This playlist contains a set of videos related to our article on ignoring the random effects assumption in multi-level models, review, critique and recommendations. The first video is a general video made by John Antonakis and myself and we go over the entire paper here, talk about why we wrote this paper and explain the most important concepts. So you should probably start by looking at that video. The remaining videos are more focused on specific topics and also give you some background information on some concepts in multi-level modeling. So the first video is the one made by John and I. The second one is this introductory video and then we have 14 other videos that explain different concepts. The next three videos are generally about multi-level data. So if you are new to multi-level data, if you are new to levels of variation, if you don't know what interclass correlation is, or if the concept of unobserted or gen 80 is not familiar to you, then these three videos are probably helpful when you try to understand what our paper is about. The next set of videos, these two videos are about what is the impact of non-independence of observations on regression analysis and how do we deal with the non-independence of observations by using cluster robust or just robust standard errors. The key here is to understand that if you are just interested in estimating the population average effect which the regression gives you, you don't necessarily need to do any fancy stuff like multi-level modeling or panel data regression using GLS. So this is the first set that explains why you should care about non-independence of observations in regression analysis and what it means that regression assumes that the observations are independent. The video about heteroscedasticism is consistent and cluster robust standard errors a bit technical, but I hope that those technical details will help you to understand the issue on a more fundamental level. Then I'll talk about how we can model different effects from the data using normal regression analysis. In multi-level data we can estimate four different kinds of effects.  Then we have the contextual effect which refers to an effect of that others in the same context have on an individual level outcome. The between effect is the effect of cluster mean of one variable on cluster mean of another variable. I'll talk about how you estimate these effects in just normal regression context. In most cases you are actually going to be okay by just using normal regression analysis and these centering techniques and cluster robust standard errors if required. The next set of videos are about more advanced techniques so I'll cover what is a mixed effects model, what's a random part, what's a fixed part, what's a fixed effect, what's a random effect. Then I'll talk about GLS fixed effects and GLS random effects estimators. This is something that if you for example use data, if you run XD-reg this is what the command does. I'll explain a bit about the idea of the GLS estimation and why one would like to use that kind of techniques and when. Then finally I'll talk about correlated random effects models which is an application of these cluster means in a normal regression analysis or a GLS or multi-level model. Finally we have two videos about how to test the random effects assumption. So we have generally a set of three tests that we talk about in the paper. We have the Hausmann test, we have Wald test and then we have a likelihood ratio test. I have a separate video about a general Wald test and a general likelihood ratio test but those are general tests so they are not specific to this testing for this random effect assumption. However what is fairly specific or the most well-known test for the random effect assumption is the Hausmann test. If you look at management journals they almost exclusively use Hausmann test for the purpose of testing random effects assumption. Therefore it's a good idea to understand the logic behind that test because its application is more specific. And finally I have one video that gives you a summary of the main takeaway of the paper. So how do you choose an analysis technique when you work with multi-level data and you want to estimate the within effect and possibly the contextual effect or the between effect of a variable. I hope that you enjoyed the paper and if you find these videos or the paper useful please cite that identify for the paper and you can always find the most recent version from here.


My name's Jeevan and I'm currently studying a Bachelor's of Science doing my major in data science. I had a pick one I think it's that it really gives you a good balance of work outside of the classroom as opposed to inside. So doing data science is a really large and wide discipline. You get access to a lot of different professionals in the industry at uni. I've worked as a data science intern at a couple of places during my time at uni. I've been an intern at a footy team. I've worked as an intern in the police force, mortgage industry as well as just sort of student consulting for a company. Every aspect of my work experience has been through someone at uni. I found a lot of usefulness in resume reviews that are being done at Curtin. So I've been given a lot of opportunities by supervisors that I've had in past projects that have put me on into professional experience.


This is about your people. You're scared? Check that down there. Get it down there. I'm just kidding.  Show up in a way that no one else ever showed up in the other store. Does everybody in here get these every single day? Can I ask you a question? Should you guys all be deadly to explaining this? Yes or no? Yes sir. Are you yes or no? What the? That's a problem, isn't it? What are you scared of? You wanna see how fast people answer and then don't answer? Watch this. Do you guys believe you have potential to make more money? Yes or no? Yes. Why aren't you? How old do you guys get? How quiet you get?  Listen, whatever you're afraid of, they're afraid of. Whatever you're not confident in, they can't be confident in it. You're scared? Check that down there. Get it down there. I want you to be scared. I want you to understand what to do. Once you learn a process, you'll never be afraid again. There's two types of salespeople in this world. One that lies and the one that's really good at selling in clothes. Which one do you wanna be? You can sleep like a baby at night if you learn how to sell on clothes. The ceramic tint doesn't mean anything. What means something is this. Look, would you agree that there's quantity and quality, sir? Would you agree that something's right? There's quantity, there's just a whole bunch of them and they're cheap and then there's quality. Would you agree there's a difference between a Timex and a Rolex? There's two different kinds of window tint, right? Our goal is the safety of your body, right?  We take that stuff into consideration. Look, when we're looking for window tint for our vehicles, we're not going with the lowest bidder. It's not our goal. We don't Google cheapest tint. What we do is we Google the safest tint and the one that lasts the longest and that's a lifetime. And that's what you've got. I'm sure you expect that, right? So we're only doing what you would want to get on your own. You don't like cheap stuff, do you? No. Either do we. Why are we talking about cheap?  Oh, what's going on? You have to put that on your car. That's it. Listen, I don't have to do it. It's good for you. That's what selling is. It's good for you, sir. Look, what we've learned is that 95% of our customers, they wanted this prep package. 95% of them were buying. And you know what it was costing us? $3,700. And our customers were complaining that they wanted it and it was just too much money. So we made a deal across the board to put it on every single vehicle so we could lower the cost from $3,700 to $1,899. It saved you $1,700. And what's the safety of your family work? Everything, right? Guys, there's nothing wrong with it. You can sound just like I sound. Some of you guys are taking something out there and you don't believe that you upgraded. You know what you think?  You know what a ripoff is? You're not doing a good job.  You know why you're scaring them off? Because you're not bought in. I'm here right now to get you bought in with the stats show, the door handle, the guard, increase resell value by $3,000 at the end of the shift. I'm gonna ask you a question right now. This package is a total of $1,899.  But you got your door guards that done damage your vehicle and you'll say, man, I thought that guy was selling me something I didn't need. You don't think you need it until you need it. Do you think that's not funny? I don't know if he's saying 71 or... How long? Guys, 50 years, guys, watch this. What we've learned, sir, in the last 50 years is that when a customer comes in to trade your vehicle and getting all the dough for the car means a lot to them. You know what we did is that we took the fact that when somebody buys a vehicle, they want to keep it looking like new for them and their family until they go to trade it. The only reason why you don't have the life that you want right now is because you're not putting the work in, period.  When these people walk in here, right, and they're nervous, they're not nervous about the money. You know what they're afraid of?  I really believe that. And you know what?  Y'all are killing these people's dreams out here. For what? Because you don't get it. You know why you're not obsessed? You know why you're not obsessed with winning and training? Right now you're not like leg shaking.  You know why? Because you haven't thought about what your customers are going through. You keep thinking about yourself. This ain't about you. This is about your people. You take care of them. They'll pay you more than you know what to do. Show up in a way that no one else ever showed up in the other store. You can do it. And the person that's in charge of making sure that happens is you. Which means you've got a freaking change. And you don't have to change because we want you to walk around here and act like you're cool. We want you to walk out of here and go take care of people at a different level. Hey, why are you hiding? I'm just kidding. Don't be so sensitive to me. Hey, don't want to be so sensitive to that. Hey, answer. You guys want to get paid big money? We need big answers. Does everybody get that? And have them believe and understand the number. Do you get it? If you do, what will happen? Get paid. You guys want to get paid? Have answers that support getting paid because I'm certain. Everybody, certainty is the number one thing that a closer has. Listen, you're the nicest guy in the world. No certainty, you're done. Every man and woman should be tested every day. Look, I'm gonna tell you something.  And by the way, if you do, will you let them push you? See, some people won't let yourself be pushed. Only when you're pushed, when you're backs against a wall will you grow. And my wife, she pushed my back against that wall.  It's a mindset shift. You're so talented. And the fact is, is that you won a win.   You need that freaking fire and that pissed offness in you to win. Explain this to you. When you were a little baby, you would cry for something. You'd throw a fit until you got it.  And now as you get older, guess what happened? You want something? You know what? I'll see if everybody else is okay with it.   You want to go kill it right now? That raw instinct you have in your stomach? Nobody's setting the rules on my life. I break rules for a living. I set my own rules. I don't break the law. I break the rules of civilization.  Question is, will you cash the check? You know how you cash the check?  And the only thing you'll care about is being the best speaker in the world, having the best attitude in the world, literally having conviction and confidence and training every day so you can sharpen your sword outworking everybody. And also at the end of the day, it's your mission. Customer comes in, they're buying a car. Nobody's leaving. It's not an option anymore. It's in your blood, it's buy or die. It's not a saying, it's not something cool. That's a quote. We don't just say it like that, we live by it. It is a code and we can tattoo it on our arm. What are you capable of?  Okay, here's what I want to tell you. I don't care what you have right now. What I care about is what are you gonna get? I don't care who you are. What I care about is who are you becoming? Would you guys have believed that honestly, it's about who you're becoming along the way in life? You know what, if I die right now and I don't die with any money but I become a great person, I'm okay with that. Would you guys be okay with that? Yeah. Dude, money doesn't mean anything to me.  Dude, you guys sell cars for a living. Be the best. When people get rich, when time shifts. You're never gonna see time shifts like you're gonna see these next four years. We're all gonna get slapped in the face. But if you're training, you'll be ready. This market shifts hard, trades drop, books drop, everything changes. Good. My competition, I will bury them at that point. They are unskilled. They're running around with heavy wallets. They're average people, no skill, broken mindset now.  Now they don't have the skill to keep up with it in a weird market.  Not a theory teacher. I'm not teaching you like in theory guys, if you were to do this, I could see you doing, well, Andy, how many cars did you sell when you sold? Well, 13, but on my good months, I sold between 16 to 18. Guys, no way. I sold 70 a month every month and I slaughtered them in a small store.


The next talk is going to be by Scott Irwin who is a senior developer in Bloomberg So today we're going to talk about Dunder methods and why they are special So we're going to cover pretty quickly what special methods are Talk a little bit about what the Python documentation calls basic customization Then we're going to dive in and we'll cover some of the Dunder methods some of the special methods there And then we're going to go more into some special cases like callable Look at numerical operators and then finally we'll finish off with protocols or at least a couple of the protocols One thing to keep in mind is there's 40 plus special methods So there's no way I can cover all of those in this talk. So I'm cherry picking a few So special methods, what are they? So special now methods are the name used in Python documentation You might also have heard these referred to as magic methods or Dunder methods And for those of you that haven't heard the Python slang Dunder stands for double underscore the official definition from the Python docs is Special methods are Python's approach to operator overloading allowing classes to define their own behavior with respect to the language operators So one example is Dunder add method, which is called by the plus operator and is defined by various built-in types Such as int float and stir so why are special methods useful to you as a developer they enable you to Give your custom types your classes to have the same features and expressiveness as the Python standard types So one general note is when you're emulating a built-in type You should generally only implement the special methods that you need which is to say if you are in your own application You shouldn't necessarily worry about completeness You should just care about what you need to get your application running now if you're a library writer and you are Accepting things from other people then you might want to pay a little more attention to completeness if you want to block Specific functionality you can essentially set the special method in your class to be none And then that will prevent that type of operation one example would be there's a special method Dunder'd reversed Which allows an optimization for reverse iteration across sequences if your sequence doesn't support Efficient reverse iteration then you could block that by setting Dunder reverse to none so Basic customization so what is the what is in the basic customization? So one of the ones is probably if you've written any Python classes at all you have seen this special method and this basically takes an already obstantiated object and fills it in so this Should not have a return statement because within the language It's a type error to return anything other than none and since in the Python World if you don't have a return statement the default return type of your function is none Best thing to do is to leave the return out One little note is if you have a derived class and you want to make sure that you are Using the base class and initializing there as well you need to explicitly call the base class and it Dunder and it function So that's what this little bit of code down here is showing the the base class and then the derived class calling the Parents class Dunder and it Also in the basic customization is Dunder repper. This is the official string representation of an object If possible, and this is from the documentation if possible, it should look like a valid Python expression This is typically this is the string representation that is typically used for debugging So it should be information rich and unambiguous. So if you have spent any time at the Python Ripple and you've typed a variable name and then watched what the values get dumped out You've invoked Dunder repper a closely related special method is Dunder stir This returns an informal or you could think of it as a pretty print string representation of your object But this is the one that is called by the stir constructor also by format and by print But you don't necessarily need to implement this on your class because the default Implementation that's inherited from the Python base object will call Dunder repper as its default implementation One of the other things that you might want to think about is implementing Dunder bool. This defines the truthiness of the object Generally, this should return true or false But if you're if it if you don't implement Dunder bool The Dunder len method is called so for containers. This is why an empty list an empty dictionary an empty set Return false is because they call the Dunder len method for for those classes And the truthiness is is if len returns zero, it's false if it returns any other value. It's true now if you don't implement either of these methods then all Instances of your class will be considered true and so here in the We have a class swallow and We're keeping track of the state of this swallow and we are only true if we have an unladen swallow There are some additional customizations way too many to go into there's Some more around representations such as Dunder format and Dunder bytes There's what the documentation calls rich comparison methods, which is the less than less than or equal to someone and so forth And then there are some advanced Dunder methods such as Dunder new Dunder Dell and Dunder hash Which you should only be implementing when you really know what you're doing you can get yourself into serious trouble with those three So with that let's move on to callable So the definition of a callable is any object that can be called So it's a little bit of a recursive definition there, but basically it's any object that supports the The paren operator, which is to say it can be called like a function Python callable objects that you might be familiar with are any of the built-in functions Any function that you write yourself is a callable the class objects that you define are callables methods on built-in objects and Methods of your classes that you you define all of those are callable one additional thing and this is where the special method comes in is if you've defined a Dunder call method then Objects of your class are also callable as a function. So what does that look like so informally? What you end up with is being able here We're creating an instance of this multiply by and then we're invoking that instance with arguments just like we would any other function and Where you might want to do this is if you have you want to create a function with state So here we've given it a state of three. So this function always multiplies by three. I Could create other instances of the same class that multiply by something else And I can have all of those active in my system at the same time Next up are the numerical operators This allows you to emulate numerical types by defining these methods So they're the operators the plus minus star single slash and double slash.  There's matrix multiply mod div mod pow left shift right shift and The bitwise and Xor and or if you're not going to Implement it or I'm sorry if you are implementing it and you're not going to support a particular style of argument You should return not implement it.  You should return and not implement it There's also this concept of reflected operators All of the numerical operators have a reflected version. So where we had Dunder add We have a Dunder R add and a Dunder R sub and etc the right hand Operand of an operator is its reflective operation is called if the left hand Operand does not have the supported operation Or returns not implemented. So one of the ways to look at this is if we look at an example So here we have a star B First we'll try to call the mole method on the a object Giving B is the argument if that returns not implemented and a and B are different types Then it will call the R mole method on the B object passing it a as an argument and where you can see this in regular Python is that's how This duplication of string methods work The int doesn't have a mole method that takes a string But the string has a mole method that takes an int. There's also augment augmented assignments Nearly all of the numerical operators have an augmented assignment Which is to say an in-place version, which is where the the I comes in here So we have I add I sub so on the only one that does not have an in-place version is div mod and These are the things that implement plus equals minus equals so on and so forth Generally these methods should do the operation in place, which is to say modifying self and return the result That said well the result could be self it doesn't necessarily have to be self and one of the places where you would see this in One of the basic types is integers the integer instances of integers are immutable So if I do a plus equal operation, it's going to Do the operation and return a new object so if I do 42 plus equals one I'm going to get Not self of 42. I'm going to get a new object 43 There's also fallback behavior if there's no in-place Version available the the operator falls back to the normal method So if your class does not support plus equals essentially it would break down into one of these two where it would do the assignment and Do the add or our ad depending on what the types are here? So an example of that is the stirred class does not implement an I'm all method But it does support the star equals Because of this fallback behavior here There's lots more operators Some of these are These are the unary negative unary positive abs invert so on and so forth If you are interested in these these are well documented in the Python documentation so on to some more Complicated things let's talk about protocols so protocol or Let me back up so Protocols everything that we've seen up till now we could get away with implementing one and only one special method on our class If we wanted our class to only support ad we could do that For protocols these are sets of special methods that we would need to implement in order to fully implement the protocol Python has multiple protocols that you can use to tap into some of the most common protocols are things like collection and iterator They're so common that the Python has a module collections dot ABC which is to say abstract base class that will help you implement these it will guide you towards implementing the the necessary methods to The to implement the protocol So let's take a quick look at those two things. We're going to look at collection first So a collection is a sized iterable container class Special methods for the collection include Dunder iter which returns an iterator for that collection It also needs to support the Dunder contains and the Dunder lend method because remember we have we're supporting sized here So we need to be able to know how big we are So These slides are hosted on github. There is also a Implementation of this linked list class in that same repository Where the where these examples are coming from So here I'm pulling in the linked list I'm instantiating a linked list and then I'm just quickly adding some things here and then I can do things like some on the linked list and This works on my linked list because it's just using the underlying iterator And I can do testing of contains that's what in is calling the Dunder contains and Then lastly lend calls Dunder lend. So what does this implementation look like? so that the Dunder iter just returns an instance of the linked list iterator class with is instantiated with The particular container we're working on right now the basically self of the linked list Contains is just it's just going through the list again. It's using the iteration it's doing the or This is essentially causing an iteration and I'm just searching through And then lastly The linked list class happens to keep track of how many nodes so the lend operation is very efficient in this particular case so a sequence methods for sequence containers They are everything that a collection is plus get item Which is the square brackets It could also include optionally reversed index and count Some additional methods if you're going to have a mutable sequence. So this is like tuple versus list Is set item and Dell item and then there are all there are several more optional Methods that you might need to implement all of these are documented in the collections dot ABC documentation But again, I'm going to Remind you that you should only implement the minimum necessary functionality to suit your application within or your use case within your application for mapping Mappings are also containers. So they start with a collection, but then they also support get item iter and lend But they also Include things like contains keys items value. So basically it should Work similar to a Python dict for additional methods if you want to have a mutable mapping You would need to have set out set Dunder set item and Dunder Dell item And there are several other methods that you could include such as clear an iterator is an object that iterates over an iterable An iterable needs to implement the Dunder iter, which we saw before in the container The iterator needs to implement Dunder iter. It's as well, but it just needs to return itself So if you call iter on Something that is an iterator or it just returns you a reference to itself But an iterator also needs to implement Dunder next and the Dunder next is basically how you step through the iteration and It should return the next item from the container and when you reach the end of the container It should return a stop iteration. It should raise a stop it raise stop iteration and This is the internal workings of Python are very much reliant on this So let's take a quick look at the implementation for the link list iterator, so Dunder iter is very easy to understand the Dunder next is Basically if we're an empty list, there's nothing to do or if we're already at the end of the list Otherwise we move on to the next position and then we return the data of whatever position we're at and This is just conforming to the definition So some examples of iterator behavior So again here, we're just quickly building up a link list and Then we're getting the iterator on that link list and then we're getting the next item and Then we're getting the next item. So next here is calling our Dunder next to make this work When I get to the end of the list I get the stop implementation or stop iteration exception and That is used implicitly by The the for loop if you were to iterate or if you were to do a while x in blah blah you would see that so inclusion We have special methods are pythons approach to operator overloading and They enable your custom types to have the same features and expressiveness as the Python standard types so Essentially what is the Python language has done is exposed the inner workings and Hooks to allow you to write very fully featured expressive code with your own classes References this is a direct link to the language reference and then this is a this is the link to the slides The github repo is basically SJ Irwin or a github.com slash SJ Irwin Which I should have put on the slide, but I forgot And that's it. Thanks I So we went a little fast. So I have time for a few questions for one question if someone would like to Hello, and thank you. Is it working? Okay Just carry on. All right. Thank you for this amazing talk I would like to just ask you one question regards to it You have given us examples of what's what actually caused this next dunder method in under the hood like a for loop Like a while loop at the truck, but I was thinking I think generators They also call when when you when you call a yield for example, it actually caused the next under the hood as well It's alright. Yes That's all. That's all. Thank you Any other question?  I Don't want to embarrass myself or anybody else. I think this gentleman on the end had a question. Oh Same question All right. So If there are no more questions, there is a coffee break for 20 minutes on the seventh floor And there is also going to be a book signing by Ian Oswald So, thank you


Hello everyone, welcome to the what is probably the last presentation for you guys, this session I will introduce the concept of statistical HTA, this is where the STA methodology is moving towards HTA given the lot of complexity in technologies that are lower than 45 nanometers. Although we are not at a stage where we are doing 100 percent HTA, but we are using some of the tools or some of the methodologies that are somewhat statistical in nature. So, till the so I would say STA methodologies are divided into kind of two types, one is still OCE and other is beyond OCD. So, in the last session we discovered what OCD was, what all configuration was and we saw the methodology where we select an we select one operating condition for one run and within that operating condition use timing the rate tool model we want to publish it. Now, this is not we will see in this session that why this is a shorter comparatively shorter presentation, but we will see why this is not good enough or why this is not sufficient or why this is moving out to be lot more complex for technologies beyond 45 and we will see what sort of technology is replacing it. Let us first look at a Gaussian and a normal distribution. So, Gaussian is distribution is a continuous probability distribution that is used to describe real value random value. This is very essential now, this is the concept of random variable is very very essential to the whole process of statistical experience. Now, consider let us discuss a non semi conductor scenario. Now, let us say you go one of you goes ahead and tries to map the height of and you can choose let us say you want to map the height of all the people in one particular city of let us say all males in one particular city. Now, there will be the data will be in number of lakhs of for a for a big metro and you will find that the it is the data is concentrated around an average value. So, it will be a bell shift curve a Gaussian curve which will be the average of it will be concentrated around the average of that. So, this is a random variable the height obviously, is a function of genetics and all that, but when you measure height of a of a big sample size the variable itself becomes random, but it is focused around one particular average value. Same thing happens in fabrication in fabrication let us say for 45 nanometer crosses there are billions of billions of some millions of transistors on a particular chip not all transistors will have exactly 55 nanometer length some will have less some will have more, but again they will they tend to cluster around this is the idea they tend to cluster around a single mean value. The probability distribution formula is this 1 by underscore 2 pi sigma square this sigma is the standard deviation and mu is the mean. So, mu is the mean and sigma square is the variance the measure of width of the distribution the square root of sigma square is called standard variation right. So, you do not need to remember this formula you just need to understand that any such variable in a fabrication process will have a random distribution in fact not it might not have a completely random distribution, but it is being modeled as such we are modeling it is an approximation again see the idea here is that continuous what we call as CPD is the used as a first approximation the variable under group we might also have a different kind of distribution, but most of the variables that affect the performance of the chip like panel when the place of the oxide and so on they can be approximated as a possible distribution there are other probability distribution also, but we are we will be focused on the normal distribution the graph is something like this now on the upper hand only in the upper half of the slide you can see three normal distributions this means mu is equal to 0 once the the blue curve is this one is mu is equal to the the mean is 0 it is centered around 0 and the standard deviation is 0 point. So, variance is 0.2 standard deviation will be square root of that the the red one is again mean is same, but variance is a bit more the third one the yellow one the mean is again 0, but the variance is still more you see that that the greater the variance or the greater the standard deviation the wider is the first what it means is that standard deviation is a measure of the total bit the bit of the Gaussian curve the green one here is the the mu mean is minus 2 and the variance is 0.5. So, as a as an engineer working in fabrication the idea is to make sure that your the standard deviation is under control because the greater the standard deviation the greater is the variance that is what it literally means right. So, let us say you are examine the yellow curve let us say this curve depends the channel length of n most devices. Now, this is not what you want you do not want n less is average is 45 nanometer instead of 0. Now, this kind of wider distribution we do not want because this is telling me this kind of curve is telling me that yes there are. So, this is number of this is here this is the probability distribution right or you can even say number of devices. So, if number of devices the ok yes there are maximum number of devices at 65 nanometer, but a lot more devices are showing channel length which are greater than 65 nanometer and less than 65 nanometer and all and the curve is pretty wide right we do not want that we want a curve of this kind which is sharper less wide which has less variance less standard deviation this is what manufacturing price to control right. Now, one more interesting statistic is that if you take area around the the mean value within one sigma within one standard deviation 68 percent of the area under the curve is within one standard deviation 95 percent of the area is within two standard deviation and 99.7 area is within three standard deviation. This is the fact the third one 99.7 percent area is within three standard deviations this is the idea behind the corner based analysis or SSPA book that is we try to find a corner base STA which covers up to. So, let us say you plotted the device. Now, the minus 3 sigma will be faster devices plus 3 sigma side will be slower devices. So, if you cover if you want to cover almost if you want to have the yield which is more than 99 percent you will try and sign off at plus minus 3 sigma this is the important figure here plus minus 3 sigma this is important here. So, we will look let us go to the next slide. So, the idea is whatever corner is chosen for corner base STA there is one slide which yeah. So, this is this this is the slide I am talking about. So, corner base STA we should try to choose a corner which covers up to 3 sigma slow corner on the plus 3 sigma side plus corner on the minus 3 sigma side this is an example I am doing because there are hundreds of parameters in public this is one parameters where we have plotted channel and number of samples again we get a Gaussian curve. So, we will get something like this we will get a curve something like this around a main value and now we are choosing a corner somewhere around there and here and this is the way we target that my yield should be more than 99 percent almost or rather almost 100 percent. So, the yield is never 100 percent but this is the idea right. So, now let us talk about let us talk about process variations how many types are there and what what do we model how and how. So, process variations are of two type two type systematic and non systematic again systematic non systematic so systematic are the ones which are I would say they are problems in the fabrication process for example, they are they are something which are not acceptable something like saying that the thickness of the oxide is lower than some critical limit and or the channel length is beyond a particular permissible value. So, systematic process variations are not handled in a they are handled in the fabrication process fabrication process should be corrected to get rid of these right. Now, we come to non systematic non systematic are the ones which S S T A or S T A put it in S T A tends to model right, but we try to model these non systematic variation.  So, it may happen again there are systematic variation non systematic version within die that means, are a meter affecting the performance of different devices different right. Now, again the derivative within die are of two types which are specially correlated another independent for example, let us take two two parameters let us take the channel length of the CMOS and let us take the thickness of the oxide. Now, these two parameters if they show no correlation to each other that means, the distribution of one is entirely independent of distribution of other then they are independent, but if we figure out that in a particular area the devices that the CMOS devices that have high channel length for example, they also have more thickness of side then they might be specially correlated this is very important for S S T A. S S T A needs to know whether the parameters in question are the independent or are the specially correlated right.   So, let us say there is some issue with the some issue with the fabrication where in the die is on the corner have slower in MOS devices it can happen or slower CMOS devices that means, that all the PMOS on the corner if are slower this is a die to die this is an example of die to die variation because all the PMOS are generally slower than the compared to the die on the center of the group right. So, here is one example where we plot number of samples and we plot a parameter called EP 1 we get a Gaussian curve. Now, in practice G for example, the example is that G 1 parameter may correspond to the device threshold the V t value for a standard PMOS right. Now, this is we already know that G 1 GP 1 is a global.  Now, let us say for a different die you plot GP 1 again it might look like this, but slightly shifted the distribution is same almost same, but the main may be slightly shifted.  Now, non statistical STA is also called deterministic STA. So, in this case or what we so in this case the slow process model will belong to the plus P sigma comma, our process model will belong to the minus P sigma comma. Die to die variation is handled in deterministic STA by assigning a particular corner a worst case corner or a best case corner. What will that worst case corner will be? Now, let us say let us look at this curve a bit differently. Let us see that this curve assume that this curve is GP 1, but it is now number of samples is the number of die. So, the parameter of GP 1 is nothing, but the average value of GP 1 across number of dies across number of die. Let us say I chose I I plotted this GP 1 across let us say 1000 dies.  Now, I choose a plus 3 sigma corner and a minus 3 sigma corner and do deterministic STA. This will ensure that all these samples are captured in my STA right. So, this is where deterministic STA does the corner represents. So, that is why we call in corner base STA we call the operating condition to be a global corner right because it corresponds to global values right. That is what we discussed right that is why we discussed in the different sections of our series wherever we talked about operating condition is that operating condition represents the worst case scenario across all dies it is a global corner the process SS corresponds to the worst case from a worst case condition and that is the plus 3 sigma condition. Similarly, fast case represents the fastest condition fastest where a particular parameter will be into a fastest device across all dies. So, this is again a global corner.  It refers to the process parameters which can differently affect devices on a given die.  So, it is intended to capture the random process variation within the die the process even if the fabrication process is correct is absolutely it cannot be perfect. No process can be such that it will manufacture millions of parameters on a particular die which has the same parameter right. So, this is the graph where global variation obviously is a much wider curve and within this this lesser we have we got the delay a number of samples. So, global variation would be a much wider curve obviously, because it is a cross dies it takes into account lot of dies the local variations can be let us say for this curve can be for one particular die this curve can be for another particular die this curve can be for some other die.   Within die variations we saw that there are two types purely random the one effect is independent of other second is specially correlated. Processes tend to affect the imperfections in the processes tend to affect closely space devices in a similar manner if such thing happens then it is a sparsely correlated body variation this make them more likely to have similar characteristics than those placed far apart right. So, please remember these two things random is completely random of each other correlated ones they are dependent on the proximity. Similar devices in a very they are that are closely spaced will have similar variations right random are not related to each other. So, some of the effects can be purely random some of the variations can be linked to one another one another one another right. So, this is the essence of the local variation there are two types random and specially correlated. Now, we have already discussed what corner based data tries to address the global variations right and what about local variations local variations are taken care by the by the OCB we will see. So, now the problem with corner based FPA as we go deeper in as we go smaller and smaller is that the variations are now there are no so many types of variations which we cannot ignore. There are metal variations which can range from minus 10 percent to 25 percent environmental variations voltage island and low power devices, alloy drop, temperature rise for T MBTI this is negative bias I think this is the MBTI stands for I think negative bias pressure or something there are hot electron effects these these effects are not they were negligible for 90 nanometer or more, but as we go smaller and smaller these effects are now very much renowned. Again VT and TOX tracking hardware and modeling uncertainty mathematical errors, NLP mistrack fast rise slow fall fast fall slow run PLL. So, all these these variations that were earlier very very small are now becoming bigger and bigger. So, if you want to in a corner based STA if you want to make sure that you take care of everything you you count all the corners then it says some 2 to the power 20 timing run I guess maybe yeah because how many 1 2 3 4 5 ok I am not sure where 2 to the power 20 comes from, but the guard band is minus 65 to 80 percent because a huge guard band you cannot verify this with corner based STA perfectly. So, if you make sure if you let us say you will somehow one or one way or the other you will miss out one particular corner that part I am saying earlier I used to do STA on two corners corner based STA now I am doing STA on 6 to 8 corners. The corners are increasing because of these this variation right because of so many variations earlier the variations like device particular not even of any consideration right. So, this is where the problem arises. So, let us look at the corner based analysis and see how it it tries to model the the local variations we saw that we saw OCD that OCD is a way to model the local variations and how does it do. So, now let us say I am working in a you know in a session where OCD is set and timing the rate is also set right. So, let us consider this part of postage part. So, each delay here each AND gate here has a typical delay which comes from the library it has a min delay which is because of the exact timing delay command we have applied for OCD again it has a max delay because of the timing delay term. So, it each of the gate has min ticker max delay cumulative this ranges to we will add all the min delays we will add on the typical delays we will add on add on the max delay. So, this is min delay reported this is max delay reported what the basic ST analysis is conservative in the sense that it is overestimate the delay of long counts why because it is assuming that all 4 AND gates are at their slowest. For example, when it computes the max path it is assuming that all 4 AND gates are slowest. So, this slowest delay is 0.0.2 for whole path it will assume that all AND gates are fasted right. Therefore, but what is the reality? Reality is this may be fast, but this may be slower or this may be slowest and this may be again fast this is the reality because of the local variations not all the devices will be slowest. So, this is why we say that it will overestimate the delay of long count. So, let us say delay the actual delay will lie somewhere in between it will lie somewhere here may be, but it will overestimate the delay on the max file it will underestimate the delay on the min file. This makes the analysis safe, guaranteed net design will function at least as fast as predicted on the set up side and will not suffer from full time on it. So, this this is the guard band which is very wide because it overestimate the delay of the long path max path and this will be the delay of the min paths. This is the way it makes sure that the analysis is safe from the performance point of view and there are no full time positions right. This is why we say that corner base SPA and most of the cases is pessimistic right ok. So, traditional STA is deterministic means that it tries to define a corner it tries to that is the flat value is either positive or negative and there is only one value that is why we call it deterministic. Traditional STA will tell you whether the path is met or valid that is it. It computes the circuit delay for a specific process condition because it is a corner base STA all parameters that impact the delay of the circuit gate length oxide thickness etcetera are assumed to be fixed and uniformly applied to all the devices. Operating voltage and temperature are uniformly applied because we choose a corner for that the device gate length and even oxide thickness these are not direct these are not these do not influence the STA directly these are part of the the PVT. So, this is operating voltage is V temperature STA oxide length and oxide device gate length and oxide thickness are part of the PVT. It takes care of the global variation by creating multiple corner files and no statistical way of modeling within diverse variation. There is a way OCV is a way OCV is a way, but OCV is not not statistical in nature OCV deterministic means OCV assigns fixed guard band and which tell us that whether the timing is met or valid it is not it is not not a statistical way of modeling what it means it means that the effects the physical effects they are statistical in nature, but the modeling is not statistical we are using a fixed guard base guard band base technique to model the statistical physical modeling. What is ideal? Ideal is what if we could model the variation which is physically statistical also in a in a tool in a tool can we also model them as statistical let us see this is what what SSCA tries to do it models non systematic variation as random variables. Remember non systematic let us go back and see the categories again. So, it only models non systematic right not the systematic systematic as I told you is a has to be corrected in the flow in the in the fabrication process itself. These variables can be uncorrelated partially correlated or perfectly correlated and deterministic STA and SSCA differ in the way they treat correlations. This is the new thing about SSCA SSCA deterministic STA will assume that all the variables are correlated right because it assumes that for example for maximum it assumes that all the gates have maximum delay. So, it is assuming that all the parameters or non systematic calculation all the parameters that result into a device being slower are applied at the same time. So, they are all perfectly correlated for example, go what happens let channel length is bigger vt is higher and all the both these will cause a device to get slower right. So, it assumes that all these devices have more vt all these devices have more channel length. So, it assumes the worst for all the devices for non systematic calculation for best for best mean delay calculation it assumes the best condition for all the devices. So, it assumes that all the variation that are causing causing the all the all the parameters that are causing the variation are perfectly correlated. This is where SSCA is different SSCA tries to model the variables as it can also model the variables at perfectly random that is uncorrelated, partially correlated or perfectly correlated and this is what happens in the real world this is what happens not all variables will be perfectly correlated this is what SSCA models right. So, let us see correlation let me first clarify a couple of things about correlation. Correlation represents the statistical relationship of two or more random variables or observed data values. For example, what is the correlation between height and two types of a person the correlation would be pretty high they are perfectly correlated if the correlation is 1. So, this correlation I am not sure what the number would be, but it will be higher maybe it will be at a 1.8 to 0.9. The taller the person is the greater his shoe size demand of a product and its price this is also correlated supply and demand go hand in hand if the demand of the product is more the price will be higher if the demand is less its price will be lower. What about third weight and IQ of a person obviously not correlated IQ has nothing to do with weight. So, they are they can be either very there can be either very less correlation negative correlation or perfectly random these weight and IQ appear to be perfectly random. Correlation does not imply causality what it means is that a greater shoe size is not not caused due to a greater height alone right. They are correlated means they move together does not mean one causes another right. Now, let us see so now the what what we will do what SSG will try to do it will model the delay of a single path in terms of mean and standard deviation. So, this is the formula. So, it will the delay of a single path the n is the number of stages standard deviation increases as n increases right. So, as the number of stages increases the standard deviation increases row is the correlation row is 1 the effect adds up as a number of stages in p row is 0 the effect can cancel each other as a number of stages in p. Now, let us see one example what it means is that. So, so look at this path it is a multi stage path 1 2 there is an n the combinational stages MCP if let us say for a particular device now I am calculating for a particular device let us say for device 1 for for this this one I know the standard deviation I will know the standard deviation easily this this data can be calculated by SSG obviously, we need some data from boundary also, but let us say we know the standard deviation of this. So, in a perfectly random case where the let us say that the delay of this device is independent of the delay of this device in this case the square root law follows that means, sigma square TPP is equal to sigma square 1 sigma square 2 sigma square 3 say is sigma square MCP assuming the sigma square of T9 is same sigma is same for all the NAND gates which is possible for all the NAND gates will show same sigma sigma square TPP is nothing, but N into sigma MCP into sigma square T9. So, we rearrange and we find that this particular sigma. So, standard deviation is calculated as sigma so ok. So, for a particular delay of a single path n stage path you will have two values one is the sigma other is the mean mean is nothing, but the addition of mean delay for each of the cell each cell in the stage right. So, if you have N NAND gates in this example the mean will be will be simply n into the average delay of the typical delay of 1 NAND gate. Sigma now the calculation of sigma depends on whether they are correlated or not. Now, we will assume for now that delays are perfectly random they are not correlated that is delay of 1 because of the process parameter variation will be independent of delay of 2. So, in that case sigma of a of the total path will become 1 by a square root of the total sigma. So, it is it follows the square root law. Let us see some example now please note we are considering this case we are considering the case where rho is equal to 0 where the effects tend to cancel each other. Now, let us see a path let us see 50 let us say you have 50 gates each end 21 means 20 is the mean this is the new value this is the new value and 1 is the sigma. Now, in a in a deterministic SCA your regular prime time run you will find that the NAND delay would be. So, the OCV would represent the 3 sigma. So, that is why we multiplied by the this 3 is sigma is a sigma value of sigma is 1. So, OCV and determinant deterministic SCA will try and limit the guard band between minus 3 sigma and plus 3 sigma. So, the worst case delay would be mean plus 3 sigma which is 23, mean delay would be mean minus 3 sigma which will be 70. If they are perfectly correlated then this is for every gate each gate will have max delay of 23, mean delay of 17. If all that gate delays are perfectly correlated which means which is what is assumed by a OCV method all of them will show worst case value for max max top that means then total max start delay would be 50 gates would be 50 into 23 or it would be what is the mean of mean value of 50 gates combined with 1000 20 into 50 what is the sigma value sigma value simply is the addition 50 into 150. So, or it will be 1000 plus 3 into 50 mean plus 3 into sigma both from both cases the value is same this is what deterministic SCA does right. It would assume worst case value for every gate, but in real it will not happen. In most of the cases the delays some will be fast some of the gates will be slower and the steps will tend to cancel each other out over a long path and that is mathematically modern by the square root law. Now the sigma will not be 50 for the combined path the sigma will be square root of 50, sigma will be square root of 50 according to the random variable loss. So, it will be 7.07. So, what is the max part delay it will be 7.21. This is what we mentioned we say that the deterministic SCA will overestimate the delay of long path overestimated 1150 whereas, in SCA we found that if we assume the delays to be random perfectly random we get a value of 1021 this is less this is I would say this is more accurate, but obviously, there are some conditions we have assumed that all the variables all the gate delays are random of each other right ok. So, SCA removes specimen worst case process corner will be determined by this these are die to die variations these are sister these are systematic variations these are random variations worst case product corner potential. So, we do not the SCA does not target die to die which is or does not target systematic it only targets the random effects that is it it only targets this effect random effect nothing else. So, rest all the things remain same for die to die the corner based SCA use the corner operating condition for die to die same thing will happen in SCA, but what about the within die within die random to this SCA will only reduce specimen from within die random variable instead of square of random sigma I mean sigma square of random it will do 1 by NCT that means, it depends on the particular path how long is the path the longer the path the more more pessimist it will remove the shorter the path the less pessimist it will remove because the pessimism builds up as the path stage number of stages increase right ok. So, do not worry if you do not understand when you start working in industry you will obviously, come a profit. So, ideal SCA system the effect of a particular variation on delayed model statistically correlation is identified this is the most difficult and most challenging step of SCA the correlation is identified between variables and this is where the thinking is changed slack is not a deterministic value, but again a probability distribution it does not say whether your timing is met or say it says that your timing is met with this probability it is a probability distribution. So, a statistical timer engine a part. So, a static timer a normal time time static timer engine needs net list plus assertions is just constraints delay and slew models what it gives it gives you the slack value right it gives you the slack value and it gives you some method to do diagnosis what SCA adds over it. It needs statistics of the sources of variability it needs some data from foundry it needs those mean and sigma values for this the the process variation and it also needs the dependence that means, how are the variables correlated this is the most difficult part the foundries do not have they have no good way of giving this data they are not ready to give away this data very easily. A lot of testing would be involved and apart from giving the slack it also gives it actually gives the yield breaking it tells us that this is your yield with this particular timing violation this is your yield right. So, it tells us that obviously, the path that is shown a to us as violated will probably not violate at a typical corner even if we do not solve some timing violation we will have some amount of yield although it will be lower. So, this will give us the yield number also some yield number right. Example let us say we see the example of channel length variation tool needs information on distribution of channel length tool calculates the distribution of gate length right. So, parameter is this distribution of p and it will calculate the gate delay tool will calculate the gate delay a lower channel length will have less gate delay a higher channel length will have more gate delay the mean will correspond to some typical length right. So, if we give the tool the effect of channel length variation and we tell the tool that what is the formula to calculate delay it will calculate the delay from the channel length variationdistribution this is what the ideal SST system will do. So, a delay report for SST will look something like this for every gate it will have a mean and a sigma value and combined it will give you a part delay this is the part delay. So, it will give again a mean and a sigma wrong and it will give some kind of a graph like this there this slack curve is again a normal distribution and you say that ok at minus 3 sigma the slack is minus 0.12. So, if you want to sign off till minus 3 sigma you will have to move this curve on the right side you will have to make the sixes right you will have to make sure that minus 3 sigma value is 0 only then you can say that I have signed off my trip for minus 3 sigma right. So, this is where SST differs it gives the yield numbers in terms of sigma value. So, here what is the yield the yield is somewhere between minus 2 sigma and minus 3 sigma somewhere between 95 percent and 99 percent. So, it gives for every part it tells us what is the sigma what is the mean if it is mean minus 3 sigma or mean plus 3 sigma depending on whether it is a perfect part or a whole part if it violates. So, you can report timing up to 0 sigma up to 1 sigma. So, report timing 0 sigma mean you get only the mean value you can report timing plus 3 sigma for set of case you can report time in minus 3 sigma for whole case for example. So, this is how things are done in SST so, it is a so with the increase number of what is the mean with the increase number of corner pessimism is increasing if there is lot of pessimism then you are unnecessarily wasting your time and energy in solving paths with greater pessimism SSCA will reduce the pessimism for random process variation and it will help you in closing the timing much easier that the process becomes much easier. Obviously, there is a shifting thinking earlier we thought in terms of flat being 0 now we think in terms of flat being met till 3 sigma or minus 3 sigma and so on. So, this is the difference these are the references I use to make the presentation you can you can go through this if you want if you are much more interested in this topic I will just now seek about a couple of things which are not there in the slide. So, what is the situation now in present day SSCA is not being used 100 percent we in last session we saw that there is an advanced version of OCD called OCD and there is also one more one thing called TOC. So, AOCV and POCD both they try to bring some advantage of SSCA into a regular STA tool how do they do that for example, in AOCV there are two things now it replaces OCD and it replaces by two things one is the number of stages. So, in case of AOCV the delay of a particular path will depend on the number of stages in a particular path and it will also depend on how far are these cells away from each other. So, prime time needs two tables one is the STA stable. So, what happens in STA stable? STA stable happens it mimics the SSCA standard deviation calculation that table what it does the number of as a number of stages increase the rate will decrease. So, let us say you have two number of stages two the rate will be let us say 1.0 if the number of stages are 10 the rate will be 1.0 it is mimicking the standard deviation to a root formula of SSCA. We what it is telling us that if the number of stages increase the random effects will kind of cancel each other out right. So, the rate will be lower then you have to remove more percentage as a number of stages increase this is the way how random variables are modeled in AOCV. The second factor here is it needs a location based table that needs that ok if the two cells are far apart. So, the table describes that that ok if you are this much far apart then this rate will increase or decrease. So, now it is modeling the correlated variation correlation of the variation it is saying that as the if the cells are closer together the rate will be less if the cells are farther apart the rate will be more. So, the cells that are close to each other have less the rate and therefore, less delay the cells that are farther from each other they will see some of the effects which are specially correlated. So, the delay is more. So, there are two factors one is the location based the rate this is called location based. So, AOCV is combined of two things location based the rating and path based the rating both location based the rating tries to model the specially correlated variable and path based the relation tries to model the random variables. So, this is how we are taking. So, right now since we are not 100 percent into SSCA we are taking the good things of SSCA which are which can be modeled easily inside a regular state rule and we are the and the tools the EDA companies are trying to reduce the things. So, once you are comfortable with this course once you are comfortable with SSCA you can actually try your hand at AOCV or even POCV POCV slightly different variation over AOCV. So, you can read more about it there are these are the resources about statistical STA and unfortunately I do not have any lab which shows the lab is not easier to model because you need lot of data you need some tables which I do not have access to. So, you can read about this is a very nice article the good bad and the statistical the first one you can read more about it and but for all the practical purposes you will be using OCD for some time and then when you go into industry you will see that you will start using more and more of AOCV and POCV. Thank you.


This, as you can see, is a vintage Star Wars comic book. This is issue number 16, published in 1978, only a year or so after the first movie came out. One of the things that I really love about these early Star Wars comics is, up in the corner, the thing that they used as their call sign, if you will, for the Star Wars series was this crazy off-model drawing of Luke Skywalker. This is what Marvel Comics did with all of its series back in the day. They would have a rectangle in the upper left corner where the price and the book number was with a drawing of the main character of the book, and in this case it was Luke.  So this was on the very first issue of Star Wars at a time when the series was just starting out. Lucasfilm wasn't that concerned about controlling everything. It was just kind of a lark. Marvel had already been doing these these quick knock-off movie adaptations with Planet of the Apes, which turned out to be a surprise hit and a surprise seller. So they were doing stuff like John Carter, World Order of Mars, and Kill Raven, which was a War of the World sequel. They were doing Tarzan as well. I think this may have been a Kill Raven drawing, an adaptation of a Kill Raven thing. Anyway, I've always loved this thing. The edges of the book have been cut off here, so the number isn't showing, but this is issue number 16. It's dated October of 1978, which means it would have been on the shelves in August, maybe even July. Back in the day, Marvel and DC Comics had this running competition going on where they were always trying to show their publishers and their investors that they were publishing books earlier than their competition, so by around this time they were putting books on the shelves with cover dates that were two, three months ahead. So you should keep that in mind when you're dating books from this period. If it says October, that means it was on the shelf in August or July. This book would have been on the shelf maybe 15 months after the movie first hit the theaters, which was in May of 77, so the movie was still brand new, but there were these new stories, new Star Wars stories coming out from Marvel Comics. The writer of the series was Archie Goodwin. The first artist on the series was Howard Chacon, who drew the first six issues, which told the story of the movie, and a couple of issues after that, but then the regular artist became Carmine Infantino shortly after that, whose work I never liked. He was a real turnoff for me. But this issue, for this one issue, the artist was this newcomer named Walt Simonson. The interior art doesn't so much have Walt Simonson's signature style, partly because he was new then, but mostly because I believe it was inked here by Bob Vechek, who was not known for allowing the penciler's style to come through, to show through in his work, but the cover is Walt Simonson all the way. I mean, if you're familiar with Walt Simonson's art style, you can see it, even back then. He already had his unique signature here, which you can see down the side. Anyway, let's talk about what was going on here. Marvel Comics did something really smart and really interesting with the Star Wars series. The first six issues told the story of the movie, but then after that what were they supposed to do? The series from the beginning was such a huge seller that of course they were going to continue the series. And Lucasfilm very very quickly decided there were going to be movie sequels, but in the meantime what do you do? Archie Goodwin, who was giving the assignment of writing these things, he realized very quickly that with Lucasfilm planning new stories for the future that Luke Skywalker and Princess Leia and Darth Vader were going to be really hard to write important stories for. And Obi-Wan Kenobi was dead so he realized that the place to go with writing a serial about Star Wars characters was Han Solo and Chewbacca. Because with these guys the sky's the limit, you could write anything. This character here that Archie Goodwin created, his name is Valence he is a mercenary, he leads a team of mercenaries who bounty hunt or do whatever they're paid to do. As it points out here in the corner, this particular mission Valence is paying for himself.  He hates droids. He hates robots in particular, but machines in general and what he's rating here is a hospital, a remote hospital. He's killing all the medical droids and in particular he goes to the records room and destroys the records computer. Why in particular would he do that if it's really droids that he hates? A couple of his men they come across this doddering old man in the hospital. As he's mumbling to himself he reveals that his name is Don Juan Quixote and this is a character that Archie Goodwin introduced right after the first six issues with issue seven. See he can't use Obi-Wan so he creates this Don Juan character.  He's not a Jedi but he thinks he is. And he becomes involved in a story starting with issue seven where Han Solo and Chewbacca and a group of other mercenaries, seven of them, go to protect a small town from pirates and from the empire. It's a magnificent seven pastiche. Like I said Archie Goodwin realized that this was the direction to go. He could do anything. But these guys hear this old man mumbling about Han Solo and they say wait a minute Han Solo every bounty hunter in the galaxy knows you can make a lot of money if you kill Han Solo. So they take off looking for this old man's compatriots who he names in his delirium who of course are the friends of Han Solo, the green rabbit named Jackson, and the lady dressed like a vaudeville hooker named Amazza. So they have to take off to meet up with the kid that they had saved before who is not Luke Skywalker by the way. They're not far in front of Valence and his pirates. A side note here. I'm going to ramble some more. The letters page here starts off with somebody asking hey what happened to the letters page why haven't you had a letters page in recent issues. There's a surprisingly candid response here. It basically says that the Star Wars comics have been selling so outrageously well, much more than they expected, that they decided they need to sell ad space in the books and they gave up the letters page for a little while. I thought that was surprisingly honest. And then they go on to point out that Archie Goodwin has a habit of being O.W. which means his books are L.A.T.E. So anyway, they have a bit of a firefight with Valence and his crew.   But then he takes off leaving them saying whew I wonder what that was all about. At the end we see that Valence is a cyborg. That's why he hates robots so much. He was badly injured when he was a trooper with the Empire. His life was saved in a remote hospital where they replaced almost half of his body with machinery. And yes it was that same remote hospital and that's why he destroyed the records. He has an obsession with destroying robots and with destroying records of his past. Interesting character and I don't know that he was ever seen again. But this was an example of the kind of thing that could have been with Star Wars. Three years later when Lucasfilm kicked into high gear and got serious and Empire Strikes Back came around. All of this real creativity early on kind of had to stop. This expanded universe stuff that nobody talks about anymore and nobody seems to like. At the time was very entertaining because we didn't have anything else. There was the one movie and the comics. The novels hadn't really started yet.  Please remember to press that like button. It helps my videos get seen and then subscribe so you can come back next time. I do science fiction, book, TV and movie reviews all the time and please consider becoming a patron. There's a link in the description below.


What's up everybody Jason for Jasper's case base calm 2019 20 panini opulence basketball one box break half case break Random teams number 30 just sold out all 30 spots in all teams in good luck guys Here's the dice really is a customer name so from Roy down a robbery guys got those straight up and then hang from Donner's 11 Down to Don a Donner's 12 got those in a pack for the second. Congratulations guys. Here's the teams Let's roll it and we got ourselves a two and a six eight times. Good luck one two three four five six seven and eight Roy down to Michael two and a six eight times one two three four Was it eight times? five six seven and Eight eight Magic down to the nuggets. Hey, what's up Joe? Piz? How's it going man? So Roy you have magic Robert with the Bulls Donnie with the Suns Allen with the 76ers Robert with the 70s a T-Wolfs are Skull with the Raptors Jeremy with the Wizards Robert uncle with the Pacers and Rockets Matt with the Kings Brian with the Knicks Michael with the Hawks Roy with the Jazz Donnie with the Bucks Robert with the Pistons Danny with the Thunder Robert with the Celtics Nets Michael the Warriors Michael Sorry Scott with the Warriors Michael P with the Hornets Robert with the Lakers as well as the Heat Roy with the Spurs Scott with the Clippers Robert with the Blazers Hank with the Grizzlies Jeremy with the Cows Allen with the Pelicans and Michael with the Mavericks and Denver Nuggets Nice. How's Arizona buddy? I was easy right now. Is it hotter already? Is it in the hundreds? All right guys, anybody want to trade heat pull heat Bulls Lakers Bulls heat Lakers for Grizz or Pelicans Robert saying Jullbreaker All right, you guys I'm gonna close the trade window then back of envelopes Try to trade could a trade mojo. That's right. Oh You know, I'm a Thunder fan, but hey with LeBron and a D healthy, I don't know JP More harder than it used to be 2 out of 39 for the Pelicans Brandon Ingram Pelicans with that one that is Allen Kenny Smith 6 out of 10 for the Houston Rockets Robert Runkel There you go. Well out of the ordinary last-year JP. He was really healthy Ad was and LeBron hasn't really had a major injury This is probably the longest he's been out like in a very very long time. I'd have to say Christian Leitner 7 out of 10 Washington Wizards Edition going to Jeremy. We have buddy healed for Sacktown 9 out of 10 for the Kings gonna Matt Arnold and try to trade couldn't trade mojo Cam Johnson little rookie patch autograph three colors And that is 32 out of 79 For the Suns and Donnie Donnie burger Redemption and we got an all-star team LeBron booklet LaMarcus Aldridge 63 out of 79 That is for the Spurs San Antonio Spurs that is Roy. Let's look at the redemption guys. Good luck. We got ourselves a Patch autograph was a no vu rich Card number 11. What number is this actually? I'm very curious now so no vu resh and that is I Guess they're all gonna be at a 49 or 25 Gold is at a 10 holo gold out of 5 and platinum one on one card number 11 Tyler hero. How about that? There we go So usually it's Jersey number to 99 or parallel cards is Jersey number out of 99 and then so number 11 Tyler here will be out of 79 There you go. I Wonder if these are just the normal rps. Oh, yeah, these are just the normal rps like this There you go Tyler hero for the heat Robert Ronkel try to trade couldn't trade mojo There you go, so that's just an antsy mojo right there and there you go everybody That was the break So Tyler here will count Johnson our PAs Christian later and Kenny Smith and a little Marcus all just booklet patch So there you go guys. That was opulence basketball one box half case break round of teams number 30 Jasper's case breaks comm


Imagine if someone told you, I have a stalker, would you consider that a good thing or a bad thing? Probably a bad thing. But there is one situation where you would want a stalker and we're going to talk about that today. Hello everybody hooded Cobra Commander 788 here. This is the show where I re-review every vintage G.I. Joe toy from 1982 to 1994. Thanks to Hans Chow for the title card image. Really great work. I love it. Who is your favorite G.I. Joe? What character stood out to you? What action figure did you always include in your play battles? For me, there is one answer to all of those questions and that action figure is the subject of today's review. Stalker was one of the original G.I. Joe's from the first wave in 1982. He was a leader. He was a ranger. He was a vital character in the mythos of G.I. Joe. Today this ranger will lead the way. HCC 788 presents my favorite G.I. Joe in his original form, Stalker. This is Stalker, G.I. Joe's ranger from 1982. There are two figures here which means we are going to look at two versions depending on how you categorize them. All the G.I. Joe figures released in 1982 were re-released in 1983 with updated articulation and parts. When 1982 releases are referred to as version 1, also called Straight Arm, the 1983 releases are referred to as version 1.5, also called Swivel Arm. I will explain the differences later in this video. The Straight Arm Stalker was released in 1982 and was available only in 1982. The Swivel Arm Stalker was released in 1983 and was also available in 1984. It was discontinued for 1985. It was available through a mail-away offer in 1986 and 1987. Overstock mail-away figures were sold at the 1992 G.I. Joe convention. Larry Hama, the writer of the G.I. Joe comic book series, implied Stalker was based on his friend and colleague Ed Davis. Ed Davis served in Vietnam on long-range recon patrol and lost the use of one eye. He was a gifted artist and a member of Neil Adams' Crusty Bunkers at Continuity Studios. According to Larry, the last anyone heard from Ed Davis, he was heading to Central America to work as a mercenary. He never returned. There are variations of these figures. The Straight Arm release had a Thin Thumbs and Thick Thumbs variant. The Thick Thumbs variant also had lighter camouflage. The Swivel Arm mail-away and convention releases also had lighter camouflage. Shown here are the Thin Thumbs variant of the Straight Arm figure and the standard release of the Swivel Arm figure. There were other versions of Stalker released in the vintage era. Version two was released in 1989. He came with a big kayak. Version three was in the Talking Battle Commanders set in 1992. Version four was in the Arctic Commandos mail-away set in 1993. And version five was in the Battle Corps in 1994. Stalker is billed as a Ranger. U.S. Army Ranger School was established in the 1950s in the early 1960s during the Vietnam War. The U.S. Army deployed long-range reconnaissance patrol or LRRP units in Vietnam. In 1969, those units were designated as Rangers. This tracks with Stalker's backstory in the comic book. He would have graduated from Ranger School before serving in Vietnam. Ranger is denoted as his specialty, but most of the Joes would probably be Ranger Qualified. Some other notable Rangers or Ranger Qualified personnel for GI Joe would include Scarlet from 1982, Beachhead from 1986, Repeater from 1988, and although it's not specifically mentioned on his file card, Snake Eyes was probably Ranger Qualified as well. Stalker is a name that has not aged well. The word Stalker did not have the same negative connotation in 1982 that it does today. This makes a live-action version of the character unlikely, at least with the same code name. The light green plastic used for Stalker is very fragile. Something about that light green pigment made the plastic very brittle. Other figures from 1982 made with the light green plastic were also notoriously easily broken. That includes zap and stealer. If you have one of these figures, be very cautious. I would not move the joints very much. It would be very easy to snap off an arm just with the friction of moving the shoulder joints. I would also not put the figure on a figure stand. It would be very easy to crack the heel off. I'm more careful now with my figures than I used to be. I used to display Stalker on the Manta. I used to jam that foot peg into his foot. It's a miracle I didn't break it. Don't follow my example. Take care of your toys. Stalker was a popular figure and had many post-vintage and international releases. Here are but a few examples. This version of Stalker was released in Japan. GI Joe did not have great success in Japan, but did see release there. Thank you to Chris from Comic Tropes for sending this Japanese Stalker to me. Stalker was included in the current 2021 retro toy line. Even though these are called retro, they are made in the modern 25th anniversary body style. They are not vintage o-ring style figures. That card art is beautiful though. Thank you to Kevin from Peg Warmers for giving me this retro Stalker. In Brazil, the company Estrila released a Stalker that was very similar to the US release. Thank you to Mr. Ulrich for sending me the Estrila Brazilian Stalker. This is 25th anniversary Stalker. It is Stalker version 9 from 2007. This figure shows off modern articulation and sculpting from the 4-inch figures released in that era. Let's take a look at Stalker's accessory. He included only one. Both the 1982 and 83 releases included the same accessory. It was his M32 pulverizer submachine gun. It was in dark gray plastic. It is based loosely on the real-world Heckler and Koch MP5. This submachine gun was a popular accessory and was re-released several times. It was included with the 1983 Malaway and 1984 Retail Duke action figure recolored green. It was released again in a dark gray almost black color with the 1988 Tiger Force Duke. It was released a couple times without action figures. First with the 1983 Battle Gear accessory pack number one. In a lighter greenish gray plastic, it is distinguishable from the original because the color is much lighter. It was included with the 1985 Transportable Tactical Battle Platform in a medium gray that is between the lighter gray of the Battle Gear accessory pack release and the original darker gray release. There is also a molding difference. The rear sight is flattened. Here are the vintage releases of this accessory. This is the original. This is the Battle Gear accessory pack version. This is the Duke accessory. This is the Transportable Tactical Battle Form accessory. And this is the Tiger Force Duke accessory. Let's look at Stalker's articulation. But this figure is far too fragile for me to demonstrate the articulation. So I am going to use a stand-in short fuse. A figure that was released the same year and with the same articulation but with much more robust plastic. Both the swivel arm and straight arm figure could turn their heads left and right. They could lift other arms up at the shoulder and swivel at the shoulder all the way around. They had a hinge at the elbow so they could bend the arm at the elbow about 90 degrees. There was no other articulation on the arm for the straight arm figure. The swivel arm figure could do all the same things the straight arm figure could do but also had another point of articulation. He had a swivel at the bicep so he could swivel his arm all the way around. This was marketed as swivel arm battle grip. Both releases of the figure were o-ring figures. Meaning the figure was held together with a rubber o-ring that looped around the inside. That allowed him to move at the torso a bit. He could move his legs apart about so far. He could bend his leg at the hip about 90 degrees and bend at the knee about 90 degrees. Let's look at the sculpt to design and color of Stalker and first I have to point out that most of this figure is reused from other 1982 figures. For example, Grunt also released in 1982 and re-released in 1983 used the entire body from Stalker. Only Stalker's head is a unique part. Even so, that still made Stalker special. Some 1982 figures didn't even have their own unique head. Let's look at that special head. It is the same on version 1 and version 1.5. He is wearing a green beret with no beret flash.  This is one of the few 1982 heads that was not reused on another figure. For 1982, this was a really good head sculpt. On his chest he has a light green shirt with dark green striped camouflage. This may not be as impressive as the camouflage we got on later figures, but in 1982 it was remarkable to get any camouflage. He also has black straps on the front and the back. On the front he has pouches and a sculpted-on grenade and knife. This camo pattern is probably meant to approximate tiger stripe camouflage, which was used by some elite units in Vietnam. His arms feature long green sleeves with that dark green camouflage pattern, and on the straight arm figure he has pockets on the outside of his upper arms. The arms on the swivel arm figure are almost the same. Still has the light green sleeves with dark green camouflage pattern. The pockets have been given more detail and moved to the front of the upper arm.  There is a significant difference between the straight arm and swivel arm figures on the waist piece. Both have light green plastic with dark green camouflage. On the straight arm figure he has a thick waist piece with a wide belt and an H-shaped belt buckle. That belt buckle is probably a brand stamp for Hasbro. The waist piece on the swivel arm figure is still in light green plastic with dark green camouflage, but it is a slimmer waist piece with a more detailed belt. And the Hasbro branding is more blatant because the belt buckle is now in the shape of Hasbro's logo. Both the straight arm and swivel arm figure had the same legs, again with the light green plastic and dark green camouflage pockets on the outside of both legs and we finish up with some solid black standard 1982 boots. The camouflage made this figure special. Hasbro cut costs on the 1982 lineup of figures. Paint was expensive so Hasbro tried to do as little of it as possible. One figure, Snake Eyes, was made entirely of black plastic with no paint at all. The money saved by producing one figure with no paint allowed them to add paint to stalker. It really made the figure stand out. Let's take a look at the file card. The file card was printed on the back of the card on which the figure was packaged. This was the 1983 release because you can see the swivel arm battle grip blurb. It shows his faction as G.I. Joe. It has a portrait of stalker with some wonderfully painted card art by Hector Guerrero. There is a difference between the card art and the action figure. On the card, his beret is camouflage, not solid green. Let's talk about this beret. The green beret was worn by U.S. Army Special Forces, which is not correct for stalker. Starting in 1975, the U.S. Army Rangers wore black berets. That is probably the period correct option for stalker. One vintage version of stalker did include a black beret, but it had this funky yellow band. That's not the weirdest thing about this figure by a long shot. I did a review of it. Please check it out. His specialty is Ranger. His codename is stalker. His filename is Lonzo R. Wilkinson. His primary military specialty is infantry. Secondary military specialty is medic and interpreter. He was G.I. Joe's medic before dock. His birthplace is Detroit, Michigan. Probably a Lions fan. He's done more winning than the Lions have since 1982. His grade is E5. This paragraph says stalker was warlord of a large urban street gang prior to enlistment. Fluent in Spanish, Arabic, French, and Swahili. Graduated top of class. Basic combat training. Advanced infantry training top of class. Special training U.S. Army language school. Explains why he knows so many languages. Intelligence school. Qualified expert M14. M16. M1911A1 auto pistol. M3A1 grease gun. Which I believe was outdated in the 80s and probably even in the 60s. M32 pulverizer submachine gun. Glad they fit that in there somewhere since that's the weapon he comes with. This final paragraph has a quote. It says, functions well under high stress situations. Intelligent. Perceptive. Moves like some sort of jungle cat. Silent. Fast. Strong. This is probably the source of his stalker codename. This is a pretty standard file card for 1982. These file cards were written by Larry Hama, the writer of the comic book series. It does not hint at the importance of stalker to the G.I. Joe's story in the future. The urban street gang background is expounded upon a little in the comic book series. It's a bit stereotypical to make the only African American character in G.I. Joe a former gang member. That part of his background is far less important than everything that happened after he joined the army. Looking at how stalker was used in G.I. Joe media in the cartoon, he first appeared in the real American hero miniseries part one in 1983. He had a moderate number of appearances in the animated series, but he was not as prominent as he was in the comic book series. He appeared in the geek era of the animated series in his later uniform, but was rarely more than a background character. In the comic book series published by Marvel Comics, he first appeared in issue number one in 1982. He was a main character in the series. He served with snake eyes and storm shadow in Vietnam on a long range recon patrol team. He brought snake eyes onto the G.I. Joe team. He was a mission leader on numerous occasions. The final issue of the Marvel series issue number 155 explains that stalker joined the army to get away from the mean streets of Detroit, which had already killed his two older brothers. There are very few characters in the comic book series more important than stalker. I already loved the figure. The comic book sealed stalker as my favorite G.I. Joe. Here's an example of what I mean from issue number 39. A squad of Joes is escaping from Sierra Gordo after rescuing Dr. Burkhart from captivity and certain death. Dr.  Ripcord doesn't like this and starts tearing into her, but stalker stops him and explains that the reason they fight is not so everyone can think the same way they do, but so everyone can have the freedom to think anything they want. Stalker gets it. Not enough people get it even today. Stalker is not just a tactical and strategic master. He also understands the why. Looking at stalker overall, it's no secret that I love this figure. It's beautiful. It was a special figure in 1982, and that's a special figure to me. And now stalker doesn't have the details and accessories that later figures would have. It also reuses a lot of parts, which is usually a big problem. If you compare this figure with figures that came out during the golden age of the vintage GI Joe era, stalker seems a bit lackluster. I can't pretend this figure is objectively better than figures that came out later with better accessories, better sculpting, and better paint. Despite that, this figure was special in 1982. He had the beret. He had the camouflage. He had a unique weapon. He was cooler than cool. Stalker included only one accessory. That was probably another cost-cutting choice. A backpack would have been appropriate. But the accessory he came with was a great one. The pulverizer submachine gun was so cool, it got reused many times. I review a lot of GI Joe figures that are not very good. It's fun to dunk on a bad figure. And I do. I dunk on them like Wilt Chamberlain. Wilt Chamberlain and I have a lot in common. Or as I call him, Shorty. But most GI Joe figures are great. That's why I enjoy collecting them. Looking at a beloved figure like Stalker reminds me why I do this. There is no dunking on Stalker. Stalker dunks on you. If you're watching this video, you probably have some history and experience with GI Joe. I'll bet there was one figure that captured your imagination and drew you into the world. If it wasn't Stalker, who was it? What was the action figure that inspired you? This is the figure that inspired me. It wasn't my first GI Joe figure, but it was and is and always will be my favorite. That was my review of Stalker. I hope you enjoyed it. If you did, please give this video a thumbs up on YouTube. Share the video and subscribe to the channel for more GI Joe tour reviews. Thanks again to Hans Chao for the title card image. Really well done. Great job. If you would like to help me continue to make these videos, you can support the channel on Patreon. You see the name scrolling on the screen right now. Your name could be there. You can find me on social media on Facebook and Twitter, and I have a website, hcc788.com. Thank you very much for watching. I will see you next time. And until then, remember, only GI Joe is GI Joe.