Shadowing-Übung: Quant Interview Questions #2 | Bayes Theorem - Englisch Sprechen Lernen mit Video
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You have a bucket of 500 coins.
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499 on normal coins?
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but one of them is a double -headed coin.
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You draw a coin randomly for the bucket and then you flip it five times.
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Question one.
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If you picked a normal coin, so if you drew a normal coin, What is the probability of flipping 5 hints?
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Question 2: What is the probability of flipping 5 heads?
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in general, just from the situation.
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And lastly, What is the probability of picking a normal coin having obtained 5 hits from flipping the coin that was drawn.
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Now from this last question, you can tell that we are trying to calculate a probability
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using or knowing some new piece of information in this case is the knowledge that we have flipped Five hits.
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using this random coin.
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Hence, this is a question regarding Bayes' theorem listed on the right.
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So the probability of A of event A given event B is equal to the probability of event A, so known as the prior,
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And this is scaled by some fraction, which is the probability of event B given A.
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normalized or divided by the probability of event B.
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So, To break down this equation, we can think of it as the posterior, so our posterior estimate of probabilities, In this case, the posterior estimate of
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The probability of event A on the left is equals to the prior estimate of this, which is just probability of event A,
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And this is scaled by some you could think about it scaling coefficient.
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And this is represented by the fraction.
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Now.
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At this point, I like to just write out all the probabilities
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that I can just obtain just from the question description itself.
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So, Here we have some Straightforward ones, the probability of picking a normal coin, there are 499 of them out of the 500.
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Therefore, it's 499 over 500 and the probability of picking a double -headed coin, which is 1 out of 500.
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Now focusing on a normal coin, what is the probability of having a heads or tails, right?
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Because this is a normal coin, we only have two outcomes for when we flip one, a heads or tails.
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and you will agree that it is half and half for both of them, because it's a fair coin, a fair coin or normal coin in this case.
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Whereas for the double -headed coin, because it is double -headed, the only outcome you can get is hits.
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Therefore, the probability of drawing a hit or flipping a hit using a double -headed coin, or in mathematical speaks, the probability of Flipping ahead.
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Given that you have a double -headed coin, It's just 1 because you'll always get it.
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And the probability of getting tails, having the double -headed coin, is obviously 0 because it's double -headed.
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So let's address question one.
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If we pick a normal coin, what is the probability of flipping 5 hits with this normal coin?
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So we flip it once, twice, 4 times, 5 times, what is the probability of getting 5 hits?
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Now because these are five flips, 5 independent flips, so each flip does not affect the other
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we can say that the probability of having 5 hits given that we have a normal coin is just Half?
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times half, times half, times half, five times.
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1 /2 to the power of 5, which is just 1 /32, right?
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Because these are five independent flips, each of them having, with each outcome having an equal opportunity of occurring.
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And you can also say that the probability of getting 5 Tails will be the same thing, right?
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Because the probability of getting a hit full of tails on a normal coin is the same.
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And for the sake of completeness, let's also calculate the above but for a double -headed coin.
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So the probability of getting 5 hits Assuming you have a double -headed coin, it's naturally just 1.
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because you're always going to get ahead with a double -headed coin, therefore it's 1 to the power of 5, which is just 1.
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So that answers the first question.
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The probability of getting 5 /8 given that we have a normal coin is 1 /32.
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Thank you.
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Now for the second question.
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What is the probability of flipping 5 hits?
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So we know that we have flipped.
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a coin five times, right?
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This coin could either be a double headed coin or a normal coin so
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what is the probability of us just getting 5 hits, regardless of what type of coin we have?
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So we can say
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And I hope you are following
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that the probability of getting 5 hits is the probability of getting 5 hits with a normal coin.
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plus the probability of getting 5 hits with a double -headed coin.
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Breaking that down further with more mathematical notation, it is the probability of getting 5 hits,
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It's probably the event of 5 hits intersected with the event of getting a normal coin,
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plus the probability of The event of five hits intersected with the event of getting a double -headed coin.
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And breaking this down further using the laws of conditional probability, we can see that these two terms here.
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these two terms here break down into these two terms here, alright?
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using this equation here.
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So, Let's think about what we have, right?
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On the left, Here, we have the probability of getting 5 hits, given we have a normal coin, multiply by the probability of having a normal coin.
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And similarly for the second term, And if you think about it, we already have all these probabilities.
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This is what's listed above us.
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hence it's plugging in the values, we should get this.
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1 over 32 times 499 over 500 plus 1, times 10500, which gives us 0 .03318, right?
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So this is the probability of getting 5 hints.
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Okay.
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Hence, Going back to our question, And going back to our last question,
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One is the probability of picking a normal coin, having obtained 5 hits from flipping the drawn coin.
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So expressing that in mathematical terms is the probability of getting A Nullo coin?
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given that we have flipped 5 hits.
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So using Bayes' theorem, we can break this down into the probability of getting a normal coin,
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our prior multiplied by this scaling coefficient, this fraction.
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So it's the probability of getting 5 hits given that we have a normal coin.
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normalized by the probability of getting 5 hits in general. and These
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three terms we have already calculated from
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either the question itself based on the description or from parts one and two above so just plugging in the values
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we will see that The answer for part 3 is 0 .9399.
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Great.
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You've answered the question.
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Thank you.
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At this point, the interviewer may now ask you, does this result make sense?
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Why or why not?
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So let's think about what we have so far.
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So we started with a prior, and we started with a prior estimate of Flipping.
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um, Sorry, we started with a prior of the probability of getting a normal coin here,
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which is just 499 out of 500 because there are 499 coins normal coins out of 500 coins.
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And then we drew a coin and we had some new information about this having flipped five hits, So let's think about it.
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Now our posterior, estimate of probability of getting a normal coin, is 0 .9399.
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Right.
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And if we just express the prior in a decimal form, just to make it easier for us, What we have is...
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The probability of getting a normal coin, the prior, is 0 .998.
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And now what you will notice is that our posterior 9399 is lower than our prior.
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0 .998.
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Why?
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Why has the posterior changed and lower it, lower slightly compared to our prior.
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So let's think about what this new information is.
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This new information that was given to us was that we obtained 5 hits.
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Right?
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Yeah. And...
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The fact that we obtain 5 heads, this New information.
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actually supports the other outcome which is us having a double -headed coin.
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because the probability of getting a...
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of flipping 5 hits using a normal coin is so much rarer compared to that of a double headed coin,
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that this new information that we have is actually supporting the fact that we might actually have a double -headed coin.
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Therefore, this Um, posterior estimate of the probability of getting a normal coin has dropped.
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It's dropped a little bit, Why?
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Why did they drop a little bit?
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Because Overwhelmingly, most of the coins are still normal coins.
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Therefore, it's still likely that we have drawn a normal coin.
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but it's dropped a little bit because we know that this new evidence doesn't support us having drawn a normal coin.
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It actually supports us having likely drawn a double -headed coin.
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Hence, we see this very small drop in the from the prior to the posterior estimate.
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Now, depending on the I guess the structure of the question,
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you might actually see that this prior to posterior drop in probabilities or maybe increase, depending on the question, can actually be quite large.
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And if you want such a question, please refer to The other base question that's found on this playlist on the left
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And if you would like to learn more about my recent experience and also my mistakes from my recent quantum interviews, applying in London in the year 2020.
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3. please refer to the playlist on the right.
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And don't forget to like and subscribe.
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Thank you.
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Kontext & Hintergrund
In diesem Video geht es um die Anwendung des Bayesschen Theorems zur Berechnung von Wahrscheinlichkeiten mithilfe eines Beispiels mit Münzen. Der Sprecher erläutert, wie man die Wahrscheinlichkeit bestimmten Ereignissen zuordnet, insbesondere in Situationen, in denen neue Informationen verfügbar sind. Diese Erklärungen bieten nicht nur Einblicke in statistische Konzepte, sondern auch praktische Ansätze, um die Wahrscheinlichkeit in alltäglichen Situationen zu verstehen. Durch den Einsatz von realistischen Beispielen wird das Konzept des Bayesschen Theorems anschaulich und leichter verständlich.
Top 5 Phrasen für die tägliche Kommunikation
- „Was ist die Wahrscheinlichkeit, 5 Kopf zu werfen?“ – Eine häufige Frage in der Wahrscheinlichkeitsberechnung.
- „Das ist ein faires Spiel.“ – Um die Fairness eines Würfel- oder Münzwurfes zu beschreiben.
- „Jede Ausziehung hat die gleiche Chance.“ – Um die Unabhängigkeit der Ergebnisse zu veranschaulichen.
- „Die Wahrscheinlichkeit ist 1 von 32.“ – Mathematische Ausdrücke von Wahrscheinlichkeiten.
- „Was passiert, wenn ich eine doppelseitige Münze ziehe?“ – Fragen zur Anwendung von Wahrscheinlichkeiten bei speziellen Fällen.
Schritt-für-Schritt Shadowing-Anleitung
Um die Inhalte dieses Videos effektiv zu nutzen und Ihr Englisch zu verbessern, verwenden Sie die shadowspeak-Technik. Hier sind die Schritte, die Sie befolgen sollten:
- Vorbereitung: Schauen Sie sich das Video zunächst an, um die Struktur und den Inhalt zu verstehen. Machen Sie sich Notizen zu den wichtigen Konzepten und Begriffen, die erwähnt werden.
- Erstes Shadowing: Spielen Sie das Video ab und wiederholen Sie die Aussagen des Sprechers laut. Achten Sie auf die Aussprache und Intonation. Nutzen Sie diese Gelegenheit, um die shadowspeaks-Technik anzuwenden und die Sätze gleichzeitig nachzusprechen.
- Reflexion: Stoppen Sie nach wichtigen Abschnitten, um über das Gehörte nachzudenken. Stellen Sie sicher, dass Sie die Konzepte wie das Bayessche Theorem verstanden haben und wie die Wahrscheinlichkeiten berechnet werden.
- Zweites Shadowing: Spielen Sie das Video erneut ab und versuchen Sie, schneller und flüssiger mitzulesen. Fokussieren Sie auf den Kontext, und versuchen Sie, den Inhalt in Ihren eigenen Worten zusammenzufassen.
- Wiederholung: Üben Sie regelmäßig mit weiteren Videos sowohl zu Wahrscheinlichkeiten als auch zu anderen Themen. Nutzen Sie die Technik des Englisch Shadowing, um Ihr Hörverständnis und Ihre Sprechfähigkeiten weiter zu verbessern.
Durch die Kombination von visuellem Lernen mit der Praxis des Englisch lernen mit YouTube schaffen Sie eine dynamische Lernumgebung. So werden Sie nicht nur die Sprache besser beherrschen, sondern auch komplexe Konzepte in verschiedenen Kontexten nachvollziehen können.
Grammatik in diesem Video
Die Strukturen, die der Sprecher am häufigsten verwendet, mit den genauen Worten aus dem Video:
| Struktur | Im Video |
|---|---|
| Present Perfect have/has + Partizip Perfekt – eine vergangene Handlung, die jetzt noch wichtig ist | have flipped · have already calculated · You've answered |
| Passiv be + Partizip Perfekt – wichtig ist, was geschieht, nicht wer es tut | was drawn · is scaled · is represented |
| Relativsätze who / which + Satz – eine Zusatzinformation über eine Person oder Sache | fraction, which is · this, which is · coin, which is |
Was ist die Shadowing-Technik?
Shadowing ist eine wissenschaftlich fundierte Sprachlerntechnik, die ursprünglich für die professionelle Dolmetscherausbildung entwickelt und durch den Polyglotten Dr. Alexander Arguelles populär gemacht wurde. Die Methode ist einfach aber wirkungsvoll: Du hörst englisches Audio von Muttersprachlern und wiederholst es sofort laut — wie ein Schatten, der dem Sprecher mit nur 1–2 Sekunden Verzögerung folgt. Anders als passives Hören oder Grammatikübungen zwingt Shadowing dein Gehirn und deine Mundmuskulatur, gleichzeitig echte Sprachmuster zu verarbeiten und zu reproduzieren. Studien zeigen, dass es Aussprachegenauigkeit, Intonation, Rhythmus, verbundene Sprache, Hörverständnis und Sprechflüssigkeit signifikant verbessert — was es zu einer der effektivsten Methoden für die IELTS Speaking-Vorbereitung und reale englische Kommunikation macht.