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فسيلة - transplant
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هي مكتبة رقمية تحتوي علي آلاف الفيديوهات العربية في جميع المجالات
It is a digital library containing thousands of Arabic videos in all fields.
قوائم تشغيل فسيلة
https://www.dailymotion.com/fasela/playlists
Category
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LearningTranscript
00:01My daughter, this is his profile, the dream profile.
00:04Pablo, an Aquarius, is so beloved by him, even his name is Bahaa.
00:08His name is Nice and Strong, like the artist Bahaa Sultan
00:11What's this? JJ
00:19Stay, our party, you've delayed us.
00:22In the Katian family, we don't want to park the place in front of the shops.
00:26He tells me, "I don't mean anything to you, Fandy, you have to leave her with the night."
00:28And I don't rely on anyone for the place, this came after God's will.
00:31God, did you save up and bring it yourself?
00:34No, I left it in Al-Tabinna on time, Hamada Benjokh
00:37God, is this your friend an artist?
00:40No, no, no, this is someone registered with us, and we think he's a religious man.
00:42Overall, I'm glad you came down and met me after we chatted.
00:47By God, I came because of your zinc.
00:49I'm telling you, kiss, what's on your mind is above you
00:52You don't make sense to me, and I don't commit.
00:55Go inside and stick to things that aren't mine.
00:58No, no, no, I'm not being snobbish at all.
01:00I know you're a man and you like to go out and hang out with your friends at the coffee shop.
01:04stitch
01:04And you don't want anyone to give you a headache while you're drinking tea.
01:06Ghamra
01:07And you want someone to pamper you
01:08She hits me
01:09I just want you to tell me everything about yourself
01:11I'd love to know your history, don't be afraid, I'm not jealous at all.
01:15No, no, no, not any date, they are two cases.
01:18The third one was closed due to the absence of a judge.
01:21My dear, you've been living your life oppressed like this all the time.
01:24No, I'm not being wronged. I'm actually the one who's been wronged by the gram, the one who's been wronged by the Israa.
01:28We wanted it with our own hands
01:29Yes, that means you're someone who doesn't give in to circumstances.
01:32You are brave
01:33No, no, no, a burglar, jumping on houses and stealing from them
01:37God, Zira Benhoud is stealing from the song to give the paragraph
01:41No, sir, I'm stealing from the paragraph to make it easier and give it to my dealer.
01:44What is a dealer? Isn't he someone who just finds his livelihood?
01:47What made him sell drugs?
01:50Because he's tired and poor
01:52And you turn it on
01:54Believe me, before that, you're trying to get over all my flaws.
01:58He sees the human being inside me
02:00He understands me, listens to me, and accepts me.
02:03I felt comfortable with you
02:04Me too, Bahaa
02:06I felt very comfortable with you
02:07Oh, before her
02:08Forget formalities
02:10Bahaa Deh Bas Mboya
02:12Call me by the name of the one who has always been with me.
02:14Ahmed
02:15any?
02:15Ahmed
02:16What's wrong with Ahmed?
02:18No, no, no, no
02:18I'm a pro at what I don't know
02:20Ahmedat
02:20You are toxic
02:21You are top-rated
02:22You don't own Oman
02:24You are superficial and lack intelligence
02:26Get out of the group you're with
02:27What's showing you?
02:29Walk a little
02:30Ahmed, I feel that this violence isn't your true reputation.
02:32I think I can fix you
02:33Matty Kaslahak
03:02Matty Kaslahak
03:05Genetics: When pea curd was used, two general principles of genetics were derived.
03:10From peas
03:10I know he's talking about us as human beings
03:12The truth is, my friend, you don't need to study physics, genetics, or oceanography to pick up on a pattern.
03:17Hamada, your 8-year-old nephew, has an incredible ability to spot patterns.
03:21If he saw a red car in the street and I told him it was a car, and then went home and gave him a yellow toy car
03:26He will say that this is an Arab and that this is an Arab
03:28He'll stop if something is walking on four wheels.
03:31If it's a car
03:32Victory is not about color, and victory is not about size.
03:35Time to work, Amster Action
03:36But he left it to him to draw his own conclusion.
03:38Here, my dear Hamada's brain, or our brain, we all know, finds a shortcut.
03:42God, Abu Hamad, this is a good topic, or rather, this topic of petrification.
03:44Sweet and pattern-catching
03:45I need an expert in identifying patterns.
03:47My dear, I was waiting for you to make the same comment on this same camera.
03:50To tell you that this is not necessarily a good thing all the time
03:54It might deprive your life of many things
03:56It might enable you to differentiate between cars
03:58And distinguish between cats
04:00It uses artificial intelligence to differentiate between cars
04:02He differentiates between cats
04:03But it can also cause problems
04:05Your nephew will not only put an Arabic word on all the cars
04:09But any man with a mustache could be considered a dad.
04:11Because his father is from Shelb
04:12Why Cent, a long poet, remains Mama
04:14Because they are similar
04:15This is a lot for independent children, which might be a normal need.
04:17But for the independent giants, it could be a disaster.
04:19If you sit around for ten days, the stock you're following every day will go up
04:23You'll assume that you've caught a pattern.
04:25Sometimes you'll put all your money in and lose everything.
04:28Or this stock didn't continue to rise as you expected.
04:30Sometimes, I have a very good experience with someone of a certain skin color and certain characteristics.
04:35This might lead him to generalize this action to all people with this skin color.
04:39Or those who have these qualities
04:40This is racism
04:41She considers them all bad, or all uncouth, or all unpleasant.
04:45In this example, my dear, we saw that the loss or racism was a result of a lazy mind.
04:49I'm not following the pattern and I'm giving up.
04:51Human beings, just as their ability to search for patterns made them great,
04:55The one I sent with the planet, his ability to perceive patterns
04:58Anything like that could also cause him to fail
05:00Oh, Rezi, Abu Ahmed, you did the same thing you do in every episode.
05:03Because I'm going to tell you what the solution is, I don't want to know.
05:04What's up, my dear? You're allowed to ask? We didn't agree on that.
05:07I'm not interested, I mean
05:08My dear, did you see Abu Ahmed? I didn't want to see him again. I knew it.
05:11Fadl Khalas, I say, "Okay, what's the solution, brother?"
05:13Life, my dear, the solution is mathematics.
05:15Specifically, probability theory
05:18Probability science helps us to arrive at an objective conclusion.
05:21To answer our questions
05:22In a way that protects us from the fungus's tendency to generalize
05:24Because he answers us with numbers, not with readings.
05:27This, my dear, is what makes them call it probability science.
05:29Quantum intuitive science is not intuitive.
05:31That means you might have the correct answer.
05:33And two mathematicians are absolutely certain of it.
05:35But please, feel a strong sense of camaraderie as you try to convince your brain that this is the right answer.
05:39Don't feel like she's riding you.
05:40But in the end, I surrendered to mathematics.
05:42Let's give you an example of a parameter analysis you perform in a lab.
05:46If you have a recurrence of the disease, the probability of the test coming back positive is 90%.
05:51You did the test and it came back positive
05:53The question now, my dear, is for you, and will you answer it with someone?
05:56What's the probability that you have the disease, Abu Hamad? 90%
06:00He is in a hurry.
06:01There's a difference, my dear, and pay attention to this part of the sentence.
06:04If you have the disease, the test will come back positive with a 90% probability.
06:08The statement "If the test comes back positive, you have the disease" has a confidence level of up to 90%.
06:14Yes, what are you saying? I don't understand anything, Abu Hamad.
06:17Who upset you? In the first sentence, my dear, you are sick with the disease.
06:19We saw the symptoms, you have a cough, you have sneezing, you have everything
06:23We know that you are sick
06:25When we ensure this certainty, the test will come back positive 90% of the time.
06:31If we brought 100 patients who were confirmed to have the disease and analyzed them
06:35The analysis will come back 90% positive.
06:3890% of them will have one positive test result.
06:40Ten of them will have negative test results.
06:43So, what's wrong with you, my dear? We don't know if you're sick or not.
06:45We started with the analysis, and all our reliance is on the analysis.
06:48At that point, the question will be
06:49This analysis can confirm that you have the disease.
06:52If the percentage of health is estimated, what will it be?
06:54Here, my dear, the question has no simple answer.
06:57The answer here might confirm it to us with a percentage of 90%.
07:00Or 40% or 10%
07:02I don't know what to do here.
07:03Unless you provide me with more information about this analysis
07:05We are revealing other factors that we haven't discussed.
07:09But it goes very far in answering the question.
07:11Take care, my dear
07:11What kind of factors?
07:12For example, what is the probability that humans will contract this disease?
07:16Is this a common, widespread disease?
07:18Is it a rare disease that affects only a few people?
07:20This analysis, for example, shows us that if a person is sick
07:22The probability that it remains true
07:24The probability of the analysis giving a positive result is 90%.
07:27But here we don't know what the probability is of a person testing positive.
07:30He doesn't have the disease.
07:32It's possible that this is a flawed analysis and that it will produce a more expensive wave at the same time.
07:35Regardless of whether you have the disease, I say no
07:36Any human being is 90% human.
07:39Will it turn out that he has a disease?
07:40What is this stick?
07:41You probably still don't understand.
07:42Let me just make the drawing longer for you
07:44Imagine, my dear, that this drawing in front of us
07:46It's the world in a bundle
07:47Our waste represents
07:48It contains a person
07:49Each person is represented by a sign
07:51Anyone with a plus sign
07:52It represents a person with the disease
07:54Anyone whose symbol is a circle represents a healthy person
07:56He has no illness
07:57Take her, Mid, a person
07:57The one with the plus sign
07:58The one whose mark is a circle
07:59And we solved them all
08:00The color is red, but the test result was negative.
08:02And its color is blue.
08:03It came out positive
08:04Look at the information I've given you.
08:05For the painter
08:06You'll find the world isn't right
08:07We said each one's mark is in the shape of a circle.
08:09Not sick
08:10But why is that?
08:10In circles, it means people who are not infected.
08:13Its color is blue.
08:14Her analysis came back positive.
08:15While we said that anyone with a plus sign is infected with the disease
08:18Why do we see people with positive results when the test doesn't say they have the disease?
08:22Why do we see plus signs that are red?
08:24The analysis doesn't show that she has the disease.
08:26Despite the fact that she is infected
08:28Here, my dear, we will use mathematics.
08:30The one who solves this world and its problems
08:32And she will tell us that out of 40 people infected with the disease
08:34That means their marks plus that, as we said
08:36There are 36 people who are blue
08:38Their analysis is positive.
08:39This means another 90% of those infected with the disease
08:41Their test came back positive
08:42If you remember, my dear, this was the first premise I started talking to you with.
08:45If we brought in patients who were certain of their illness
08:47We analyzed 90% of them
08:48The analysis will come back positive.
08:50Come on, my dear, with the drawing and the math
08:52Let's answer the second question that you got wrong.
08:54Why did I reverse the question for you?
08:56If your test comes back positive
08:58What is the probability that you have the disease?
09:00Here, my dear, we return to your head
09:01We will need to see everyone whose test came back positive.
09:04Regardless of whether they were a circle or an addition
09:06But the important thing is that they are blue.
09:07Write, my dear, in the drawing 87 blue marks
09:10Now we'll see how many of them are plus one
09:12How many positive?
09:14It means he has an action for the disease
09:15Does that mean the patient actually understands?
09:17It means the countries that have a plus sign and are blue in color.
09:20Do you understand the concept? What does that mean, my dear? 36
09:22Count them like that, you'll get 36
09:23If we divide them (36) by 87
09:26We'll get a strengthening percentage, my dear.
09:28How much does it cost on the clover? I won't let you get away with it.
09:3041%
09:31Oh, how come, Abu Hamad? So, my dear, we'll go over it again?
09:34That means at the time when the probability of your analysis
09:37It will come back positive if you are definitely sick
09:3890% reverse subtraction
09:40Or the possibility that you will still have the disease
09:42It's a shame your test came back positive.
09:44This proverb is 41%
09:46But that means the person who analyzed you needs to analyze it themselves.
09:48Oh Narisa, oh Abu Hamad, is this how he does the analysis?
09:50Or is it an analysis studio? I want to know, Abu Hamad.
09:52What affected the package and made this difference?
09:54Let me tell you, my dear, about the factors I mentioned to you regarding the presence
09:57I have this device
09:58Answer me about the percentage of humans in general
10:00Those who have this disease in this world
10:03Regardless of the analysis
10:04In the world of art, they constitute 40% of the world.
10:06This, my dear, is in the world that I showed you at the beginning.
10:09The deceased is one of those people with these characteristics.
10:11This, my dear, was a scholar
10:12Let's go to a new world
10:14With different calculations and figures
10:16If we went to a world like the drawing in front of you...
10:18In this world, 60% of people have the disease.
10:20We won't find 40% of them in this world anymore.
10:22The probability of developing the disease
10:24With the world knowing that your analysis came back positive
10:26It won't reach 41%
10:28No, that will be 61%
10:30Why? Simply put, to put it simply
10:32The tool we inserted here is small.
10:34Therefore, the name we made was smaller.
10:36And again, my dear, count them
10:38The second thing that contributed to this result is that we
10:40We can determine this analysis
10:41It will come out positive by a certain percentage if you are already
10:44You don't have the disease in the first example.
10:46You will find that among 60 people
10:47They don't have the disease, but the test comes back positive.
10:4951 of them, just here.
10:51If you don't have the disease, there is a possibility
10:54The analysis reached five and two percent.
10:56Yours will also come back positive, so don't cry.
10:57Basically, fundamentally
11:00This analysis isn't the best thing.
11:01In differentiating between the sick and the healthy
11:03And may God bless Abu Ahmad and take your lantern.
11:05Even though, by God, he gets them right in the sample, I drank three Retbols.
11:08We, my dear, did a blood test
11:09Ah, you see, my dear, how great sports are!
11:11It protects you from yourself and it protects you from the police.
11:13Kats, whose location you live in, will dress you in it.
11:15By God, Abu Ahmed, you're absolutely right about these sports.
11:17The location, not the director, is great, Atef El-Tayeb.
11:20In his time, he loved cinema and his wife
11:21Okay, Abu Ahmed, I understand.
11:22Let's watch the previous episodes.
11:23And the episodes that came
11:24Wait, Ahwaj
11:25It's not finished yet
11:26My dear, you saw what I did
11:28To understand this topic
11:29We are a nation of blue people and red people
11:32A plus sign and a circle sign
11:34Take this as an extension to protect our location from the CAT police.
11:37Cat's police are coming from the fact that he collects patterns.
11:40We took her in a very long party
11:42Repeating this ritual will take time and effort.
11:44So, what's the point of the door if we do all this?
11:46In just one step
11:48In the eighteenth century, he will present to us
11:50The storyteller, the philosopher, and the scientist
11:52Thomas Pais, Abu Ahmad
11:53Thomas Pace definitely left the fridge
11:55Oh my brother, sleep outside the honey jar
11:58Can you focus with me?
11:59Thomas Pace, my dear, is a respected scholar.
12:01This is the one who set the rules for the Peace Roll equation.
12:03This summarizes everything I've told you.
12:05In probability calculation
12:06The account is compared in The Lance Journal
12:08Titled Peace Rules
12:10Pace's rules will become more widely used.
12:12With the Second World War
12:14When the need for probability calculations increases
12:16In a frightening time like wartime
12:18Is the world Alan Turing
12:19He will use base rolls
12:21So that he can surpass the famous star code
12:24Remember the second scientific case
12:25He is expected to help the allies win the war.
12:28In a race against time against the Nazis
12:30At the time when the Russian world
12:31Andrei Kolmergov
12:33Bayes' equations will be used
12:34To improve the accuracy of artillery fire
12:37Not only
12:38British Air Force
12:40Bayesian equations will be used
12:41And its techniques to improve the efficiency of terrestrial attacks
12:45A war without peace, my dear
12:46It remained a second gender
12:47One mathematical equation has proven its effectiveness
12:50In calculating probabilities
12:51People's lives and deaths depend on this.
12:54Bayes uses his equations
12:55Don't just stop at wars
12:59Everything in insurance and trade
13:01The seeker of sunken submarines
13:03They kept using them instead of the dead of the waves.
13:05We'll see it too, my dear.
13:06Simple cases were used
13:07Like SPAM FILTERS
13:09What stands out among desirable emails
13:11Unwanted emails
13:13And imagine, my dear, one equation
13:15Kat Azim is offering a condition
13:16It is permissible under the condition of Kat Salmakh
13:18I'm working, my dear, because you don't understand it.
13:20You'll find it simpler than you imagine.
13:22Simple despite all its complex layers
13:24And this, my dear, is the essence of mathematics.
13:26A written line can change the world
13:28Okay, Abu Hamad, it's clear you won't leave anything alone until you explain it.
13:30Continue, my dear, as I explain it to you
13:32Let me introduce you to some simple terms
13:33Which makes the explanation easier and, God willing, makes the topic simple.
13:35What? I'll simplify it for you.
13:37Oli Azizi, a term we use is
13:38Or the hypothesis
13:40In our example, the hypothesis we want to verify
13:42And we calculate its probabilities.
13:44Do I have the disease or not?
13:45Without doing any analysis or gathering any information
13:48We would have something like a presupposition
13:49In mathematical terms, we call it
13:51For example, when we come to cut the winter
13:53We assume, by default, that everyone has a cold.
13:56We endorse them, so you do so without even seeing anyone's analysis.
13:58You'll be convinced and expecting that these next two days, out of every four dinners you'll meet, you'll be the one
14:02One of them probably has a cold.
14:03My dear, the presupposition or mathematics
14:0625% of people have a cold
14:08And you described, my dear, the medical analysis as working
14:10I showed this mathematics
14:12If your analysis turns out to be accurate and reliable
14:14And it came out positive, so here's the probability you calculated.
14:16The probability that so-and-so is sick and has a cold
14:18In 25% of cases, if you performed the procedure on someone other than this person, it would be beneficial.
14:20It might increase, for example, to 50% upon successful completion of the analysis.
14:23The analysis has now updated your profile.
14:25Then you'll come back and find a new guide.
14:27Efdens
14:28This ephemeris will allow you to make an edit
14:30For example, you might find a man coughing or sneezing.
14:33Effence and Effence
14:34Here you can make another update and your confidence level will increase to 75%
14:38Every update confirms that your assumptions are flawed.
14:41The analysis indicated ephedra, fever ephedra, and cough ephedra.
14:44Each of these steps, my dear, begins with PRIOR or PRIORI
14:47This is where you get the adjusted or subsequent probability that you arrive at after you know the effendience.
14:52What do you call this subsequent probability in the science of the moment?
14:54The pestyur or pestyuri
14:57This sterile step is the priority for the next step.
15:00Understand? That means any stereotype is PRIOR
15:02Any prayer could be a stereo
15:11Let's take, for example, our patient.
15:13What if your friend coughs constantly for no reason because, for example, he has a similar sensitivity?
15:17There's a possibility he has a cold; if you chase him away, he'll cough.
15:19It would be less than if you saw someone who had no sense of smell.
15:22Someone with a sensitive disposition is expected to cough all the time.
15:24Your job
15:25In the ephesus here, everything that was rare was included.
15:28The greater its impact on your understanding of the end, the greater its effect.
15:30However, if it were to benefit unemployed workers, its impact would be less.
15:33In case, my dear friend, that you have a sensitive nature
15:35This is not a rare occurrence
15:37While your healthy friend who coughed
15:38This is rare evidence, and its power lies in increasing the probability of your hypothesis.
15:43This is new evidence in the case.
15:44Okay, Hamad, I understand.
15:45I have a hypothesis that I keep working on repeatedly.
15:48Like iOS, using what you said and what you forgave
15:50What is proven
15:52Then I examine the evidence.
15:54I see it as rare or not rare
15:56God willing, may God bless him
15:57Muhammad ibn Musa al-Khwarizmi relieved her
15:59Wow, this is so sweet!
16:00Let's use the words we heard to make a formula, my dear.
16:03Her name is Dear Bayrose
16:04Take it before your eyes, win it, remember it, analyze it
16:07Cut it, my dear, and pay attention to me.
16:11This means the probability of the hypothesis is equal to the given evidence.
16:15Open it, please.
16:18This means the probability of the evidence given by this hypothesis is multiplied by the probability of the hypothesis itself.
16:24By dividing me on the probability of the evidence
16:28Of course you don't understand anything
16:29Abu Hamel, you're starting to feel me.
16:30I was about to tell you that I don't understand anything
16:32I'll explain to you
16:33Before that, my dear, we will explain it to you in detail.
16:34Let's review the terms I just taught you.
16:36Priory, pasteury, and those things
16:39Let's include them in this equation.
16:40Shakhl equation in our terms
16:42Is he squeezing it like that?
16:43The pasteurization equals the probability of the evidence given the hypothesis.
16:46This is divided by the probability of the evidence.
16:49All countries are multiplied by the Priory
16:55Here is the relationship between the pasteuroid
16:57Or the possibility that I want to reach
16:59Based on the evidence I work with
17:01update and collect
17:02And the prior, which is my initial assumption
17:05Which is the prerequisite that I haven't yet gathered evidence for.
17:07These countries, my dear, are governed by the middle percentage.
17:09I mean the part in the middle
17:10She's the one who doesn't hit in the priori, she makes the pasteuri
17:12So this is the element, this is mischief
17:14If the percentage that will be produced here is greater than one
17:17So here your pasteury will be larger than the priory
17:19Therefore, the next possibility
17:21Greater than previously assumed
17:23And the higher the percentage, the higher the pasteuroid.
17:25What if the percentage that will be produced is less than one?
17:28So the pasteuroid will be less than the priorio
17:30The lower the percentage, the lower the pasteuroid.
17:32By Ahmed, my priority is that I understood
17:36I want to update and ask you a question that will give me a guide.
17:38I hope I can turn it into a pastiche
17:40If this ratio equals one
17:42How do I spend it?
17:44At that time, my dear
17:45This guide is worthless.
17:46It neither increases nor decreases your chances.
17:48Railway guide
17:49For example, when you say
17:50What are the chances that I have a cold?
17:52Given the evidence, Giffen means
17:53President Putin visited Egypt today.
17:55You'll tell me
17:56It's the same possibility, Abu Hamid, that you have a cold.
17:58Without my knowledge, President Putin visited Egypt today.
18:01President Putin doesn't catch a cold
18:02It's not like you're trying to stop the plane.
18:04These are two things that have absolutely nothing to do with each other.
18:06Should we still apply this equation according to its rules?
18:08For example
18:09probability of disease
18:10Those who know this
18:11Which is
18:11This is
18:13Your presupposition
18:14In winter
18:1525% of people have a cold
18:17Without owning any drill yet
18:18No tests, no coughing, no one lifted fingerprints, nothing at all.
18:21As for the one on the left
18:24Assuming the test is positive
18:26Here's your stereotype
18:28The probability of the suffix
18:29The one I want to pray
18:30From my prior borrowing
18:31Which means
18:32After I found out my test was positive
18:34What are the chances that I will get sick?
18:35And this possibility
18:36How much will it increase?
18:37And how much will it decrease?
18:38Amak Peace is here telling you
18:39The relationship between the initial assumption
18:41The
18:41and the adjusted probability
18:42After I saw the evidence
18:43Which is the sterilizer
18:44It is governed by the rules in our example.
18:46A very small percentage
18:47We will write it as follows
18:48In the simplest
18:49We'll put the
18:50So that you can say EG
18:51What probability of debt analysis should we include?
18:53It will come back positive if I have the disease.
18:54In the place or
18:55We'll put
18:56What did you say about this analysis?
18:58Positive
18:59What are the results of this analysis?
19:00It turns out to be a positive result for unemployed workers.
19:02Nor for the sake of the first
19:03The relationship between
19:04It will determine if our sterilizer
19:07It will be bigger
19:07And he said
19:08Come, my dear, let's make up for it with a question
19:09If we were to say that this analysis is a ridiculous analysis
19:11Its result is a success over time
19:13Regardless of what you're saying, I'm not saying no
19:14Its percentage is 100% motivating.
19:16So here the percentage will be one hundred percent.
19:18At that hour
19:19It will be equal to one or one hundred percent
19:22And
19:22It is assumed that we have the disease
19:25In this episode
19:26Our ratio will equal one.
19:28Like I told you
19:29Our guide is a path
19:30It's pointless
19:30We will notice this, we will find
19:32The sterile peas equals the
19:33Mohammed, honestly
19:34I don't understand this rule.
19:35Where did we get it from?
19:36It can be proven to you mathematically.
19:37You actually want me to prove it to you mathematically?
19:39Absolutely not
19:40You're just using me as a bridge.
19:41To connect your episodes
19:43Dear, don't say that in front of my dear.
19:44The one who doesn't speak
19:45I doubted her
19:46He doubted that he knew
19:47Making transitions between topics
19:48This is a flaw
19:48My dear, you are a thorn.
19:49I'll calculate it for you mathematically
19:50Exactly as you want
19:51Hello, my dear
19:52Our drawing is coming down
19:53We, dear
19:54Our goal was to joke around, my dear.
19:54We arrive at the probability of the disease
19:56given
19:56given
19:57I mean, we know Quraidi
19:58The analysis is positive
19:59Or another meaning
20:00Among the people
20:01Those whose test came back positive
20:02How many of them?
20:03He has a serious illness
20:04Of course, my dear
20:04If you doubt your illness
20:05It won't be revealed about lineage
20:06But you'll go and ask
20:07What is the probability?
20:08If you develop the disease
20:09But Hern
20:09We deal in percentages
20:10Because it's mathematical
20:12simpler to understand
20:12Among the possibilities
20:13But in the end
20:14The two questions are two sides of the same coin.
20:16For one currency
20:16If we talk in mathematical terms
20:18So this ratio
20:18It is a percentage
20:19Benqamin
20:20Number of people
20:20The one who has the disease
20:21Her test came back positive.
20:22On the total number
20:23For those who analyze them
20:25It came back positive
20:25Sports foam
20:26means dismantling
20:27We will compensate for every given factor
20:28Simpler
20:29Look now
20:30On the simplified alone
20:30or the number of sick people
20:32Her test came back positive
20:33You'll find it, my dear
20:34It can be disassembled
20:34This equals the number of people
20:36Those who have the disease
20:36Multiplied by the proportion of people
20:37Those whose test results are positive
20:39People from the group
20:40Who has the disease internationally?
20:41Let's dismantle the stall further
20:42You will find
20:42The number of people who have the disease
20:44Money, my dear
20:44We compensate for it with sports
20:45We will find it equal
20:46Total number of people
20:48Hit
20:49In the proportion of people who have the disease out of the total population
20:52Regardless of any analysis or anything else
20:54In other words, my dear, in mathematical terms
20:55She said, "My dear, this equation is beautiful."
20:57Number F Deez
20:58The number of people who have the disease
20:59It equals the number of people
21:01Multiplied by the propaneti of Dize
21:03probability of disease
21:04So, my dear, simplicity can be expressed in the following formula
21:06The number of sick people and their test results are positive
21:08The total number of people equals the total number of people.
21:10multiplied by the incidence rate of the disease
21:11Multiplied by the percentage of people whose test results are positive
21:14The disease has spread in the German province.
21:15So, Fakik, that's the same place too.
21:17Fakik, or we could say
21:18The number of people with their sett is positive
21:20It equals the total number of people.
21:21Multiplied by the proportion of people
21:22The group that prays for her is called Al-Mujab from all the people.
21:25This is a bachelor, regardless of the analysis.
21:26here
21:26Now, the number of people
21:28The one whose sprite is a scatter
21:30The total number of people is equal to N.
21:32multiplied by the P-post test
21:34The probability that people will test positive
21:36I won't go back to you about it, so you should have noticed.
21:39N means number P probability
21:40Number and probability
21:42This, my dear, means that our meeting is above a house like that.
21:44As you can see, we can eliminate the N total from the numerator and denominator.
21:47We will find that the P-disease gave a positive test
21:50The P-positive test for disease is equal to the P-positive test given for the disease.
21:54P-positive test
21:55My dear, this is the Bice Rule.
21:57The one we talked about a little while ago
21:59Look, my dear, at the little bit of tinkering, how is the house doing?
22:00This is what needs to be proven.
22:02Here, my dear, is the mathematical proof you were asking me about a little while ago.
22:07my dear
22:09Dear Aya
22:10Ah ah ah Abu Hamad
22:12Bayz
22:12Pure Bayz
22:13By God, you want to reach the verse
22:15What is your goal in all of this?
22:17If I know that I'll take you on a long journey with me
22:18But believe me
22:19A noble goal scorer who wants what's best for you
22:20This equation can be used to analyze any problem
22:23From the first medical or nuclear hypothesis
22:25To the simplest extent, a meme between your mother and your aunt
22:28Imagine, for example, if my dear had an individuality
22:30She says his name is Muhammad Khinin
22:32Secondly, isn't that a greeting?
22:34No, this is individual, and I'll give you an example.
22:35My dear, I worked as a single person because I heard many stories.
22:38Its hero's name is Muhammad
22:39They are all cowardly men
22:41She remained convinced that it was all north first.
22:43Now, my dear
22:44Did you see this episode?
22:45Can you use the app?
22:45Peace Rolly
22:46And analyze your words, Al-Almain.
22:47Let's see if it's right or wrong
22:48Since you are listening
22:49Stories of betrayal whose protagonists are named Ahmed
22:51This is a sports translation
22:53Indeed, the father of Ahmed
22:54It's possible it's Ahmed
22:55Given that it is Khin, it is given that it is Khin, a large number
22:59Pais helps you understand why this is such a large number.
23:01That's a large number because it's influenced by Brier again.
23:04Brier tells you
23:05Oh teacher
23:06Oh, my mind
23:06Oh learned one
23:07People named Ahmed
23:08There are many monkeys in the country
23:10Simplicity
23:11If the whole country was named Ahmed
23:12And you're listening
23:13All traitors are named Ahmed
23:16This does not mean
23:16All of them are named Ahmed Khinin
23:18Because the whole country is named Ahmed
23:20If five people were to come, all named Ahmed
23:23This doesn't make you speak
23:24On 95, the one named Ahmed
23:26And what a mess
23:27My time limit, of course
23:28Working means working
23:29But there's still no space.
23:31Okay, Abu Ahmed, the message has arrived.
23:32We know you're trying
23:34No, no, no, no
23:34We'll just talk about the recorder, my friend.
23:36Here, my dear, is the form of your equation, just as it appears in front of you.
23:39If you want to know the probability that your husband is cheating on you
23:41given lineage Ahmed
23:42Here you are looking at the flaw in the equation
23:45You need to look at the P betrayal
23:47The possibility of betrayal is given. The name of the person is Ahmed.
23:50Here, our friend Pais says it equals P, Ahmed.
23:53Given that he is relying on the probability of Ahmed multiplied by the percentage of betrayal
23:58He was satisfied, my dear, and wanted us to discuss the equation.
24:00It turns out that the people named Ahmed were fake.
24:02Because, my dear, I'm eager to know that the past is vast, as evidenced by the stories you hear.
24:06All of these are still stories that have not been proven with evidence.
24:08WhatsApp and Telegram messages have never been conclusive evidence.
24:10These are still just possibilities.
24:12So here the past will be big
24:14And also, my dear, the position here will be very important.
24:17Because there are already a lot of people named Ahmed
24:19The two are divided amongst each other
24:21Under normal circumstances, it will equal some
24:23And in the end, we'll find that the equation is completely contradictory.
24:25And the two will become equal
24:27The possibility of betrayal, and his name is Ahmed.
24:29The probability of betrayal is generally equal
24:31Whatever his name is
24:33The problem isn't in the name field.
24:34The problem is in the category field.
24:36Muslim Christian Ahmed Mohamed Michael
24:39It is the male category
24:41Finally, my dear, can we summarize this episode?
24:44In the words of the French athlete Yercy Mola Plus
24:47The grocer
24:51Probability theory is nothing more than logic and common sense.
24:55After that, we reduced it to calculations and numbers.
24:57We, dear friend, are the ones who create the logic in our minds.
24:59He might deceive us
25:00But numbers don't embellish or deceive.
25:02It might be misunderstood
25:03But she herself is realistic
25:05She throws it in your face, Saima
25:06This is the greatest security system
25:08To protect your mind from the tricks and schemes he uses
25:10The condition is the sanctity of perfume.
25:12But my dear, probability theory is one of the most important theories.
25:14Although it gives possibilities
25:16I don't feel it
25:16How long, my dear, did she raise her shoulder?
25:18But that's how she raised her shoulders, her face, and her analysis.
25:20It is probable
25:22Probabilities based on hypotheses that are supported by evidence
25:25It makes it complete
25:26So, my dear, this theory is not a complete theory.
25:29Daksh gave definitive answers
25:30But it works with probabilities
25:32I'm dealing with it as if it might be wrong
25:33It works even though it corrects itself with evidence.
25:36What makes us, my dear, is a great example that makes us
25:38Firstly, we appreciate this program's merit.
25:40Let's look at his previous episodes.
25:42Not in its next form
25:42Enzo looked at his sources
25:43If there's a YouTube channel, we can share it.
25:45I have to watch it. I know sports episodes can be tiring.
25:47I know
25:47But let's now consider the possibility of sports episodes.
25:49Given, she's tired.
25:50Amidst the circles of Dahia Katutel
25:51I hit them with the environmentalist Hamad Al-Asitak
25:53She named them with the number Avocado
25:55multiplied by y, raised by π
25:56It will give you a number
25:57He has no blindness
25:58Hello
25:59By God, they're terrifying