Real History of Terror
CandyMan
Halloween trick or treat give me candy and not peanut halloween trick or treat
trick or treat
dance my children
What darkness
dad there is nobody in this house
if we are going to another
Dad, why did you stay?
daughter turns out that if there was someone in the home have the sweets
How strange was nobody
son, you can eat the sweets
They know bitter these sweet dad
Take a glass of juice Glass of juice
Hahaha
Hahaha
ajajajaja
Jajajajajajaja
He's already dead
Miss, could you tell me what he died of?
of poisoning
cyanide poisoning
girls tell the truth who gave the candy to Timothy
It was my dad, we went to a dark house and he was left alone standing there while
we went to another house to look sweet
if he was Timothy's father
and they are safe
Yes, we are safe
yes sir officer
He said that in the house they gave him the sweets my dad killed Timothy
it's true that Timothy's dad gave them the sweets
if he was he gave us those sweets
the autopsy revealed that he died because of cyanide poisoning
that caused convulsions and vomiting
the father is one of the suspects
over and out
The father killed his son to collect life insurance since he had a debt of $ 100,000
Ronald asked his university professor What is more deadly cyanide or another poison?
The jury found Ronald guilty on capital murder charges and 4 attempted murders of the other children who were on that day
Ronald was executed in the electric chair
For more infomation >> CandyMan | History of Timothy | Avakin Life - Duration: 4:56.-------------------------------------------
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Naby Keita stretchered off against Napoli - Liverpool fans distraught after injury - Duration: 2:38.
The midfielder returned to the starting line up having been on the bench in Saturday's draw against Chelsea
But Keita's night was cut short when he went down off the ball. The summer signing went into a challenge with Lorenzo Insigne before going to ground
Keita was then stretchered off after assessment from Liverpool's medical team. Jordan Henderson was the man Jurgen Klopp called upon to replace Keita
Fabinho had to watch on from the bench, he has made only one start since his arrival from Monaco
Liverpool fans have yet to see the best from Keita since he joined from RB Leipzig
Now they're fearing the worst and that the midfielder could face a spell on the sidelines ahead of Sunday's clash with Manchester City
One fan fumed on Twitter: "Napoli's pitch is an absolute joke. Disgraceful for a top European side
Not by any means saying that it's the reason that Keïta has injured himself, but there is for sure a chance that it at least played a part
" Another added: "FFS. Keita's big chance. 15 minutes in and he's off. He looks gutted and a stretcher is being used
S***. Hope it's not too bad." "Should have rested him for City," one fan claimed
The severity of the injury is not yet known but it is expected that Keita was undergo tests while the match continues
The game as a contest was very tight in the first half. Insigne had the best chance of the match, drilling wide of Alisson's post
Napoli need to make amends from the opening match day draw at Red Star Belgrade. The Reds top the group having beaten PSG 3-2 at Anfield
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The 10 HARDEST RUSSIAN WORDS to Pronounce! - Duration: 6:38.
Всем привет! ["Hi everyone!" in Russian] Welcome back to another video with me Conor Clyne.
This is the Tsar Wxperience and in Today's Tip Thursday I'm gonna be going through the
10 hardest words to pronounce in the Russian language you probably just saw
some Russian written there that's called the green theater here in Odessa in
Ukraine - Зеленый театр and let's see how I get on trying to pronounce those
10 hardest words. Now I have been learning Russian of course for you know
a few years and I spent a good bit of time here in Odessa and in other cities
where Russian is spoken a lot but there's always gonna be some things that catch
you out so let's get in today's video and see how I get on with the Russian
language and it's hardest ten words!
Всем привет из Одессы! Greetings from Odessa in Ukraine and right
behind me there you should just be able to make out the statue of Alexander
Pushkin the guy who really founded the Russian language created it took it from
being something that was spoken in the villages and actually formalized it.
He's a huge influence on the language and it's kind of really appropriate for
this video, I'm here with Nastya. Nastya is from an amazing YouTube channel in
Russian called 'Room Factory' gonna link those guys below and in this video we're
gonna be going through the 10 hardest words pronounced in the Russian language
as you know Russian is not my first language
by a long way so I'm interested to see how I get on because I do speak some Russian
but you know these hard words might catch me up a little bit.
Apologies to everybody who speaks Russian as their first language before
we start because I'm about to butcher your language so let's get into it!
{Russian] Let's start! First ... - First word ... Skylark
- Skylark - Oh, that's easy, really easy. - Easy, ok!
[English] I don't know. This is fucking hard!
[Russian] What's that in English? - [English] Electrocardiographic X-Ray
- This is 'landmark' yeah, Pushkin!
[Russian] I don't understand!
- Further? - Yes, let's go on! - Last word ... - Last one...
[English] Shit! This is too hard!
[Russian] - Almost - Almost! - Really close! - That's all 10? Yes all 10 words.
High 5! Thanks a lot! [English] Okay so how do you think I got on there? That was a bit of a fun
video as I said go check out Nastya's channel down below if you're interested
in like learning Russian by actually watching some cool stuff then go check
her out she's a lot of fun great videos a lot of them actually can understand
even if you don't really speak Russian that well because a lot of the humor is
universal. I was watching some of them earlier and actually you can actually
watch them even if you don't speak Russian so go check that out if you've been
learning Russian write me a comment below how you thought I got on. If you're
Russian speaker of course let me know give me a grade give me grade 9 out of
10 5 out of 10. Thumps up thumbs down? And I will see all of your smiling enthusiastic
faces in the next video from Odessa Ukraine. До свидания! Па-па!
So that's it for today's video how do you think you would get on with those 10 hardest words in
the Russian language and how do you think my performance went? Drop me a
comment below in the comments section definitely if you have something to
contribute always go and write it there because we're creating this great
community people who are really passionate about traveling here in Eastern Europe
and in particular to Ukraine to Odessa so anything you can contribute is always
appreciated, you can help everybody out there if you are not subscribed to the channel what
are you waiting for? Squeeze the red subscribe button and make sure that you
whack the notification bell because that's how you get notified when I
upload new content here on YouTube and if you don't well YouTube normally
doesn't tell you that there's a new video so even my some of my friends even
ask me hey why don't I know that the videos are uploaded and it's like get
the hit the bell, it's not like like I don't say it in every damn god video here so that's it from
today's video from Odessa in Ukraine. До свидания ['Goodbye' in Russian] in Russian and I will see all of
you are smiling enthusiastic faces for in this part of the world
in the next video. Пока! ['Bye!' in Russian]
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François et Penelope Fillon : cinq choses que vous ne savez (peut-être) pas sur eux - Duration: 7:15.
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Sense ficció - La gent de l'escala - Duration: 56:41.
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Venom Movie Review (No Spoilers)| Stream it or Theater Beam it?| Was This Movie Worthy of Your Money - Duration: 7:57.
what's good YouTube returning life gang fans what you're looking at are the
reviews for the movie venom and man some of them are extremely ugly and I hate to
be the bearer of bad news y'all know I hate to do that some of these reviews
are accurate and we're going to discuss that in this video without giving y'all
the whole cookie we're gonna give you a little bit of crumbs and not give you
any spoilers in case you decide you want to go see this monster named venom if
you're finding me for the first time please go ahead subscribe to the channel
click that notification bill so you're down every time we drop these life gains
videos I also check my description box that's where I leave other life gains
goodies affiliates and sponsors we do business world that can give you life
gains ultimately and also connect with me on my social media links as you see
them scrolling across the screen now let's go ahead dive on into the spoiler
free venom movie review
what's good YouTube you're back in the building with your uncle my bringing you
your life gains and moving views should you go out there and spend your
hard-earned money on venom this is Sony's rendition of the Marvel
MCU the Marvel character excuse me venom and we're going to talk about the hose
up to what the Marvel Cinematic Universe would do but first y'all know when we do
these reviews I have to put on my plus seven glasses of cinema sexy as hell
work on skilling up my craft bringing you a better YouTube experience
something better to look at sponsors are the ones you see scrolling across the
screen HD IPTV offering you everything you see for $14 a month they're doing
trials risk free also do you think that the pen is mightier than the sword well
I've got a sponsor that's giving away a free pen that does everything it's got a
surgical knife it's got a laser it's got a light
I think this pen might be mightier than the sword check them out video
description does this movie hold up and is better than the venom we seen from
the Tobey Maguire spider-man and the answer to that is yes but let's break
this story down Tom Hardy plays venom and man he does a good job did anybody
think that Tom Hardy wouldn't do a good job in his role as venom the cast is
good in this movie as well and you can tell that the cast played this movie in
a manner where they thought it would be a rated R or PG type of movie you can
also tell Tom Hardy thought that that was going to be the vibe for the movie
as well those are the good parts let's go ahead and dive onto what the issues
are Oh in the beginning before Tom Hardy becomes venom fully he's going through
the transition when he gets sick and then he starts feeling bad and he
realizes there's something else in his body that part is a little silly it's
like they try to interject comedy and didn't know that they
was doing it so that part can get a little silly with this movie because it
doesn't match the tone of the movie when he's first trying to discover what's
going on with his body there are two other parts of this movie that I think
are just out that are good they're not bad parts so the post-credits scenes in
this movie if you are a comic book fan there's two post-credit scenes and they
are both lead ups to what's going to happen in the rest of this connected
universe because sony is trying to take this venom franchise and make it a
connected universe kind of the way Marvel MCU has done their universe
they've got a bunch of characters that the MCU can't use and they're trying to
connect and make it a shared universe so if you're into comics you'll fully
understand what's happening at the end with the post-credits scenes and you'll
probably like it but if you're not of if you're a novelist to comic book movies
you're probably not gonna get it so but just just to let you guys know
about that does this script hold up to be something that can be connected in
the universe he'll to the note the script of this movie was not great I
think this is probably the lowest point of the movie they're gonna have to work
on making this a better script now the special effects of the movie now hold up
you ain't gonna be disappointed with the special effects special effects was cool
the villain in the movie he was okay you're not gonna be wild by the villain
in the movie but I think considering that they are trying to build a
connected universe they just kind of had to do what they had to do with
disability I think that some people are gonna argue that the movie feels rushed
based on the weak script now when you go in there you see this and you sit down
if you decide to go the first thing you're going to see is that the script
is weak you probably alike the character development between venom and Eddie
Brock transitioning into venom himself because the venom of this looks great
you're probably like the fact that there is a foundation to do a connected
universe but if you go in there expecting the trick
the feeling you get from a Marvel MCU movie you're gonna be sadly disappointed
because there are times when this movie feels a little weird so you might see
people making memes about the movie being weird it feels weird it feels a
little different it's not what you're going to expect it's not what you're
going to get from a Marvel MCU universe overall I'm going to give the movie 6.5
and that is if you are a comic nut if you are a general person or novelist you
don't do comments I'm probably gonna say it's probably six for you you could wait
but comic book fans you know we're going to see it I was curious it beats the
Tobey Maguire venom like I said the graphics and the special effects and the
CGI they're decent they're not bad they're decent but the script is weak
the villain is not the villain in the boss fights are not going to be probably
what you're used to in the Marvel MCU universe I would say that the movie
feels like it should have been done 10 years ago and it would have been hot but
having said that Sony is trying to build their connected universe they're trying
to do a Morbius movie they probably gonna bring spider-man back into this
thing I would love to see Sony just team up
with the Marvel Cinematic Universe to make this universe and it would probably
make things a whole lot better so that's my spoiler free review of this whole
entire movie I would say if you can wait you can definitely wait if you're a
comic book fan I know you're not gonna wait but everybody else you can wait on
this movie it was okay but it's not gonna wow you that's gonna do it for
this video don't forget to like my video comment and subscribe go get yourself a
life game your life gained on this video save your money you can wait and until
that next sex is hell video I'll see you
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AMERICAN HORROR STORY APOCALYPSE MICHAEL LANGDON MAKEUP LOOK | KOSMIC KRISTEN - Duration: 7:12.
hey everyone its Kristen and today we're going to be doing an American Horror
Story apocalypse Michael Langdon inspired makeup look
first we are using the Mac prep and prime spray and the Maybelline fit me
foundation in natural ivory first gonna put the foundation all over the face for
a matte look
his brows are a little bit more straight than mine are I'm going to be using that
Anastasia Beverly Hills dipbrow in medium brown to create the shape of the brows
that we are looking for also his brows are very thick and very dark so don't be
afraid to put down some color on these
I also found this the brows went a little bit more inward towards the nose
then I usually do mine so make sure that you do that as well now I'm going to use
the LA girl Pro concealer in white and just kind of go around the outside of
the brows make them a little bit more defined
now for underneath the eye I'm using the Maybelline fit me foundation stick and
porcelain and just putting it under the eye area I'm using the same la girl
concealer I have a primer on the eyes
next we're gonna using the morphe picasso palette and I'm using red shade
and I'm putting this sort of in a triangle shape underneath the brow you
don't want to get any on the lid and you don't want to get me in the nose area as
well so keep that in mind and I also found that he doesn't have a
very sharp edge on any of this it's all very blended out also I felt like the
color I chose for the red came out a little bit more pink but I actually felt
like this still looks similar to what we had I kept adding and taking away color
black blending it out and the line was copy with the saturation of the reddish
pink color
or the contouring and using the Maybelline fit me foundation stick in
Toffee and I went pretty heavy on the contouring because his faces want more
contoured than mine is and I do feel like the contour makes you look a little bit
more masculine which does make you look more like him I know I did try to make
this more of a female version but I don't think there's much difference
between male or female version because I feel like he's a pretty androgynous
character himself
here I start to use the Kat Von D shade + light contour palette but I forgot to
take some footage to show you that but I'm just adding it mainly in the outer
areas of the face to darken those and make the cheeks a little bit more hollow
here I'm using these foundation stick again for lips because the color that he
has is very pale and to make it more of a little bit of a female version of this
I decided to put on mascara and for this I'm using the flower Beauty lash warrior
mascara but this is really the only thing that differentiates between his
will and my look so really you could forego this and have it be a male or
female version of this type of look and to top it off I'm going to using a
blonde wig from wig is fashion and I went ahead and used a red fabric and a
long black t-shirt along with blonde wig to create this look , this completes the
Langdon makeup look let me know what you guys think this looked down the
comments down below and let me know what you guys think of the season so far I'm
really excited for it and I'm liking it so far let me know what you guys
think in the comments down below thank you guys so so much for watching and see
you guys
again soon
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François et Penelope Fillon : cinq choses que vous ne savez (peut-être) pas sur eux - Duration: 7:15.
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Halloween Picture Coloring for Kids - Jack O' Lantern Coloring Page - Duration: 2:20.
[Magical Chimes]
Lalay Kids Tv
Halloween Picture Coloring for Kids, Jack O' Lantern Coloring Page
[Music Begins]
Thanks for watching! Don't forget to like, subscribe, and share! :)
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Un an après le scandale, que devient Marie Fillon, la fille de François Fillon ? - Duration: 2:42.
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Penelope Fillon: elle ne veut plus sortir de chez elle - Duration: 3:00.
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Join the Board - Duration: 6:22.
Join the board!
MNCDHH has 15 board members
(8 Regional Representatives & 7 At-Large Members).
Each of the 8 Regional Representatives
must be a member of the Deaf and Hard of Hearing Services (DHHSD)
regional office advisory committee in their area. (Minnesota Statute 256C.24)
While the Commission and DHHSD
can submit recommendations based on our needs,
the Governor makes the final decision on
who is appointed to the board.
Who is on the board?
At least 50% of the members must be
deaf, deafblind, and hard-of-hearing.
The statute also requires that parents of children
who are deaf, deafblind, and hard-of-hearing, and
representatives of county and regional human services,
including representatives of private service providers,
are included on the board.
(Minnesota Statute 256.C.28)
Diversity is important!
In addition to what is required by statute,
the Governor's Office and the Commission also consider:
the racial,
indigenous,
ethnic,
gender,
and cultural diversity of the state.
Representation of people who are
D/deaf, DeafBlind,
hard of hearing blind, hard of hearing
and communication modes
(ASL, spoken language, bilingual,
Cued Speech, other modalities).
Experts on the topics: We are working on in our 5-year strategic plan.
This includes education, employment,
communications, and age-related hearing loss.
The selection of board members is not an easy process.
We need to make sure all points of views are included at the table.
Board Responsibilities:
Board members must commit to attending
four all-day Commission meetings each year
(3rd Friday of January, May, September and November)
and commit to attending 3-4 shorter business meetings as needed.
During our November meeting, we hold a longer board and staff retreat.
We also convene work groups and committees
to implement the board approved strategic plan.
Length of Service:
Terms are for four years.
Members may not serve more than three consecutive terms.
How to Apply?
If you believe you are a good fit and
bring an important area of expertise to the board,
do apply!
Go to the Office of the Minnesota Secretary of State's Boards and Commissions page,
search for MNCDHH's open positions, and
then complete the online application.
Anyone may apply for the At-Large positions.
To apply to be a Regional Representative,
you must be a member of your region's DHHSD advisory committee.
Contact a DHHSD regional office to learn more about their advisory committees.
MNCDHH is able to accomplish its work
because of the board members and supporters in the community.
Thank you for all that you do!
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|| CUPCAKE DIMEZELL CHOKOLAD || CUPCAKE AMANDE CHOCOLAT || - Duration: 4:07.
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Regression: Crash Course Statistics #32 - Duration: 12:41.
Hi, I'm Adriene Hill and welcome back to Crash Course Statistics.
There's something to be said for flexibility.
It allows you to adapt to new circumstances.
Like a Transformer is a truck, but it can also be an awesome fighting robot.
Today we'll introduce you to one of the most flexible statistical tools--the General
Linear Model, or GLM.
The GLM will allow us to create many different models to help describe the world.
The first we'll talk about is The Regression Model.
INTRO
General Linear Models say that your data can be explained by two things: your model, and
some error:
First, the model.
It usually takes the form Y = mx + b, or rather, Y = b + mx in most cases.
Say I want to predict the number of trick-or-treaters I'll get this Halloween by using enrollment
numbers from the local middle school.
I have to make sure I have enough candy on hand.
I expect a baseline of 25 trick-or-treaters.
And then for every middle school student, I'll increase the number of trick-or-treaters
I expect by 0.01.
So this would be my model:
There were about 1,000 middle school students nearby last year, so based on my model, I
predicted that I'd get 35 trick-or-treaters.
But reality doesn't always match predictions.
When Halloween came around, I got 42, which means that the error in this case was 7.
Now, error doesn't mean that something's WRONG, per se.
We call it error because it's a deviation from our model.
So the data isn't wrong, the model is.
And these errors can come from many sources: like variables we didn't account for in
our model-- including the candy-crazed kindergartners from the elementary school--or just random variation
Models allow us to make inferences --whether it's the number of kids on my doorstep at
Halloween, or the number of credit card frauds committed in a year.
General Linear Models take the information that data give us and portion it out into
two major parts: information that can be accounted for by our model, and information that can't be.
There's many types of GLMS, one is Linear Regression.
Which can also provide a prediction for our data.
But instead of predicting our data using a categorical variable like we do in a t-test,
we use a continuous one.
For example, we can predict the number of likes a trending YouTube video gets based
on the number of comments that it has.
Here, the number of comments would be our input variable and the number of likes our
output variable.
Our model will look something like this:
The first thing we want to do is plot our datafrom 100 videos:
This allows us to check whether we think that the data is best fit by a straight line, and
look for outliers--those are points that are really extreme compared to the rest of our data.
These two points look pretty far away from our data.
So we need to decide how to handle them.
We covered outliers in a previous episode, and the same rules apply here.
We're trying to catch data that doesn't belong.
Since we can't always tell when that happened, we set a criteria for what an outlier is,
and stick to it.
One reason that we're concerned with outliers in regression is that values that are really
far away from the rest of our data can have an undue influence on the regression line.
Without this extreme point, our line would look like this.
But with it, like this.
That's a lot of difference for one little point!
There's a lot of different ways to decide, but in this case we're gonna leave them in.
One of the assumptions that we make when using linear regression, is that the relationship
is linear.
So if there's some other shape our data takes, we may want to look into some other models.
This plot looks linear, so we'll go ahead and fit our regression model.
Usually a computer is going to do this part for us, but we want to show you how this line fits.
A regression line is the straight line that's as close as possible to all the data points
at once.
That means that it's the one straight line that minimizes the sum of the squared distance
of each point to the line.
The blue line is our regression line.
Its equation looks like this:
This number--the y-intercept--tells us how many likes we'd expect a trending video
with zero comments to have.
Often, the intercept might not make much sense.
In this model, it's possible that you could have a video with 0 comments, but a video
with 0 comments and 9104 likes does seem to conflict with our experience on youtube.
The slope, aka, the coefficient--tells us how much our likes are determined by the number
of comments.
Our coefficient here is about 6.5, which means that on average, an increase in 1 comment
is associated with an increase of about 6.5 likes.
But There's another part of the General Linear Model: the error.
Before we go any further, let's take a look at these errors--also called residuals.
The residual plot looks like this:
And we can tell a lot by looking at its shape.
We want a pretty evenly spaced cloud of residuals.
Ideally, we don't want them to be extreme in some areas and close to 0 in others.
It's especially concerning if you can see a weird pattern in your residuals like this:
Which would indicate that the error of your predictions is dependent on how big your predictor
variable value is.
That would be like if our YouTube model was pretty accurate at predicting the number of
likes for videos with very few comments, but was wildly inaccurate on videos with a lot
of comments.
So, now that we've looked at this error, This is where Statistical tests come in.
There are actually two common ways to do a Null Hypothesis Significance test on a regression coefficient.
Today we'll cover the F-test.
The F-test, like the t-test, helps us quantify how well we think our data fit a distribution,
like the null distribution.
Remember, the general form of many test statistics is this:
But I'm going to make one small tweak to the wording of our general formula to help
us understand F-tests a little better.
The null hypothesis here is that there's NO relationship between the number of comments
on a trending YouTube video and the number of likes.
IF that were true, we'd expect a kind of blob-y, amorphous-cloud-looking scatter plot
and a regression line with a slope of 0.
It would mean that the number of comments wouldn't help us predict the number of likes.
We'd just predict the mean number of likes no matter how many comments there were.
Back to our actual data.
This blue line is our observed model.
And the red is the model we'd expect if the null hypothesis were true.
Let's add some notation so it's easier to read our formulas.
Y-hat looks like this, and it represents the predicted value for our outcome variable--here
it's the predicted number of likes.
Y-bar looks like this, and it represents the mean value of likes in this sample.
Taking the squared difference between each data point and the mean line tells us the
total variation in our data set.
This might look similar to how we calculated variance, because it is.
Variance is just this sum of squared deviations--called the Sum of Squares Total--divided by N.
And we want to know how much of that total Variation is accounted for by our regression
model, and how much is just error.
That would allow us to follow the General Linear Model framework and explain our data
with two things: the model's prediction, and error.
We can look at the difference between our observed slope coefficient--6.468--and the
one we'd expect if there were no relationship--0, for each point.
And we'll start here with this point:
The green line represents the difference between our observed model--which is the blue line--and
the model that would occur if the null were true--which is the red line.
And we can do this for EVERY point in the data set.
We want negative differences and positive differences to count equally, so we square
each difference so that they're all positive.
Then we add them all up to get part of the numerator of our F-statistic:
The numerator has a special name in statistics.
It's called the Sums of Squares for Regression, or SSR for short.
Like the name suggests, this is the sum of the squared distances between our regression
model and the null model.
Now we just need a measure of average variation.
We already found a measure of the total variation in our sample data, the Total Sums of Squares.
And we calculated the variation that's explained by our model.
The other portion of the variation should then represent the error, the variation of
data points around our model.
Shown here in Orange.
The sum of these squared distances are called the Sums of Squares for Error (SSE).
If data points are close to the regression line, then our model is pretty good at predicting
outcome values like likes on trending YouTube Videos.
And so our SSE will be small.
If the data are far from the regression line, then our model isn't too good at predicting
outcome values.
And our SSE is going to be big.
Alright, so now we have all the pieces of our puzzle.
Total Sums of Squares, Sums of Squares for Regression, and Sums of Squares for Error:
Total Sums of Squares represents ALL the information that we have from our Data on YouTube likes.
Sums of Squares for Regression represents the proportion of that information that we
can explain using the model we created.
And Sums of Squares for Error represents the leftover information--the portion of Total
Sums of Squares that the model can't explain.
So the Total Sums of Squares is the Sum of SSR and SSE.
Now we've followed the General Linear Model framework and taken our data and portioned
it into two categories: Regression Model, and Error.
And now that we have the SSE, our measurement of error, we can finally start to fill in
the Bottom of our F-statistic.
But we're not quite done yet.
The last and final step to getting our F-statistic is to divide each Sums of Squares by their
respective Degrees of freedom.
Remember degrees of freedom represent the amount of independent information that we have.
The sums of square error has n--the sample size--minus 2 degrees of freedom.
We had 100 pieces of independent information from our data, and we used 1 to calculate
the y-intercept and 1 to calculate the regression coefficient.
So the Sums of Squares for Error has 98 degrees of freedom.
The Sums of Squares for Regression has one degree of freedom, because we're using one
piece of independent information to estimate our coefficient our slope.
We have to divide each sums of squares by its degrees of freedom because we want to
weight each one appropriately.
More degrees of freedom mean more information.
It's like how you wouldn't be surprised that Katie Mack who has a PhD in AstroPhysics
can explain more about the planets than someone taking a high school Physics class.
Of course she can she has way more information.
Similarly, we want to make sure to scale the Sums of Squares based on the amount of independent
information each have.
So we're finally left with this:
And using an F-distribution, we can find our p-value: the probability that we'd get a
F statistic as big or bigger than 59.613.
Our p-value is super tiny.
It's about 0.000-000-000-000-99.
With an alpha level of 0.05, we reject the null that there is NO relationship between
likes and YouTube comments on trending videos.
So we reject that true coefficient for the relationship between likes and comments on
YouTube is 0.
The F-statistic allows us to directly compare the amount of variation that our model can
and cannot explain.
When our model explains a lot of variation, we consider it statistically significant.
And it turns out, if we did a t-test on this coefficient, we'd get the exact same p-value.
That's because these two methods of hypothesis testing are equivalent, in fact if you square
our t-statistic, you'll get our F-statistic!
And we're going to talk more about why F-tests are important later.
Regression is a really useful tool to understand.
Scientists, economists, and political scientists use it to make discoveries and communicate
those discoveries to the public.
Regression can be used to model the relationship between increased taxes on cigarettes and
the average number of cigarettes people buy.
Or to show the relationship between peak-heart-rate-during-exercise and blood pressure.
Not that we're able to use regression alone to determine if it causes changes.
But more abstractly, we learned today about the General Linear Model framework.
What happens in life can be explained by two things: what we know about how the world works,
and error--or deviations--from that model.
Like say you budgeted $30 for gas and only ended up needing $28 last week.
The reality deviated from your guess and now you get to to go to The Blend Den again!
Or just how angry your roommate is that you left dishes in the sink can be explained by
how many days you left them out with a little wiggle room for error depending on how your
roommate's day was.
Alright, thanks for watching, I'll see you next time.
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How to Crochet Simple Baby Booties - Easy Shoes for Babies by Naztazia - Duration: 4:22.
Hi! I'm Donna Wolfe from naztazia.com Today I'll show you how to make these
simple baby booties for zero to six months. Other sizes are on naztazia.com
To do this I'm using less than 50 yards of Red Heart's Chic Sheep and a size F
hook. To begin, chain 15. Skip the first chain and single crochet in the next 14
chains. Chain 1 and turn your work. Single crochet in each of the 14 stitches going
under both loops. Continue doing this for a total of 20 rows. On the last stitch of
the twentieth row, begin the single crochet with the green and finish it
with another color yarn such as white.
Chain one and turn. Working in the back loops only, make 8 single crochet
stitches across. One two three four five six seven and eight. Chain 1 and turn
your work. Single crochet in the back loops of those same eight stitches.
At the end begin your single crochet with the white yarn and then change over
to the green yarn which you've been carrying up the sides. Chain one and turn
your work. Do 8 single crochet stitches.
And do another row with the green yarn. Make 22 total rows of alternating white
and green yarn. Cut the yarn with a long tail end and fasten off. Your work should
be about nine and a half inches this way, and three and a half inches this way.
Fold the large green in half like this. And fold the stripes like this. Sew the
striped section to the solid color section.
Now we're going to gather the striped section. Use your yarn to weave in and
out along the top edge of the front of the shoes. You can go around a second
time to get a more secure fit. Pull the strand to tighten. Weave in all ends.
Securely fold over the sides. With the other strand of yarn weave in and out of
the bottom edge. Do this twice to get a strong fit. Pull tight. Make a few
stitches to knot it in place. Now you can seam together the bottom
section. And weave in all ends. If you want a button as a decoration be sure to
sew it on really tightly so the baby can't pull it off. These zero to six
slippers are about three and a half inches. Check out naztazia.com for
other sizes. Please subscribe to my YouTube channel. Like and comment on this
video. And please visit my website at naztazia.com
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Shakespeare Uncovered I "The Merchant of Venice" with F. Murray Abraham | Preview | PBS - Duration: 0:31.
On Shakespeare Uncovered
The Merchant of Venice is hardly
what we see as a comedy today.
F. Murray Abraham explores
one of Shakespeare's most vilified characters
"If you prick us do we not bleed?"
If you tickle us do we not love?
Shylock is an outsider and immigrant and alien.
It's a play for our time.
"The Merchant of Venice" with F. Murray Abraham
On Shakespeare Uncovered
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The 10 HARDEST RUSSIAN WORDS to Pronounce! - Duration: 6:38.
Всем привет! ["Hi everyone!" in Russian] Welcome back to another video with me Conor Clyne.
This is the Tsar Wxperience and in Today's Tip Thursday I'm gonna be going through the
10 hardest words to pronounce in the Russian language you probably just saw
some Russian written there that's called the green theater here in Odessa in
Ukraine - Зеленый театр and let's see how I get on trying to pronounce those
10 hardest words. Now I have been learning Russian of course for you know
a few years and I spent a good bit of time here in Odessa and in other cities
where Russian is spoken a lot but there's always gonna be some things that catch
you out so let's get in today's video and see how I get on with the Russian
language and it's hardest ten words!
Всем привет из Одессы! Greetings from Odessa in Ukraine and right
behind me there you should just be able to make out the statue of Alexander
Pushkin the guy who really founded the Russian language created it took it from
being something that was spoken in the villages and actually formalized it.
He's a huge influence on the language and it's kind of really appropriate for
this video, I'm here with Nastya. Nastya is from an amazing YouTube channel in
Russian called 'Room Factory' gonna link those guys below and in this video we're
gonna be going through the 10 hardest words pronounced in the Russian language
as you know Russian is not my first language
by a long way so I'm interested to see how I get on because I do speak some Russian
but you know these hard words might catch me up a little bit.
Apologies to everybody who speaks Russian as their first language before
we start because I'm about to butcher your language so let's get into it!
{Russian] Let's start! First ... - First word ... Skylark
- Skylark - Oh, that's easy, really easy. - Easy, ok!
[English] I don't know. This is fucking hard!
[Russian] What's that in English? - [English] Electrocardiographic X-Ray
- This is 'landmark' yeah, Pushkin!
[Russian] I don't understand!
- Further? - Yes, let's go on! - Last word ... - Last one...
[English] Shit! This is too hard!
[Russian] - Almost - Almost! - Really close! - That's all 10? Yes all 10 words.
High 5! Thanks a lot! [English] Okay so how do you think I got on there? That was a bit of a fun
video as I said go check out Nastya's channel down below if you're interested
in like learning Russian by actually watching some cool stuff then go check
her out she's a lot of fun great videos a lot of them actually can understand
even if you don't really speak Russian that well because a lot of the humor is
universal. I was watching some of them earlier and actually you can actually
watch them even if you don't speak Russian so go check that out if you've been
learning Russian write me a comment below how you thought I got on. If you're
Russian speaker of course let me know give me a grade give me grade 9 out of
10 5 out of 10. Thumps up thumbs down? And I will see all of your smiling enthusiastic
faces in the next video from Odessa Ukraine. До свидания! Па-па!
So that's it for today's video how do you think you would get on with those 10 hardest words in
the Russian language and how do you think my performance went? Drop me a
comment below in the comments section definitely if you have something to
contribute always go and write it there because we're creating this great
community people who are really passionate about traveling here in Eastern Europe
and in particular to Ukraine to Odessa so anything you can contribute is always
appreciated, you can help everybody out there if you are not subscribed to the channel what
are you waiting for? Squeeze the red subscribe button and make sure that you
whack the notification bell because that's how you get notified when I
upload new content here on YouTube and if you don't well YouTube normally
doesn't tell you that there's a new video so even my some of my friends even
ask me hey why don't I know that the videos are uploaded and it's like get
the hit the bell, it's not like like I don't say it in every damn god video here so that's it from
today's video from Odessa in Ukraine. До свидания ['Goodbye' in Russian] in Russian and I will see all of
you are smiling enthusiastic faces for in this part of the world
in the next video. Пока! ['Bye!' in Russian]
-------------------------------------------
Audi Q2 1.6 TDI 116pk Design - Duration: 1:12.
-------------------------------------------
Trump Tells Reporters What No Other President Dared: You're Part of the Democratic Party - Duration: 2:58.
I was recently re-reading William F. Buckley's "Up from Liberalism," and I noticed several
mentions of scorn for the "liberal press."
This was published in 1959, before anyone really called it the "media," but the
criticisms of the leftward bent of our reporters and mass-media institutions were still there.
Yet, even in 2018, the mainstream media refuses to characterize itself as "liberal," much
less "progressive" or "left-leaning."
I find this rather shocking, considering that what they're passing off as journalism is
stuff like Chris Cuomo's daily rants or Jim Acosta's theatrics in the Brady Room
of the White House.
And that's just CNN.
For the most part, Republican presidents have shied away from outright confrontation with
the leftward tendencies of the media, leaving that to surrogates, if they do it at all.
Donald Trump is going quite a bit further than that: He just outright called the news
media a de facto arm of the Democratic Party.
According to The Daily Caller, the exchange came during a Monday White House news conference
that was supposed to be about the new trade agreement signed between the United States,
Canada and Mexico.
However, reporters instead peppered the presser with questions about Supreme Court nominee
Brett Kavanaugh and Democrats calling for the nomination to be withdrawn.
The president went on the attack, particularly over how the media had covered the Democrats
taking aim at the nominee.
"I know them too well," Trump said of Senate Democrats.
"You know what?
They are not angels."
He called out Sens. Richard Blumenthal, Cory Booker and Dianne Feinstein by name — especially
criticizing the way Feinstein sat on a letter accusing Supreme Court nominee Brett Kavanaugh
of committing a sexual assaul in the early 1980s.
Feinstein had the letter since July, but failed pass it on to the FBI until after Kavanaugh's
initial hearing before the Senate Judiciary Committee had finished.
Trump then turned his ire to the media.
More importantly, in a sense, for (Feinstein) to have waited for that period of time, and
now for you Democrats…" the president said.
"And I guess I'm including you, too, the media.
I consider you a part of the Democrat Party."
Trump: I consider the media part of the Democratic party.
But, for you, for the Democrats, to be talking about, 'We want more time for the FBI.'
"If you wanted more time for the FBI, why didn't Dianne Feinstein bring this up?"
Trump said, according to The Daily Caller.
He also noted that the letter "was confidential until the hearing was over.
After it was over, they went public."
"Why didn't they do it during the hearing?" he said, according to The Daily Caller.
"You know why?
Because they are dishonest people."
Attacks on Democrats and the media are, of course, nothing new from any part of the White
House.
Conflating them directly, however, is a relative novelty.
It's not materially false, however.
With the exception of Fox News, where on your TV can you find anything substantially to
the right of the Democrats' platform?
They buy into most of the liberal narrative — the election was stolen, only racists
support Trump, Brett Kavanaugh was more likely than not an alcohol-crazed abuser.
I wouldn't exactly say the same thing that President Trump did about the media and Democrats,
mind you.
Then again, if the shoe fits (and has fit since at least 1959), they need to wear it.
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