponential in them . | |
05:30 | Why ? Because every equation we solve , we always | |
05:33 | have to do the opposite right ? The opposite operation | |
05:36 | to get the variable by itself . If you add | |
05:38 | something to the variable , you might do the opposite | |
05:40 | , you might subtract , that's by the way , | |
05:42 | an inverse kind of operation . If you multiply in | |
05:45 | the equation , then you might have to divide to | |
05:47 | get X by itself . If you have a square | |
05:49 | , you might do the opposite the square root , | |
05:51 | right ? We've been doing this forever , right ? | |
05:54 | But now that we have no when an exponential function | |
05:56 | is , we might often have to do the opposite | |
05:58 | of that thing to get the variable by itself . | |
06:00 | The opposite is going to be what we call the | |
06:02 | law algorithm . So that's why logs , one of | |
06:05 | the reasons why logs are so important . Now , | |
06:07 | here's our roadmap . I'm gonna write down the definition | |
06:09 | of algorithm , we're gonna work a few very simple | |
06:12 | problems so you know how to handle it . And | |
06:14 | then we're gonna draw some grass to show you that | |
06:16 | the inverse of an exponential really is the algorithm and | |
06:19 | what the graph of algorithm looks like . And then | |
06:21 | at the end of the lesson , I'm gonna go | |
06:23 | into a lot more detail about why we use logarithms | |
06:26 | in the Richter scale and ph and some other applications | |
06:29 | because I want you to understand why we care because | |
06:32 | that's really the point of this thing . So here | |
06:34 | we have enough space . Let's go ahead and write | |
06:36 | down the definition of the law algorithm . So here's | |
06:39 | what a log rhythm is . Al algorithm is , | |
06:44 | the following thing . And I know it's a mathematical | |
06:46 | were definition . I'm gonna make it very clear for | |
06:48 | you if the number B . This is a letter | |
06:52 | , but we're going to call it a number B | |
06:54 | . And the number in are positive numbers with B | |
07:04 | not being able to one because B is going to | |
07:06 | end up becoming the base of the law algorithm . | |
07:08 | And we already know that the base of an exponential | |
07:10 | can't be one . Because we talked about if you | |
07:12 | have one as a base , you don't have an | |
07:13 | exponential function anymore . But anyway , if we have | |
07:16 | these two numbers be an end , they're both positive | |
07:18 | , but they can't be equal to one . They | |
07:19 | can't be equal to one . Then we say that | |
07:22 | the law algorithm using the base B of the number | |
07:27 | N is equal to K . Right ? And this | |
07:31 | is if well let's do it like this if and | |
07:36 | only if fucking spell only if and only if B | |
07:43 | to the power of K is equal to in . | |
07:46 | So here is the definition of the law algorithm . | |
07:48 | gonna leave it on the board because well , reference | |
07:50 | it a lot . I know it doesn't make a | |
07:51 | lot of sense when you see all this jibber jabber | |
07:54 | everywhere , but I'm gonna make it very clear . | |
07:56 | What I want you to understand first of all is | |
07:58 | that here is kind of a relation that involves this | |
08:01 | algorithm . I want you first to understand that the | |
08:03 | law algorithm has a base here , we put the | |
08:05 | letter B there , but in real life they're not | |
08:07 | letters , the basis of logarithms are just like the | |
08:10 | basis of exponentials for an exponential . Remember the base | |
08:13 | was the number on the bottom two to the power | |
08:14 | of X . The base was to 10 to the | |
08:17 | power of X . The base was 10 five to | |
08:19 | the power of X . That's an exponential . The | |
08:21 | base was five . So for logarithms we have bases | |
08:24 | also . So you might have log rhythm with a | |
08:26 | base two logarithms . With the base five law algorithm | |
08:28 | with a base 10 . Why do you have to | |
08:30 | have basis for logarithms ? Well , it's because it's | |
08:33 | an inverse of the exponential function . So of course | |
08:35 | if the exponential has a has a base to determine | |
08:38 | the shape and if I'm just reflecting that graph over | |
08:41 | to find its inverse , that's what an inverse is | |
08:43 | . Then the inverse , which is the log rhythm | |
08:45 | also has to have a base and it's the same | |
08:47 | base as the exponential function that you are talking about | |
08:50 | . So we have an exponential longer than base here | |
08:52 | . Okay , so what we have is a log | |
08:55 | rhythm with a base of some number equal some other | |
08:58 | number . And the relationship of all this means you | |
09:00 | take the base to the power of whatever you have | |
09:03 | on the right hand side , we're calling it K | |
09:05 | is equal to some number . All I want you | |
09:07 | to know about this definition right now is that law | |
09:10 | algorithms can be transformed into exponential because you have the | |
09:13 | same things here , B N and K be in | |
09:16 | K . And these exponential is can be transformed into | |
09:19 | algorithms , B K and n . B K and | |
09:21 | N . So anytime you have an exponential , you | |
09:24 | can always write it as a law algorithm and any | |
09:26 | time you have a longer rhythm , you can always | |
09:28 | write it as an exponential because they're in verses of | |
09:30 | each other . All right . So let's go through | |
09:32 | a couple of very simple problems that you'll understand very | |
09:36 | quickly . And then we'll ratchet up the complexity as | |
09:38 | we go to me and we'll draw some pictures to | |
09:40 | make sure you really understand . Let's say a real | |
09:43 | life example . Let's say we have the law algorithm | |
09:46 | . If I can spell algorithm the law algorithm , | |
09:49 | Base two of the # eight , how would you | |
09:52 | calculate this ? Well we have a base to and | |
09:56 | we're taking the law algorithm of eight . Here's what | |
09:58 | you do to translate logarithms . You always have to | |
10:01 | translate them into an exponential because they're basically can always | |
10:05 | be written in terms of exponential . So what you | |
10:07 | do is you say the following thing , Okay , | |
10:09 | you say the base right ? That to the power | |
10:13 | of some number , I don't know what it is | |
10:15 | . X is equal to eight , two to the | |
10:19 | power of whatever the answer is . That I'm trying | |
10:21 | to calculate here . That's what I'm trying to find | |
10:23 | . Trying to find the exponent is equal to whatever | |
10:25 | the longer than that you have here is . Now | |
10:27 | let me ask you , how would you figure this | |
10:29 | out ? What is the exponent here ? That makes | |
10:32 | two to the power of that exponent ate . Well | |
10:34 | this means that X has to be equal to three | |
10:36 | . Sorry X has to be equal to I can | |
10:39 | write it correctly three . How do I know that | |
10:41 | ? Because two to the third power is 82 times | |
10:44 | two times two is eight . So what I basically | |
10:46 | said here and just stay with me is that the | |
10:49 | longer them ? Base two of the number eight is | |
10:53 | equal to three . And the reason I know that | |
10:55 | this thing is equal to three is because Because I'm | |
11:00 | gonna triple underlined it's because too which is the base | |
11:04 | to the power of three . On the right hand | |
11:06 | side of the equal sign equals eight . Two to | |
11:09 | the power of three is equal to eight . I'm | |
11:10 | gonna run my fingers a few times two to the | |
11:12 | power of three is 82 to the power of three | |
11:14 | is 82 to the power of three is eight . | |
11:16 | That is going to be how you translate logarithms . | |
11:19 | Every time you write them down you say base to | |
11:22 | the power of what the thing is equal to is | |
11:24 | equal to eight . The thing you're trying to find | |
11:26 | in a log rhythm . The thing that the log | |
11:28 | rhythm gives back to you is the exponent required to | |
11:32 | calculate this number . The mm said that one more | |
11:34 | time because this is the kind of thing that you | |
11:36 | learn after . You do a lot of problems but | |
11:38 | it's often not really told to you . The law | |
11:40 | algorithm as its output gives back to you what exponent | |
11:44 | is needed to make this thing equal to eight when | |
11:47 | I use this base . That is why logarithms and | |
11:50 | exponents are inverse is look how I took this long | |
11:52 | algorithm and I write it as an exponential expression . | |
11:55 | Two to the power of three is eight . This | |
11:57 | is inequality here too . To the power of three | |
11:59 | is eight . I can also start with this and | |
12:01 | go backwards . I can write this as a log | |
12:03 | rhythm for the same reason , the basis to Of | |
12:06 | the # eight . The exponent three is what's coming | |
12:08 | back . So you're often converting back and forth between | |
12:12 | exponential form and algorithmic form . You have to get | |
12:15 | used to that . So let's do a couple more | |
12:17 | of these to make 100% sure that you are getting | |
12:20 | comfortable with it because it's the most important thing . | |
12:22 | Okay let's say I have the law algorithm base to | |
12:27 | remember this base can be any number other than one | |
12:29 | , but I'm just using to hear of the number | |
12:31 | 16 . How would I figure out what the base | |
12:34 | of the algorithm ? Base two , logarithms of 16 | |
12:37 | . How would I figure out what that is ? | |
12:38 | Well I have to write a little equation to figure | |
12:39 | out what that is . I know that the base | |
12:42 | of this thing , So the power of something that | |
12:44 | this law algorithm is going to equal is going to | |
12:47 | have to equal 16 because logarithms return the exponents , | |
12:51 | it returns an exponent back to you . That's what | |
12:53 | algorithms do . And I say it a few times | |
12:56 | . I want you to remember that law algorithms give | |
12:57 | you back an exponent . So two to the power | |
13:00 | some exponent . That's gonna be what this log is | |
13:02 | equal to is equal to 16 . Now if you | |
13:03 | run through it it can't be too squared , it | |
13:06 | can't be two cubed X has to be equal to | |
13:08 | four because two to the fourth power is actually 16 | |
13:11 | . So another way of writing this is the log | |
13:15 | Base two of 16 is equal to four Because triple | |
13:20 | underlined the reason this is true is because two to | |
13:24 | the power of this exponent that the log rhythm gave | |
13:27 | me back is actually equal to 16 . You see | |
13:30 | we're following the same recipe in both of these examples | |
13:33 | to to the 32 to the third power eight . | |
13:36 | That means longer than base two of eight is three | |
13:39 | . The logger then gave me back the exponent that's | |
13:42 | needed when I raise to two , that exponent to | |
13:44 | give me this and I can write an exponent form | |
13:46 | like this , This one is two to the power | |
13:49 | of four is 16 . 2 to the power for | |
13:51 | 16 . That means the log rhythm gave me back | |
13:53 | the exponent needed . So I raised to the base | |
13:56 | to that expanded to give me that number . So | |
13:58 | it's literally a reverse exponent uh inverse , reverse exponential | |
14:02 | function . The exponential function is the base to the | |
14:05 | power of some of the exponent . The law algorithm | |
14:08 | is like okay here's your base . Here is the | |
14:11 | final number that I want you to kind of have | |
14:13 | tell me what exponent is needed to give me that | |
14:16 | number . That's what the law algorithm does . It | |
14:18 | gives you the exponent back . So you have to | |
14:21 | get the use of saying two to the power of | |
14:22 | whatever is on the other side of the equal sign | |
14:24 | equals this , two to the power of whatever's on | |
14:26 | the other side of the equal sign equals this . | |
14:28 | I'm saying it a lot of times because it's literally | |
14:31 | the most important thing in this whole lesson . Right | |
14:34 | , let's take a look at another one . What | |
14:35 | about the log Base two of the # 1 ? | |
14:39 | What would that equal to ? Well , I'm gonna | |
14:41 | show you that that's going to be equal to zero | |
14:43 | . How do I know it's equal to zero ? | |
14:44 | Well it's because of the following thing because the base | |
14:48 | to the power of this exponent that the law gave | |
14:51 | me back is equal to whatever I'm taking the longer | |
14:54 | the love . And I know that this is true | |
14:56 | because anything to the zero power is one right ? | |
14:59 | Make sure you understand that every time based to the | |
15:02 | power of this is equal to this . That's exactly | |
15:05 | what I wrote . What if I have the law | |
15:07 | algorithm based too Of the number 1/2 Is equal to | |
15:12 | -1 . How do I know this is true ? | |
15:14 | Well I know it's true because the base To the | |
15:18 | power of -1 is going to be equal to whatever | |
15:22 | I was taking the longer rhythm was remember the longer | |
15:24 | than gave me the power back . And you know | |
15:26 | that this is true because two to the one half | |
15:28 | means I can drop it in the denominator and make | |
15:30 | it a positive power right ? And so if I | |
15:33 | want to generalize this whole thing two to the power | |
15:36 | of three is 82 to the power of four is | |
15:38 | 16 . 2 to the power of zeros . 12 | |
15:41 | to the power of negative one is one half . | |
15:43 | I can generalize it and I can say that little | |
15:44 | log base two of the number N . Is equal | |
15:50 | to K . And that's because to to the exponent | |
15:54 | K is equal to whatever this number I was taking | |
15:57 | the log rhythm . What of and don't forget that | |
16:01 | this base in this . In all of these cases | |
16:02 | I'm using the number two but the base can be | |
16:04 | three . The base can be fore , the base | |
16:06 | can be 10 . The base can not be negative | |
16:09 | though because remember we go back to our definition if | |
16:12 | being in er positive numbers but the base can't be | |
16:14 | one . Why can't the base B . One ? | |
16:16 | The base can't be one because if you have one | |
16:19 | as the base of an exponential then you don't have | |
16:21 | an exponential at all . One to the power of | |
16:23 | anything is just one and you can't have negatives for | |
16:25 | the base . For the reasons we talked about in | |
16:27 | the exponential function because you don't have an exponential function | |
16:29 | there either go back to the lesson on exponentially if | |
16:32 | you forget that . So the base has to be | |
16:34 | the same kind of base as an exponential function has | |
16:36 | to be positive and the base can't be one . | |
16:39 | So as to be bigger than zero but it can't | |
16:40 | be one . Now . This definition should make a | |
16:42 | little more sense . The log base B of the | |
16:45 | number in as K . If and only if B | |
16:47 | to the power of K is in B to the | |
16:49 | power K is in exactly as we've done it with | |
16:51 | numbers down here . Okay , so so far I | |
16:54 | have shown you the mechanics of what you do when | |
16:56 | you see a log rhythm on the page . All | |
16:58 | you have to do is say the base which is | |
17:01 | written right underneath the log rhythm to the power of | |
17:03 | whatever the thing is equal to is equal to whatever | |
17:07 | . Uh you're taking the log rhythm of because the | |
17:10 | algorithm gives you the exponent back of whatever you're taking | |
17:12 | the log rhythm of , right . But we haven't | |
17:15 | really done anything graphical . We haven't really shown you | |
17:17 | that their inverse functions . We haven't really done any | |
17:19 | of that . So what we need to do now | |
17:22 | and draw a couple of quick pictures to show you | |
17:24 | that the law algorithm is really the inverse function of | |
17:27 | an exponential function . And then you'll really understand more | |
17:30 | about why they're exactly so closely related cousins of one | |
17:33 | another . Okay , so why is this behavior happened | |
17:37 | ? Why is it that two to the power of | |
17:39 | K ? Is this why is it that two to | |
17:40 | the power of zero ? Is this why is that | |
17:42 | the case ? Let's look at the following thing . | |
17:45 | Let's draw two graphs . This is the middle of | |
17:47 | my board . So I'm gonna try to draw two | |
17:48 | graphs . I'm gonna try to draw the exponential function | |
17:50 | right here and then I'm gonna try to draw over | |
17:54 | there . I'm gonna try to draw the algorithm . | |
17:58 | So here I have F of X and here I | |
18:01 | have X . And I want to draw first the | |
18:03 | exponential function . So what I'm gonna draw is my | |
18:06 | exponential function is F . Of X . Is to | |
18:09 | to the power of X again . Remember I'm using | |
18:11 | the base of two but this base can literally be | |
18:13 | 10 or five or 15 , it can't be negative | |
18:16 | and it can't be one , but it can be | |
18:17 | anything else . It can even be decimals . 1.3 | |
18:19 | to the power of X is perfectly fine as a | |
18:22 | base for this exponential function . But two is very | |
18:24 | easy because we can calculate things in our heads really | |
18:26 | , really easy with the number two . Now , | |
18:28 | I think I need to um draw some tick marks | |
18:33 | and you try to be kind of precise with them | |
18:35 | . So here's one , here's to here's three , | |
18:37 | here's 12345678 Okay , I barely made it . That's | |
18:42 | as many as I need . Remember . Every exponential | |
18:45 | uh with a positive base like this a bigger than | |
18:48 | one starts off like this and goes up to the | |
18:51 | right , so we know this exponential function is gonna | |
18:53 | look like this , we know it's going to go | |
18:54 | through the value of one because this is one right | |
18:56 | here , right ? So we know it's going to | |
18:58 | go through here , but we need to be a | |
18:59 | little bit more precise so that when we draw the | |
19:01 | inverse it'll make a little more sense . So what | |
19:03 | we're gonna do is we're gonna calculate um zero comma | |
19:08 | one , that's going to be a value here . | |
19:10 | And then when we put the value of one in | |
19:13 | here , this is one , this is two , | |
19:15 | this is three , we put the value of one | |
19:17 | in here . Uh to to the one power is | |
19:19 | going to be too , so it's going to be | |
19:20 | up right here at two . Right now we put | |
19:24 | two in here , it's gonna be two to the | |
19:26 | power to is four . So here's 1234 So it's | |
19:28 | gonna be something like this . Okay , And then | |
19:32 | three so two to the power of three is going | |
19:34 | to be eight . So that's why I needed 82345678 | |
19:37 | It's gonna be eight and it's gonna be something kind | |
19:40 | of like this . All right . So you see | |
19:43 | it's not a straight line . If it was a | |
19:44 | straight line , it would be like this . But | |
19:46 | you see it's curving so we need to do is | |
19:48 | attempt and I'm probably gonna mess this up . But | |
19:51 | it needs to go something like this needs to go | |
19:53 | through this point , through this point , through this | |
19:55 | point and then up . It's not perfect , but | |
19:58 | I'm not gonna erase it because it's actually close enough | |
19:59 | . It goes through all of these points . Now | |
20:01 | I need to label some points because I'm going to | |
20:03 | draw the same points over in the log arrhythmic curve | |
20:05 | . Okay , what do we have right here ? | |
20:07 | Well , this point goes over here , it's two | |
20:10 | to the power of three . That was equal to | |
20:12 | eight . Uh the base two to the power of | |
20:14 | three , it was equal to eight . That's why | |
20:16 | we landed right there . Okay , this one is | |
20:20 | I'm gonna save that one for later . This one | |
20:21 | right here is over here , we can draw a | |
20:25 | little line right here . It's two to the power | |
20:26 | of 12 to the power of one , that's equal | |
20:28 | to two . Now we know that this is two | |
20:29 | to the power of two . Right ? So I | |
20:32 | can kind of draw this one here . As over | |
20:34 | here , this is gonna be uh to I'm sorry | |
20:37 | 3:08 . This is 3:08 , and this one is | |
20:42 | 2:04 . And this one right here is one comma | |
20:47 | two and this is just the intercept right there . | |
20:50 | Okay , so this one right here is to to | |
20:54 | the power of two is four . But what I | |
20:55 | wanna do is I want to introduce this notation . | |
20:57 | Notice over here , I have B . To the | |
21:00 | power of K . Is in the K . Is | |
21:02 | the X . Moment the bases be in is the | |
21:04 | number you get out . Uh that the exponential calculates | |
21:08 | in . So what we really have here is I'm | |
21:11 | gonna say this right here is uh no , it's | |
21:15 | really the number two , but I'm gonna put the | |
21:16 | letter K underneath it . So really this thing is | |
21:19 | going to be something like a comma in why ? | |
21:22 | Because two to the power of K . Was equal | |
21:25 | to end . Yes , I know it's at the | |
21:27 | number four , but I'm generalizing it because I want | |
21:29 | to map it over . You'll see why I'm gonna | |
21:31 | generalize it later . So it's really the number two | |
21:32 | . But let's call it the letter K . Because | |
21:34 | any of these numbers can be K . I'm gonna | |
21:36 | run it through . It's gonna be two to the | |
21:37 | power of K . That gives me the number back | |
21:39 | . We know it's really the number four , but | |
21:41 | that's pretty much what it looks like right there . | |
21:42 | Okay . Now what we want to do if you | |
21:44 | want to draw the inverse of this exponential function , | |
21:47 | the inverse remember is the function that you get when | |
21:51 | you draw a diagonal line At 45°, , which is | |
21:54 | this line why is equal to X . And you | |
21:56 | flip this thing over ? Okay , now I don't | |
21:58 | have room on this graph . So what I'm gonna | |
22:00 | do is go over here and try to draw it | |
22:02 | right here . So here is this gonna try to | |
22:05 | draw as good as I can not gonna probably do | |
22:08 | a great job . And this is not gonna be | |
22:10 | ffx , this is gonna be f uh inverse of | |
22:14 | X , right ? The inverse function , which means | |
22:17 | that I have to draw kind of this diagonal line | |
22:19 | here , which I will do is a little reference | |
22:23 | . It's gonna be a diagonal line . And this | |
22:25 | diagnosed line is the equation why is equal to X | |
22:27 | . And we're gonna essentially you have to pretend it's | |
22:29 | here and you map it and you flip it over | |
22:31 | . Right ? So how many tick marks do I | |
22:33 | need ? Let's try to use a similar colors . | |
22:35 | Let's go if you think about it . This is | |
22:37 | gonna flip down . So you need eight this direction | |
22:39 | 123456788 And then let's just do 1234 . We need | |
22:47 | I think it's four in this direction like this . | |
22:49 | All right . So what's gonna happen is this thing | |
22:52 | is gonna get mapped over here ? So what's gonna | |
22:54 | happen is let's extend this guy down just a little | |
22:58 | bit . Remember ? The inverse function takes all of | |
23:02 | these points and it interchanges them . This point gets | |
23:06 | interchange . This point gets interchange . That's how the | |
23:08 | mapping happens . So , we know that zero comma | |
23:12 | one is here . So that means it needs to | |
23:14 | go through one comma 01 comma zero . Right here | |
23:17 | . Actually , let me Yeah , let's do it | |
23:19 | right here . 1:00 needs to go through this point | |
23:21 | , right there . One comma two is a point | |
23:24 | . That means two comma 12 comma one . This | |
23:26 | needs to be a point . Is that flip it | |
23:29 | around ? Two , comma four . That means four | |
23:31 | comma two needs to be a 20.1234 comma 12 means | |
23:36 | this guy right here , one . What's 1234 slips | |
23:39 | into the wrong ones right next door right here . | |
23:42 | 1 , 2 , 3 4 comment to and then | |
23:44 | three comma eight means flip it over eight comma three | |
23:46 | . This is eight comma three . This point needs | |
23:49 | to be in right here . So all I do | |
23:51 | is take these , I flip them around , they | |
23:53 | draw the points and then you can kind of see | |
23:54 | that it's gonna bend over like this . So if | |
23:56 | I can do a good job , which I probably | |
23:58 | can't , it's gonna go through like this , bend | |
24:00 | over and go something something like this , which actually | |
24:04 | is not too bad . Yeah , I kind of | |
24:06 | messed up the end there . You get the idea | |
24:07 | , there's something like this . That's not too bad | |
24:10 | . And if you use your imagination , you can | |
24:11 | see that this thing reflected over is the exact inverse | |
24:15 | because it's a flipped over version of this thing . | |
24:17 | So this equation down here that we've written down is | |
24:20 | not to to the X . This thing is called | |
24:23 | the inverse . Yeah . Right . And it is | |
24:27 | log base two of the number in . Remember you're | |
24:33 | taking the longer the using a given base of the | |
24:36 | number in . And what does it give you back | |
24:38 | ? It gives you back the exponent . The exponent | |
24:41 | such that that base to that exponent is that number | |
24:44 | ? You're literally going backwards . It's like the logarithms | |
24:46 | , Like we never calculate the exponent , that's that's | |
24:49 | never done . But logarithms do that . They give | |
24:51 | you the exponent back , right ? They give U | |
24:53 | K back , they give you the K . Which | |
24:55 | is the exponent needed when you raise it to the | |
24:57 | base to give me this number right here . Right | |
24:59 | . So every number I put in here the law | |
25:02 | algorithm has given me the exponent needed back . Right | |
25:05 | ? So what are these points here ? Okay this | |
25:08 | point means that I put um This point means that | |
25:13 | I put 1:00 in there which is exactly the mirror | |
25:17 | image of this guy . Okay or the flipped value | |
25:20 | of this guy . It gives me the exponent back | |
25:22 | . In other words I'm gonna take the law algorithm | |
25:23 | based two of the number one . The exponent that | |
25:27 | that I need to do that as a zero because | |
25:28 | two to the zero power gives me one . Okay | |
25:32 | um This point right here is two common one . | |
25:39 | Because if I'm taking the law algorithm based two of | |
25:42 | the number two I'm going to get a one back | |
25:44 | . I need an exponent of one to do that | |
25:46 | . Okay this guy is I'm gonna write two things | |
25:50 | down . It was two comma four . It's really | |
25:53 | four comma too . However I'm gonna also write it | |
25:56 | as instead of K . Dot comma in its in | |
25:59 | kama . Kay because what I'm doing is I'm putting | |
26:02 | the number in that I want to take the log | |
26:04 | rhythm of and it's giving me the exponent back in | |
26:06 | this case the exponent was too but in general has | |
26:08 | given me the exponent K back and then this last | |
26:11 | one here Is instead of 3:08 It's 8:03 . So | |
26:18 | remember what did I say ? Expo exponential functions do | |
26:22 | I'm sorry what what did I say inverse functions do | |
26:25 | it under does or does the opposite of the original | |
26:28 | function . So if I have a function here number | |
26:30 | one the function here number two and I put the | |
26:32 | number one in there then I'm gonna get some value | |
26:35 | out and I stick that and put it through the | |
26:37 | inverse . I'm gonna get some other number out . | |
26:39 | But the number I get out will be exactly the | |
26:41 | same as what I put in because It kind of | |
26:43 | undies the function of the first calculation . They put | |
26:46 | a two in and run it through both of them | |
26:48 | . I should get a two out , put a | |
26:50 | 10 in and run it through both . I should | |
26:52 | get a 10 out . So let's look at that | |
26:55 | in this exponential function . If I put a three | |
26:57 | in as an input , I'm gonna get an eight | |
26:59 | out of this exponential function . But if I take | |
27:02 | this eight and I put it through the second function | |
27:04 | , I'm gonna get a three out . Three is | |
27:06 | exactly what I put in to begin with . If | |
27:09 | I put a two into this original function , I'm | |
27:11 | going to get a four out . But if I | |
27:13 | put that four in here , I'm gonna get a | |
27:16 | two out , which is exactly what I started with | |
27:17 | . So you see these are inverse functions because whatever | |
27:20 | I put into the exponential function and then I run | |
27:22 | it through the inverse , which is the algorithm with | |
27:25 | the same base , the base has to be the | |
27:26 | same . What I get out is exactly what I | |
27:29 | put in . And that means of course this isn't | |
27:31 | a mirror image reflection of this thing here . So | |
27:33 | you need to remember two things about this graph number | |
27:36 | one . This is a law algorithm , it starts | |
27:38 | it gets infinitely close to the axis here , it's | |
27:42 | an asem toe , but it goes off to infinity | |
27:45 | this way , but it bends over very , very | |
27:47 | quickly like this . Okay , whatever number you put | |
27:50 | into the function , it's giving you the exponent out | |
27:53 | needed , so that if you run it backwards through | |
27:56 | the function , you kind of get what you started | |
27:57 | with . And then of course it's a mirror image | |
28:00 | reflection of this exponential function . So these guys in | |
28:05 | verses of each other . So we don't say that | |
28:13 | this is just the log is the inverse of the | |
28:16 | exponential . We also go the other way we say | |
28:18 | that the exponential is also the inverse of the law | |
28:20 | there in verses of each other and they undo each | |
28:23 | other . So if you have an equation that has | |
28:25 | an exponential function in it , but that variable is | |
28:28 | wrapped up in the exponential function , you want to | |
28:30 | kill the exponential . You might take the law algorithm | |
28:32 | of both sides because the law algorithm is going to | |
28:34 | kill the exponential , it's gonna disappear because of exactly | |
28:37 | what we said here in versus undo each other . | |
28:39 | Right ? If you have the other situation , you | |
28:42 | do the other operation , like if you have a | |
28:43 | low algorithm on both sides of an equation or one | |
28:46 | side of an equation but your ex your variables wrapped | |
28:49 | up inside of the law algorithm . But you want | |
28:50 | to solve for the variable . You gotta kill thatl | |
28:52 | algorithm . So you raise both sides of the equation | |
28:57 | to the to the exponent base to the what you | |
29:00 | basically have to raise it to an exponent to kill | |
29:03 | the algorithm and they'll disappear in your variable pop out | |
29:06 | . We'll do that later . Will solve equations . | |
29:07 | Using this property here . The bases are the same | |
29:11 | . That's the other thing I want to point out | |
29:13 | in order for this inverse business to happen . The | |
29:17 | basis are the same , right ? The base two | |
29:22 | to the power of X . The inverse of that | |
29:23 | is the base too long rhythm . And have the | |
29:25 | bases have to be the same . Otherwise they're not | |
29:27 | the same thing . And that's why when we solve | |
29:30 | logs and we do this business with solving logs , | |
29:32 | we end up writing it as an exponential function because | |
29:35 | they both kind of go together like that . And | |
29:37 | any log can be written in exponential form and then | |
29:40 | the exponential can be written in terms of a log | |
29:42 | form . Because what's happening in this log equation is | |
29:44 | I'm just giving you a number and getting the exponent | |
29:46 | out . When I go to this equation , I'm | |
29:48 | giving you the exponents and I'm giving you the number | |
29:50 | out . So it's literally like going backwards through the | |
29:53 | operation there . All right , So I want to | |
29:56 | talk about a little bit shifting the discussion to why | |
30:00 | we care about logs . There's so many reasons I | |
30:02 | can't give it all in one lesson , but I'm | |
30:03 | gonna give you a couple of really big ones right | |
30:05 | now . Um so far we've been doing a lot | |
30:09 | of base two logarithms . The reason we're doing base | |
30:12 | two logarithms because it's easy to calculate . But really | |
30:15 | one of the most common logs that you're gonna run | |
30:17 | into is base 10 logarithms . In fact , when | |
30:20 | you say the word law algorithm and if you don't | |
30:22 | specify a base at all , most people are going | |
30:24 | to assume that you probably mean a base 10 logarithms | |
30:27 | . And later on in the class , we're gonna | |
30:29 | talk about base L algorithms . The special number E | |
30:32 | . We'll talk about that later . We're not gonna | |
30:33 | get into that now , that thing is called the | |
30:35 | natural algorithm . We'll talk about that much later . | |
30:37 | For now . Let's focus on the other special algorithm | |
30:40 | which is the base 10 logarithms . Alright , so | |
30:43 | base 10 logarithms are really important . So let's talk | |
30:45 | about that . Base 10 logs . All right , | |
30:51 | so um what I mean when I say base 10 | |
30:53 | logarithms is is if you have a function F of | |
30:57 | X Equals 10 to the power of x . the | |
31:00 | basis 10 then it's inverse . Yeah . Is going | |
31:04 | to be a long algorithm . But the law algorithm | |
31:06 | has to be a base 10 as well algorithm . | |
31:09 | Base 10 of some variable X . Okay . So | |
31:13 | you see in order for these to be in verses | |
31:15 | , the bases have to be the same across the | |
31:17 | exponential and across the algorithm . Otherwise they're not in | |
31:19 | verses of each other . So let's talk a little | |
31:21 | bit about Some base 10 logs . Let's say I | |
31:25 | have log of the number one notice I didn't write | |
31:30 | the base 10 . If you see a log without | |
31:33 | any base written at all , you just pretty much | |
31:35 | assume it's a it's a base 10 law . That's | |
31:36 | how common it is . If you see a base | |
31:38 | there you have to use the base . But if | |
31:40 | you don't use a base at all , if you | |
31:41 | don't see a base at all , it's a base | |
31:43 | 10 log . What is the log base 10 of | |
31:45 | the number one ? Well , what we know is | |
31:48 | that that means that's exactly the same thing . Is | |
31:50 | this base 10 logarithms of one . And what this | |
31:53 | means is we take the base of 10 , raise | |
31:56 | it to some unknown power . We're trying to calculate | |
31:58 | because the law gives you the power back Equals one | |
32:01 | . So my question to you is what value of | |
32:03 | X . works ? And that means X . Has | |
32:06 | to be zero . Why ? Because tens of the | |
32:08 | zero is one , Right ? So what we've learned | |
32:11 | here is that log of the number one ? Base | |
32:13 | 10 log of the number one is zero . Okay | |
32:16 | . What I'm gonna do is calculate a few of | |
32:18 | these things going down the page and I'm gonna draw | |
32:20 | some really important um observations as we go down here | |
32:25 | . So that was a log of the number one | |
32:26 | . Let's take a look at log of the number | |
32:29 | 10 . Again , it's a base 10 law because | |
32:31 | there's nothing written there , but you can kind of | |
32:33 | assume that it is , this is the exact same | |
32:35 | thing as writing base 10 logarithms of the number 10 | |
32:39 | . So what does this mean ? It means the | |
32:41 | base so the power of something has to equal this | |
32:44 | number . Now . What does this experiment have to | |
32:46 | be equal to ? It has to be equal to | |
32:48 | one , The only exponent that works as one . | |
32:51 | So that means that the log of the number 10 | |
32:54 | is equal to one . So we figured out the | |
32:56 | log of 10 base 10 and the log of 10 | |
32:59 | is one again based 10 . So let's do a | |
33:02 | couple more examples . Uh Down the page here , | |
33:06 | Let's go and do the log of 100 . Okay | |
33:10 | , how do you figure this out ? Well , | |
33:12 | you know , it's a base 10 by now , | |
33:13 | so 10 to the power of something is 100 . | |
33:16 | What does this exponent have to be ? The only | |
33:19 | way this works is if x is two because 10 | |
33:21 | squared is 100 . So we've learned that log of | |
33:24 | 100 is equal to two . So I'm I'm generating | |
33:27 | a pattern here and now that we understand what we're | |
33:30 | doing , we're gonna go down the page a little | |
33:31 | bit faster if the log of one is zero and | |
33:34 | the log of 10 is one and the log of | |
33:36 | 100 as to what do you think That the log | |
33:38 | of 1000 will equal to ? Well , it's gonna | |
33:40 | be 10 to the power of something as 1000 . | |
33:42 | So it has to equal three . Right , What | |
33:45 | do you think the log of 10,000 Is going to | |
33:50 | be equal to 10 to the power of something as | |
33:51 | 10,000 has to be equal to four . You see | |
33:53 | what's happening , you started out at zero and then | |
33:56 | it goes one , then it goes to , then | |
33:58 | it goes three , then it goes four . So | |
33:59 | as I take the law algorithm , I've multiplied by | |
34:02 | 10 . I'm taking the logarithms , something 10 times | |
34:04 | bigger . And then here I'm taking the log rhythm | |
34:06 | of 10 times bigger still . And here I'm taking | |
34:09 | the longer than the 10 times bigger . Still . | |
34:10 | 10 times bigger . Still , every time I go | |
34:12 | up times 10 , the longer than just goes up | |
34:16 | by one . You see I'm taking the long rhythm | |
34:18 | of something 10 times bigger every time . But the | |
34:20 | longer term only goes up from 0 to 1 to | |
34:22 | 2 to 3 to four . And you can generalize | |
34:25 | that . What if you do something that's not a | |
34:26 | perfect little times 10 thing . Let's take the log | |
34:30 | rhythm Of 20,000 . That is not 10 times bigger | |
34:35 | . It's not 10 times bigger . That's only two | |
34:36 | times bigger . What do you think you would get | |
34:39 | ? What you're going to have is you're gonna have | |
34:40 | 10 To the power of something is 20 1000 . | |
34:46 | When you run that in a calculator and figure out | |
34:49 | what this exponent is . You're gonna get 43 Now | |
34:53 | I've rounded it to two decimal places . But you | |
34:55 | see it's just a little bit bigger than this one | |
34:57 | . See the algorithm of 10 , was four ? | |
35:00 | The algorithm of 20,000 was just a little bit bigger | |
35:02 | than four . Okay . What do you think the | |
35:04 | logger them of ? 150 would be just to pick | |
35:08 | a totally different number ? Well , what you would | |
35:10 | say is 10 base 10 to the power of something | |
35:13 | is 1 50 . When you run that through the | |
35:15 | calculator , you're going to get 2.18 And I'm getting | |
35:20 | to a point here . I promise I have one | |
35:21 | more to put on here . What about the law | |
35:23 | algorithm of 1700 ? When you run that to a | |
35:28 | calculator , you're gonna get 3.23 . Okay . What | |
35:33 | I'm trying to get you to say is something that | |
35:36 | I honestly didn't really realize about logarithms until Well , | |
35:40 | well beyond I had learned them . It's something way | |
35:43 | , way , way in the future . I finally | |
35:45 | understood that logarithms really , I don't wanna say they're | |
35:47 | only use but one of their main uses . Okay | |
35:49 | , when you run a number through algorithm , what | |
35:52 | the law algorithm really is doing is it's giving you | |
35:54 | the exponent back . That's what I've been telling you | |
35:56 | over and over again . But notice that for a | |
35:58 | 1000 what's happening is the number you're getting back is | |
36:02 | the number of decimal places past the first position . | |
36:04 | When you take the log base 10 of 1000 you're | |
36:07 | getting the three , it's telling you , hey there's | |
36:09 | three digits past the number one . When you take | |
36:12 | the log of 10,000 and get a four back it's | |
36:14 | telling you , hey there's four digits past the one | |
36:17 | when you take a log of 100 is telling you | |
36:19 | , hey there's two digits past the one . Hey | |
36:21 | there's only one digit pass the one . Hey there's | |
36:23 | no digits past the one . So the longer than | |
36:25 | base 10 is really telling you how big the number | |
36:28 | is , how many digits it is , It's ignoring | |
36:30 | all the details . Notice that the log of 20,000 | |
36:34 | is telling you , Hey there's just 4.3 digits . | |
36:37 | That's kind of a little weird because there's four digits | |
36:40 | after here . But it's basically telling you how close | |
36:42 | you're gonna be because when it gets to five that | |
36:44 | would be five digits past , right ? It's at | |
36:47 | 20,000 you have to go 20 and 40 and 60 | |
36:49 | and 80 . Then you will get to 100,000 . | |
36:51 | That would be five digits past . So this is | |
36:53 | telling you you're getting fractionally a little bit closer to | |
36:56 | that next decimal . Place that next zero in the | |
36:59 | number . It's telling you how much closer you are | |
37:02 | to that but it's basically reporting back how many zeros | |
37:06 | or how many digits you have in the number past | |
37:08 | the first position here , you had none past the | |
37:11 | first position here . You had one past the first | |
37:13 | position to pass the first position . Three past the | |
37:15 | first position four passed . This is just a little | |
37:18 | bit more past four . This is a little bit | |
37:20 | more past two so it's 2.1 a . This is | |
37:23 | a little bit more past three . Getting close to | |
37:25 | you know you have to get up to 10,000 to | |
37:28 | get to the next one and you're getting a little | |
37:30 | bit closer and the decimal part of it is telling | |
37:32 | you that . So it tells you the number of | |
37:34 | digits . So if you have numbers where you don't | |
37:37 | care about the exact value of the number , you | |
37:39 | just kind of want to know roughly how big things | |
37:41 | are . Then the logarithms a perfect thing because it's | |
37:44 | gonna throw away all of the , I don't want | |
37:46 | to throw it away but it's going to tell you | |
37:48 | basically how big the number is , how many digits | |
37:50 | the number has Without all the details of that , | |
37:53 | of the actual number there you might say . Why | |
37:56 | do we care about that ? Why don't we just | |
37:58 | give you the number ? Well , a great example | |
38:00 | is the Richter scale of of of uh of earthquakes | |
38:05 | you always hear in the news 6.2 on the Richter | |
38:07 | scale , 5.3 on the Richter scale . And it | |
38:10 | also doesn't really become very clear what those numbers really | |
38:13 | mean . But you have to remember that every time | |
38:16 | we multiplied by 10 of the number , the log | |
38:19 | rhythm of it just went up by one . So | |
38:21 | what we've learned here is since the Richter scale is | |
38:23 | log arrhythmic . If you see a four point oh | |
38:26 | on the Richter scale and a 5.2 on the Richter | |
38:29 | scale , it doesn't seem like very much , but | |
38:31 | really that means it's 10 times bigger . A four | |
38:34 | on the Richter scale and a five on the Richter | |
38:36 | scale is not a little bit different . It's 10 | |
38:38 | times bigger . How do I know ? Because the | |
38:41 | difference between three and four or let's go back to | |
38:43 | three and three and four versus four and five , | |
38:45 | The difference between three and four on the Richter scale | |
38:47 | is actually 10 times bigger in energy , earthquake is | |
38:50 | measured in energy . Right ? So if you have | |
38:54 | a situation in an earthquake , right ? I'm not | |
38:57 | an earthquake scientist . Okay , But here , you're | |
38:59 | basically measuring energy energy of the earth coming coming out | |
39:04 | in terms of , you know , um in terms | |
39:08 | of uh this guy here , let's let's talk about | |
39:11 | versus time . So energy versus time , an earthquake | |
39:14 | probably starts small and it is really , really powerful | |
39:16 | and it gets really small again . Right ? So | |
39:18 | what you have with earthquakes is there is a huge | |
39:22 | amount of difference in energy released . Right ? So | |
39:25 | what might happen is you might start out really , | |
39:27 | really , really low in this energy scale might be | |
39:30 | really , you can't even read it on this graph | |
39:32 | and you have a little spike here , a little | |
39:34 | bit bigger spike . And then the main part of | |
39:36 | the earthquake comes , it is really , really big | |
39:38 | . Really , really big and has jumped down here | |
39:41 | . You can't even read and it's really , really | |
39:43 | big again , Really , really big again . And | |
39:45 | then it gets off the chart and it comes back | |
39:48 | down like this . You see a graph like this | |
39:50 | isn't that useful to us . I mean it is | |
39:52 | useful , it does tell you how big everything is | |
39:54 | . But the problem is I can kind of read | |
39:56 | these but I can't read any of this stuff down | |
39:58 | here because at this scale the tiny little wiggles at | |
40:02 | the bottom are impossible to read because they're just so | |
40:04 | small compared to everything else . And the reason they're | |
40:07 | so small is because there's a huge difference in energy | |
40:10 | released in the beginning of the quake to the middle | |
40:12 | of the quake . Right ? So what you need | |
40:14 | is a way to tell me how big these different | |
40:17 | parts of the earthquake are or how big different earthquakes | |
40:20 | are without using the actual numbers . The actual energy | |
40:24 | numbers . Because the energy numbers are going to be | |
40:26 | huge , 100 million , trillion . And then another | |
40:28 | earthquake might be 100,000 or 5000 . And that number | |
40:32 | is just so different that you can't graph it like | |
40:34 | that . So what we do is instead of reporting | |
40:36 | the energy numbers of the earthquake , we take the | |
40:38 | algorithm Right now , the actual Richter scale is a | |
40:41 | little more complicated than this , but basically you're taking | |
40:44 | the law algorithm . So notice that when we multiplied | |
40:47 | like this , this the difference here in energy here | |
40:50 | to the energy here might be a difference of 100 | |
40:52 | or a difference of 1000 . It's hard to graph | |
40:55 | that . But the difference between 100 and 10,000 is | |
40:59 | just a difference of two points on a long algorithm | |
41:01 | scale . So actually we graph these earthquakes on what | |
41:04 | we call la algorithm scales . We think the law | |
41:06 | algorithm of all the data and that basically gets rid | |
41:09 | of all the details and it just tells me how | |
41:10 | many digits because the numbers are so huge . I | |
41:13 | only care about how many digits are in there when | |
41:15 | it's little versus when it's big . So the actual | |
41:18 | Richter scale looks something like this . So it's called | |
41:21 | Richter scale . And again , I'm not an earthquake | |
41:26 | scientists , I grabbed these right off Wikipedia . Right | |
41:29 | , so a one on the Richter scale is called | |
41:31 | a micro . That's , you can basically can't even | |
41:34 | feel that A two on the Richter scale is called | |
41:36 | a minor earthquake . Three is also characterized as minor | |
41:42 | . You probably feel that , but you're not gonna | |
41:44 | be that scared by it . A four is going | |
41:46 | to be called a light light , you're gonna have | |
41:49 | some damage , but probably not very much . A | |
41:52 | five is going to be moderate . A five is | |
41:56 | when you're gonna start reporting these things on the news | |
41:59 | . A six on the Richter scale is a strong | |
42:03 | A seven on the Richter scale is a major right | |
42:09 | ? An eight on the Richter scale is great . | |
42:13 | A nine on the Richter scale is total devastation . | |
42:22 | Right ? A nine point anything . Now there's no | |
42:23 | 10 because it only goes to 9.99 or whatever . | |
42:26 | Okay . But basically anything above a nine , your | |
42:29 | city is flattened . Major major damage . I mean | |
42:31 | , way more major than a typical earthquake . I | |
42:33 | mean , the reason that these numbers don't often convey | |
42:36 | the strength here is that because the number two and | |
42:38 | number four , they don't seem so far apart . | |
42:40 | However , between the # one and 2 , This | |
42:42 | is times 10 bigger between two and three . This | |
42:45 | is times bigger than that again . So that means | |
42:47 | between one and three is actually 100 times bigger Because | |
42:50 | 10 times 10 , right ? This is times 10 | |
42:54 | . This is times 10 . And then from here | |
42:57 | to here is times 10 and then you have times | |
43:00 | 10 , you get the whole idea times 10 Times | |
43:04 | 10 . So if you're looking at the difference between | |
43:06 | one and two , that's 100 times bigger . Between | |
43:09 | one and three , I'm sorry , one and uh | |
43:13 | this one right here . This is yeah , this | |
43:15 | is 100 . This would be 1000 times bigger . | |
43:17 | This would be 10,000 times bigger . Right ? And | |
43:20 | you can go down the calculation and figure out how | |
43:21 | much bigger A nine would be than a one . | |
43:23 | But that's why when you see on the news , | |
43:25 | you might see a 5.3 on the Richter scale and | |
43:28 | that's bad . But a 6.3 is way way worse | |
43:32 | because it's 10 times bigger . Okay . And that | |
43:35 | is one of the biggest uses of the of the | |
43:37 | law algorithm is in practical use that you would see | |
43:40 | in everyday life . But there's many other examples I | |
43:42 | can give you from chemistry , I can give you | |
43:43 | from physics or whatever , but this is the one | |
43:45 | that you'll actually probably see on TV . And it | |
43:47 | all goes back to the fact that when you start | |
43:50 | taking logarithms of numbers , if you on a base | |
43:52 | 10 Then you start multiplying by 10 , then the | |
43:55 | actual algorithms are just giving you the number of digits | |
43:58 | back . So they're they're only going up by one | |
44:00 | each time every time you multiply by 10 . So | |
44:03 | that is the concept of what is a law algorithm | |
44:05 | . I hope that you can understand what algorithm is | |
44:08 | . It's basically the opposite . Also what we call | |
44:11 | the inverse of an exponential function law algorithms are not | |
44:14 | going away . Some students don't like them but you're | |
44:16 | just gonna have to get used to them . The | |
44:18 | best advice is just to when you start to see | |
44:20 | a longer than written down anywhere . Just immediately convert | |
44:23 | it to exponential form . Because most people are more | |
44:25 | familiar and comfortable with an exponential function log rhythms get | |
44:30 | , you know crazy and people get crazy . I | |
44:32 | don't understand how to deal with it , but we | |
44:33 | have to learn it because later on we have laws | |
44:36 | of logarithms , how to ADL algorithms , how to | |
44:38 | multiply logarithms are not going away . So make sure | |
44:41 | you understand this , solve these problems . Draw these | |
44:43 | graphs , follow me on to the next lesson , | |
44:45 | we're gonna start simplifying expressions that have logarithms and we'll | |
44:48 | be using this definition , this exponent inverse definition along | |
44:52 | the way . So follow me on there will continue | |
44:54 | learning about logarithms in math . |
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