Merken

# Survey Sampling

#### Automatisierte Medienanalyse

## Diese automatischen Videoanalysen setzt das TIB|AV-Portal ein:

**Szenenerkennung**—

**Shot Boundary Detection**segmentiert das Video anhand von Bildmerkmalen. Ein daraus erzeugtes visuelles Inhaltsverzeichnis gibt einen schnellen Überblick über den Inhalt des Videos und bietet einen zielgenauen Zugriff.

**Texterkennung**–

**Intelligent Character Recognition**erfasst, indexiert und macht geschriebene Sprache (zum Beispiel Text auf Folien) durchsuchbar.

**Spracherkennung**–

**Speech to Text**notiert die gesprochene Sprache im Video in Form eines Transkripts, das durchsuchbar ist.

**Bilderkennung**–

**Visual Concept Detection**indexiert das Bewegtbild mit fachspezifischen und fächerübergreifenden visuellen Konzepten (zum Beispiel Landschaft, Fassadendetail, technische Zeichnung, Computeranimation oder Vorlesung).

**Verschlagwortung**–

**Named Entity Recognition**beschreibt die einzelnen Videosegmente mit semantisch verknüpften Sachbegriffen. Synonyme oder Unterbegriffe von eingegebenen Suchbegriffen können dadurch automatisch mitgesucht werden, was die Treffermenge erweitert.

Erkannte Entitäten

Sprachtranskript

00:05

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09:37

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19:25

Most of my years of my life that makes the plots right around than Come up And the So it's Itasca backers lot by by that Exponential out Alaska combined these 2 The didn't work such as too I But Kit What she did Becomes at Because it is this minus 1 might as times this term and this part The one-time stuff and that will cancel leading plus row squared A new search that For a while and eventually Come to the realization That inside the square bracket is a perfect square At the end of the Want to do so But at the bottom of the table But Kit At But I think ask represent Now what CEO a variable for this density its little acts and usually when you have a normal would mean new embracing square cars the density looks like minus elects Myers New Square Over A 1 over Where does That was expression look like this Not yet but we can make it a little bit and come up to me that that order which do if turnover Acts Over My something over Signetics square Their swords referring Iran's But But That Old Alright well above head I wanna give this in the something of former looks like that thing so I've X over Where the music acts About In the letters truck new food So what's new Where fire this and visiting a hawker I combine this thoughts on that track I said multiplied And abide by Singh was a taboo at very sudden tiny fractions and the nite X minus the use of capital X minus a stigma acts over Texas on Monday combined these Should this multiplied by Said necks and prayer But will That give me a role Sigma setbacks over similar so why times Though why might use of wine over West capital X squared 1 last step Yet But It What ship Puts it into this swamp You are more practices So what's Initial distribution of Capital X given that capitalize little conditional on the of capitalist couldn't capitalize the light is normal with me This guy here and variants Think so star although little but differ from where would be The marginal was normal means abusive acts and Sigma that when we're done X and Y be independent Exactly when row is 0 independence would say that the conditional density is the same as the that when is as marginal So that that well rose 0 1 year Yeah 1 near New 0 their theories are so normal during Obama's 4 0 0 4

28:45

There were some homework problems are involved in this occasions leader tenders until next Which is Do wonders missile expectations But But Just expectations using conditional here maps conditional densities in case of case of a venerable At But The definition abuse and that is again provided that when you put value you're the some converters retiring at Albert was provided with products by some mergers in the case of a continuous venerable Sir Kitsch You integrate acts against these initial density and again as provided this murders autographs pose a 1st down exercise let's do What I want a conditional spectator Nova normal fail there Our could beat up all things were done But but of all X OK well This will equal There's an ANC there have a other board He opened that But is it But Was gift What day that was Dot dot dot design will of over in settling here Thank you Alright well um for the formal let that supposedly of my ears Dot dot dot here and I did that in a row where Pfizer whereby hero X minus this thing I guess that cancer or other words what if I integrated Up Say Expression hall where yet Well chains variables but why people do X minus Neil A vast and Averill a 0 because why Tennessee Weisberg is an odd function Or in other words Alexina minus X squared over To squared Stainless where buyers and fraternity reacts is what number it's just me so I Not violated 0 but the weapons of I don't I just give me that I 4 Other words this would be the use of the capital X Well aware it I'm here to say this is just the Bonino the normal that we are not in In the expression of a past Musa backs role Singh was a cap OX X or say works of capital why 0 why bias music life support to simulate that normal as press outlet their roles Is disarmed is using this factor as boats answering a miscellaneous Role is at Thus the significance of building near accidents day Think that So Why would a year Expected either Rock Indistinct while Watson Distribution of capital X the modulus more Right Kind of you know soluble why it changes they expect their expectations of roses from 0 4 0 0 there the same froze different from 0 visibility expected our without information from 1 but if you find That capitalizes value and they do it in a vexed given that information is us Straggler example At that Need to cook True S should it He was I find it in the shower spectators you given Cabral easily so are you like to think of exponential intervals as being lifetimes of light bulbs and so on You

38:15

Time with Michael Burns out You replace it and then he would be the time when they secular life of burned out of nowhere the 2nd Life burned out what do you expect the person out So what we need to computes Besides artists like you need be conditional that's what you need to compute the initial density need a joint density and Marginal started find a joint density of you in Are you find the as of you and me As They are Well as Ford He wanted to but you would be ardent defender But Restoration stuff Is Jacoby so remember the formula density the joint density for you'd be busy It was I'm not But it cut expert With church Work she did Where this is summer G-1 1 of T-1 detail and this is G 2 0 up team Bob So what 2 Member H 1 8 servings it invert this transformation so what's each 1 of you beat you What's H 2 of you How do you get From you know I'm I get to know you Now we track from Yet Today to going Subtract this A lesser 52 So what's this determined whatsoever She wonders 2 variables as does the 1st hurdle so this will be 1 and this 0 be quiet and this is 1 of the this 1 So this doesn't appear and solely joy density Sir Well I'll be density of warranty to is white Isn't The other independent and also so it as a factor of Rwanda so it is modified to densities together Could K And this is veracity bigger 0 assault onto exponential dances together Lambert utilize times Icelander playing so you violate that now has go each 1 and he age 2 So what's each 1 us to be and recalling that the variable as Soviet around squared Utilize slammed a each 1 of you a 2 of you And that's equal to this where you might as well be what early a limits on these variables you in Our nonnegative right used to be 1 these us to do so which is bigger and use less Bolivia So there is a joint density now want convicted initial expectations so we should find these conditional density of you've given me in the joint over the marginal School That Right so we have this awareness But yet harder we get a marginal we have to integrate the joint over thievery will you think our races Took off And what are the limits aggression 0 White Serie I saw him rate Backed up the land squared And what we have here very right and what we have these giant as it will ever be As far as used constant cycle that are also And then I had to 0 0 Davine deal which is nice and scene And this is good for Aviv bigger 0 areas and what's that As some as 1 of the ones you know it's a gamma with parameter Alfie will to England The us come from some of the well sums of exponential OK so now we have This notice in the way we have slammed the squared minus liability in the rare we have Founders He is minor slammed the and this is 1 and that's for you would range from 0 to see so what's a conditional density of you've given me Far Missouri But was likely to burn off Brown anywhere in the rules His anywhere else 1st light bulb as a uniform distribution given the time when the sight of so what's expected value then you giving capital of easily beat out or 2 Demure expected value is right middle but we can't computed argued that we take you times a density

47:53

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57:22

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1:07:06

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1:16:44

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1:26:06

According to the law of large numbers of public it's far from what would be expected 1 6 Probably this close to 1 6 is very close to what the problem is far from 160 be going 0 maybe you could save and probability that As 1 thousand or 1 thousand buys one-sixth is Figure . 0 1 But the U.S. said 1 thousand Times . 0 1 4 times the race Of the but what's the rates XI It's It did Good old But What guys can XI 1 or 0 words Probably that it's 1 1 ever want comes up every once that they want 6 times 1 1 6 square And and thereby be 0 Man of the probability 5 6 We get 1 6 Times by 25 or 30 states 5 over 6 times 1 or 36 30 Oberg After 16 Think of a period of 30 and I went to 216 I got here A thousand times . 0 1 that's 10 be 30 over too Thousand 160 cancel at 3 over 216 that must be won over 70 or 1 chance at most 1 chance assembly through that This frequency of 8 user more than 100 Away from where 6 He actually ate turns out that some are stronger There were a stroke under the same circumstances What We just want dozen that faith save it If I Take a realization rest and over an electrical work says that the size of the severed realizations word post is very basic bitter says that actually sent over and will convert as a subtle difference between us is application But There are question The problem I want to But sir Oh yes I think you have it's was BA square thank you says via tender Midas for so But They put it in a more zeros here and now this is a I get another 0 here I get at Faced playoff forgot the square in a so I St. Ciento million it said a false witnesses tender 6 And for sets and squared side 2 0 0 1 cancels onerous body so forced to use these fonts and 0 1 making a great of course and city The expected value of GDR where you is uniform on 0 1 If we take a new 1 for you and uniformly asserted On 0 1 Independent Said XIV quality of you I sensed years continuous undesirable responded said has a finite and g g of you as a finite mean Is the expected expected right at some ads are new if I some of the excise and divide by in fact emerges to what 2nd murders to me They His best end over end converters to the expected value or so this summer because of that process is a way of doing numerical integration you get A sample of independent uniformly venerable survived a function that goes Banyan or Realizations Adam up divided by the the number of positions to be close to him I think do realize that they cannot integrate every function GE occurred as you think you are at innovation cannot every function as you can in a way that would be utilized expert there's no quotes expression for interval 0 1 you my sex gratuity acts But Something as exposes us You can't Soccer you get a value for is 1 way there are tables were you can off Thousand 2000 realizations of uniformly history Independent minerals and evaluate g opposed atom up divided by the number you've got to closely and their error precise areas Our breeder pressed for Wednesday

00:00

Randverteilung

Distributionstheorie

Abstimmung <Frequenz>

Mathematik

Sterbeziffer

Schlussregel

Wahrscheinlichkeitsfunktion

Gesetz <Physik>

Teilbarkeit

Raum-Zeit

Dichte <Physik>

Differentialgleichung mit nacheilendem Argument

Poisson-Klammer

Quadratzahl

Differenzkern

Zufallsvariable

Rechter Winkel

Vorlesung/Konferenz

Normalvektor

Drei

09:33

Randverteilung

Distributionstheorie

Faktorisierung

Gruppenkeim

Term

Gesetz <Physik>

Sigma-Algebra

Gerichteter Graph

Physikalische Theorie

Ausdruck <Logik>

Arithmetischer Ausdruck

Weg <Topologie>

Multiplikation

Poisson-Klammer

Massestrom

Gruppe <Mathematik>

Minimum

Vorlesung/Konferenz

Wurzel <Mathematik>

Schnitt <Graphentheorie>

Grundraum

Sinusfunktion

Bruchrechnung

Exponent

Tabelle

Stochastische Abhängigkeit

Teilbarkeit

Dichte <Physik>

Integral

Arithmetisches Mittel

Quadratzahl

Rechter Winkel

Konditionszahl

Tourenplanung

Mereologie

Ordnung <Mathematik>

Normalvektor

Ext-Funktor

28:40

Randverteilung

Distributionstheorie

Gewichtete Summe

Sterbeziffer

Zahlenbereich

Transformation <Mathematik>

Fastring

Eins

Ausdruck <Logik>

Arithmetischer Ausdruck

Variable

Erwartungswert

Gruppe <Mathematik>

Inverser Limes

Vorlesung/Konferenz

Analytische Fortsetzung

Parametersystem

Lineares Funktional

Exponent

Gebäude <Mathematik>

Reihe

Schlussregel

Biprodukt

Kette <Mathematik>

Teilbarkeit

Dichte <Physik>

Kugelkappe

Skalarprodukt

Flächeninhalt

Rechter Winkel

Konditionszahl

Surjektivität

Dreiecksfreier Graph

Gammafunktion

Gleichverteilung

47:47

Distributionstheorie

Gewichtete Summe

Momentenproblem

Wasserdampftafel

Klasse <Mathematik>

Zahlenbereich

Extrempunkt

Zwölf

Bedingter Erwartungswert

Erwartungswert

Multiplikationssatz

Vorlesung/Konferenz

Inklusion <Mathematik>

Parametersystem

Lineares Funktional

Mathematik

Exponent

Division

Stochastische Abhängigkeit

Schlussregel

Biprodukt

Modul

Ereignishorizont

Dichte <Physik>

Kugelkappe

Geometrische Reihe

Flächeninhalt

Einheit <Mathematik>

Zufallsvariable

Rechter Winkel

Sortierte Logik

Konditionszahl

Dualitätstheorie

Entropie

Ordnung <Mathematik>

Explosion <Stochastik>

Innerer Punkt

Geometrie

1:06:54

Punktprozess

Prozess <Physik>

Gewichtete Summe

Wasserdampftafel

Gruppenoperation

Zahlenbereich

Extrempunkt

Term

Sigma-Algebra

Raum-Zeit

Gewöhnliche Differentialgleichung

Bedingter Erwartungswert

Multiplikation

Erwartungswert

Ungleichung

Stützpunkt <Mathematik>

Vorlesung/Konferenz

Abstand

Binärdaten

Parametersystem

Lineares Funktional

Oval

Relativitätstheorie

Varianz

Schlussregel

Gleitendes Mittel

Frequenz

Ereignishorizont

Gesetz <Physik>

Dichte <Physik>

Arithmetisches Mittel

Lemma <Logik>

Quadratzahl

Verbandstheorie

Rechter Winkel

Basisvektor

1:26:01

Addition

Lineares Funktional

Subtraktion

Prozess <Physik>

Ortsoperator

Sterbeziffer

Tabelle

Stochastische Abhängigkeit

Annulator

Abgeschlossene Menge

Zahlenbereich

Kartesische Koordinaten

Frequenz

Division

Stichprobenfehler

Gesetz <Physik>

Arithmetisches Mittel

Arithmetischer Ausdruck

Quadratzahl

Flächeninhalt

Menge

Einheit <Mathematik>

Numerische Integration

Vorlesung/Konferenz

Figurierte Zahl

Analytische Fortsetzung

Schwaches Gesetz der großen Zahlen

Aggregatzustand

### Metadaten

#### Formale Metadaten

Titel | Survey Sampling |

Serientitel | Introduction to Probability and Statistics 131A |

Teil | 10 |

Anzahl der Teile | 16 |

Autor | Cranston, Michael C. |

Lizenz |
CC-Namensnennung - Weitergabe unter gleichen Bedingungen 3.0 Unported: Sie dürfen das Werk bzw. den Inhalt zu jedem legalen und nicht-kommerziellen Zweck nutzen, verändern und in unveränderter oder veränderter Form vervielfältigen, verbreiten und öffentlich zugänglich machen, sofern Sie den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen und das Werk bzw. diesen Inhalt auch in veränderter Form nur unter den Bedingungen dieser Lizenz weitergeben. |

DOI | 10.5446/12879 |

Herausgeber | University of California Irvine (UCI) |

Erscheinungsjahr | 2013 |

Sprache | Englisch |

#### Inhaltliche Metadaten

Fachgebiet | Mathematik |