Remembering Jimmie Savage

Judith: Welcome to Berry's In the
Interim podcast, where we explore the

cutting edge of innovative clinical
trial design for the pharmaceutical and

medical industries, and so much more.

Let's dive in.

Scott Berry: All right.

Welcome everybody.

Uh, back to in the interim, uh, I'm
Scott Berry, uh, at Berry Consultants

and I have a really cool topic for today.

We're gonna talk about, uh,
Leonard Jimmy Savage, and we have.

Perhaps the best person to talk
to it, who's also, by the way, my

father, um, and weird relations,
almost a brother and a father.

But we'll get into that, uh, biological
father and an academic brother, uh,

uh, in this, so, so Don, welcome.

And, uh, first question.

Leonard.

Leonard, Jimmy Savage.

I feel like I don't know him.

Can I call him Jimmy Savage?

Should I call him lj?

What, what, what, what was.

Tell us about Jimmy.

Don Berry: So nobody called him lj.

Nobody called him Leonard.

They would call him Savage.

Uh, and sometimes with the English
word savage, which I'll mention that.

Um, and, uh, but everybody called him
Jimmy, and he wanted to be called Jimmy.

Uh, the way it happened was serendipitous.

I mean, the whole story has really,
he, um, uh, bad connotations.

I mean, Jimmy's life was not very.

Good, especially when he was a child.

And I'll, I'll get into that because it
matters, it really leads to things, uh, in

his, uh, uh, adult life and his attitude.

But the big thing with
him was his eyesight.

And he was born with a congenital defect.

Um, and it was complicated by,

uh, myopia.

So that when he read something,
he had to take it up to his eyes

like this, and he turned, and his
eyeballs were continually moving.

Uh, it was a very sad thing that
when he was born, back to how he

got Jimmy when he was born, uh,
his mother went through some bad.

Uh, things associated with the childbirth
and wasn't able to pay attention to

things like, what's the name of the kid?

Um, and so, uh, at one point a
nurse was, you know, didn't have

a name, so she wrote down a name.

It was Jimmie with an IE and, um,
when it came time to name him, um.

There was a tentative name, and then the
mother sort of picked the name Leonard.

Uh, and, but the, the nurse kept
calling him Jimmie anyway, uh, it

stuck and he liked it so that he
was, it's his middle name, uh, but

it was also his nickname and, uh, for
reasons known only to him, he liked it.

I, I suppose it was, you know,
everybody called him that

when he was a young person.

And so he, he went by that name.

But it was, uh, all his friends
definitely called him Jimmy and his

enemies, uh, probably called him Savage.

Scott Berry: Okay, so we should let people
know how, how, you know, Jimmy, um, uh,

within this maybe, uh, your relationship
and how, how you met him, um, in this.

Don Berry: So how I met him was easy.

I was, uh, a student at, at Dartmouth
and I didn't know what I was gonna do.

Um, I had three kids, um.

I was, uh, a math, uh, math major.

And, uh, Tom Kurtz, who, uh, I knew
from, uh, the, he built along with John

Kennedy, he built, uh, basic language.

The basic language, developed it.

And, um, he, uh, and so he.

Suggested to me and uh, others in the
math department since I was interested in

probability I should go into statistics.

So I applied to various places,
uh, and I got a fellowship

at, uh, Yale and, and, uh,

went to Yale.

And I met Jimmy when I walked
into his office 'cause he was.

Uh, there, he and Frank
Anscombe were the two big names.

They had recently formed the department.

Frank was the first chair, uh,
and then Jimmy eventually became,

uh, the chair of the department.

But it was, uh, it was small.

Uh, and so I met him.

Uh, I took a course from him, uh, in
the very first semester I was there.

Uh, it was a course out of feller
and it was, um, a, a course that

undergraduates could take, but it
was also for graduate students.

And so I'll, I'll get into that.

So anyway, that's how I met him.

Scott Berry: Okay.

Awesome.

Um.

Did, did he?

I, I, I.

He, he became your, your
dissertation advisor.

It'd be interesting to hear about topics
and what, what interesting parts of this.

Did he teach a course using his
book, the Foundations of Statistics?

Did he teach a course in that?

Don Berry: Uh, maybe he did at some point.

Maybe he did when he was at Chicago.

You know, it was published in 1954 and.

We're talking about.

I was there in 65.

Uh, so I, he didn't teach a course
in his book, um, but it was sort

of obligatory, uh, to read his book
and to understand what was going on.

And it was, you know, it was, I,
I, I think he's the father of.

Modern Bayesian statistics, uh,
how can you argue about that?

Obviously, bays and, uh, so bays
is, uh, deserves to be called the

father of, uh, Bayesian statistics.

But Savage, really, Jimmy really.

Made it for, uh, bayesians.

I mean it provided for the first time
throughout statistics, it provided for the

first time a rigorous, uh, definition of
what statistics, what statistics was that

It was in fact a mathematical discipline.

Uh, and he started out.

Just a, a little bit of that.

He started out thinking that statistics,
by the way, he was not a statistician.

He got his degree in mathematics.

He was working in and wanted to
work in physics and chemistry.

Chemistry turned out.

You know, that was sort of unfortunate
because he couldn't see, uh, and it

was, uh, how he went into the lab.

So eventually he really fell in love
with statistics and the philosophy of

statistics, you know, what did data mean?

And to him, he was.

He was a polymath.

He knew everything.

He knew everything about everything.

I mean, it's, it is just amazing and
I'll give you a few examples of that.

Um, but he, he knew, uh, about,
um, uh, various EE economics,

you mentioned economics.

Scott Berry: yep.

Um, so, so Milton Friedman is, is quoted,
and you know, I, we never know if quotes

are right, but is quoted as saying
he's one of the few people I've met.

I would, he unhesitatingly call a genius.

Was what Milton Friedman said of Savage.

Don Berry: Yeah.

And David Wallace, um, and, you know,
everybody that, uh, knew him deeply,

thought exactly the same thing.

I mean, it's hard to to know him.

Without thinking, he has to be
the smartest person in the world.

'cause he seems to know
everything and with, with a depth.

That is phenomenal.

So, um, so let me give
you an example of that.

And I'll give you an example.

It's a, it is kind of a trivial one.

Uh, I mean, I love to work with him.

We worked on some examples in science
that of course he knew about the

science and he brought me into it.

Um, he, his childhood had some ops.

Mostly they were downs.

Uh, we know about his childhood
mostly because of Richard.

Savage, who was his brother, younger
brother by eight years or so.

Um, and so Jimmy was Richard's father.

Um, uh, Jimmy's father was
instrumental in making Jimmy's life

good and was a, a, a big positive.

Um, uh, the rest of his childhood
was pretty bad, but, uh, his parents

bought him an encyclopedia when
he was very young, and he read it

and, and he, he remembered it.

Uh, just a very simple thing about that.

Uh, the main thing I want
to tell you in a minute.

Uh, so he one time said to me, he said.

Uh, Don, uh, uh, Jean, his wife Jean,
um, is writing a project on Finland and

she's looking for celebrities in Finland.

She can't find many celebrities.

Do you know any celebrities in Finland?

Uh, from that they Finn and I said,
I think Victor Borger is a, uh, fan.

And he said, no, Victor Borger is.

Danish.

How did he know that?

Do you know what vi Victor Berger does?

You probably don't know.

He was, he was, he was a celebrity.

Uh, he was a pianist.

He was a comedian.

And he had a piano that joked, I mean, he
worked with the piano and various jokes in

the piano, and he was really clever and,
uh, talented, uh, but not very well known.

And he appeared in the TV shows,
like, uh, ed Sullivan show some,

you know, uh, things like that.

Uh, and, uh, but he wasn't
really very well known.

Then a little bit more
known than he is today.

Uh, so how did he, how did he know
that he couldn't watch television?

I mean, he couldn't see.

Um, and his, uh, childhood,
just, I mentioned Richard.

Uh, Richard, uh, said, um,

that, and I wrote this down.

He was a brilliant child.

But he paid no attention to what was
going on in school because he couldn't

see what was going on in school.

Um, and his teachers said,
you can't go to college.

I mean, she put in, they put in
really negative things about him.

According to Richard, uh, the
prevailing wisdom in the school

was that he was feeble-minded.

Scott Berry: Wow.

Don Berry: it was, and, and it
was a very bad thing for his.

Um, uh, emotional, uh, circumstance, but
so something that involves you, Scott, um,

mom, your mother, um, was pregnant with
you and she would go to the doctor,

you know, regular visits to the doctor.

Uh, you have three older brothers.

Um, and the doctor would inevitably
say, you're due for a girl.

she would tell me that, and I'd
say, no, you're not due for a girl.

Uh, and I, I mumbled things about, you
know, uh, um, what the probability was,

and I was really interested in that
separate from my own personal interest.

You know what?

How do you do this?

How do you find the probability that
the unborn is, is going to be a boy?

And this was in the days PR prior
to amniocentesis and any of these.

And it used to be that people would say.

Um, you know, pregnant woman would come
into a room and would, would meet somebody

and they'd say, oh, you're carrying low.

It must be a, it must be a boy.

Uh, and you know, it was really
these, uh, sort of old wives

tales thing.

But, so I was interested in, in,
in, in pressing your mother with

something that was, uh, uh, legitimate.

And so I said.

Uh, to Savage, I said it, it's silly to
say, to use a maximum likelihood estimate,

which is one I know it's not one.

Uh, so how do I do this?

How do I find a prior distribution,
let's say I'm willing to accept

that, um, my wife and I have the same
probability forever, uh, of, of a boy,

but it varies potentially between Madrs.

Um.

And, uh, so let's assume exchange ability.

Um, and, uh, but, but how do
I find a prior distribution?

And so he got up and went to his
bookcase and pulled out a book by

Cardo Genie, C-O-R-R-A-D-O-G-I-N-I, who
you may know if you're an economist.

Um, about the Genie coefficient,
which is used in, in, in,

especially in the economics.

Uh, and Genie turned out
to be also a demographer.

So I looked at the book and in the
back of the book in the last half

of the book or so, was amazing data
on families throughout the world.

A Australia, uh, Africa, the United
States on family size and number of boys.

Scott Berry: Wow.

Don Berry: And it was truly amazing.

I mean, when you looked at it, it was
absolutely clear that it was not binomial.

That was absolutely clear.

Um, and what.

What what was clear
about it was there was a,

Scott Berry: a,

Don Berry: um,

a, more It, it,

Scott Berry: effects.

Don Berry: it could have been, uh, it,
it, it, it could be, it looked like

it was a, um, uh, a distribution of,
of p and a beta binomial, and, but.

There was a, an interesting aspect
to that, uh, some sort of an

added effect that if you looked at
families with, I mean these number of

families, number of, uh, of children,
the family went up to like 18.

Uh, there wasn't very much data at 18,
but let's say you went up to 12 and, uh,

the proportion of boys and families of 12.

Uh, that was one that is, all of
them were boys, was bigger than the

corresponding proportion for 11.

Scott Berry: Yeah.

Don Berry: you know that
in a binomial it's, it's 12

times in the other direction,

so something is going on.

I eventually learned.

That, uh, there are some women throughout
the world and this was, you know,

constant, uh, throughout the world.

Uh, some women who cannot
carry a male fetus.

Uh, and so that would
explain a point mass.

So it was a mixture of a point mass
and a beta was fit pretty well.

And I calculated that the probability
you were going to be a boy was 57%.

Uh, based on that prior
probability, of course it went,

it went up for the next one.

And, uh, uh, mom and I had two girls.

Uh,

So,

Scott Berry: what what's fantastic about
that is, is first of all that somebody,

he knew exactly what book to go to.

He remembered that what, what I, what,
what's amazing is I, I kind of thought

maybe he's a pure theoretical guy with
the foundations and he came up with this

amazing axiomatic approach to probability.

But he worked in economics.

Apparently he has some, uh, uh,
some aspects that maybe he brought

brownie in motion to asset pricing.

He worked with Milton
Friedman in World War ii.

He worked with John Von Neuman
as a mathematical statistician.

I remember Edwards Lindman in Savage
where it was behavioral sciences

he worked in, sounds like he was
actually an, an applied statistician

despite being a genius mathematician.

Don Berry: Yeah.

And he, he got his, he got his
rocks off by looking at, um, uh,

uh, science and applying statistics.

I worked with, we used to have,
uh, we had a, uh, a, a fish.

Um, expert that wanted some help and he
knew everything about the ocean and about,

uh, you know, a diurnal effect and, and
the like, and was really interested in it.

We did another thing where I
remember it was really neat.

We did mathematics along the way.

It turned out that the, uh, the,
along the route we saw that, uh.

Uh, the, what the integral equation
was that you had to solve in order to

do this thing, but it was about a real
application, like this thing, um, the

distribution of of gender in, in families.

Scott Berry: Yeah.

So I, it it, was he
interested in clinical trials?

I mean, you went into bandit
problems, you talked about the

bandit problems in clinical trials.

Was he interested in clinical
trials and how did you, how did

you come to the topic with him?

Don Berry: So, um,

it, it was my topic.

Uh, he was not.

Into clinical trials.

I mean, he was sort of
like fisher in that way.

Fisher was amazing with
his, uh, agriculture stuff.

Um, he was not into clinical trials.

He, he became interested in
clinical trials because of me.

I mean, this, he was
interested in strategy.

You know what, uh, his other most famous
book is, uh, how to Gamble if you Must.

Where, uh, it was based on
a utility function that's

different than a typical, um.

Namely, there's an amount of money
that you really want and need

to buy an airplane ticket to go
home and nothing else matters.

And so it's utility, one
above that and utility.

And then there are some strange things
that happen, uh, in the strategy and

in particular, bold play is optimal.

Um, and so he took this
seemingly small problem.

And, uh, built finite adaptivity.

It made it show why you need finite
adaptivity and why it's more important.

Um, and so it was, and, and that was not
unusual, where at the end of the road

was a revelation about the mathematics.

Uh, so, uh, anyway, he was, he was,
um, not interested in clinical trials.

The one person who was was Frank anco.

Scott Berry: Ah.

Don Berry: so my initial, when I,
where did the Bandit problem come from?

From my perspective, I took a course
in the management, uh, uh, department.

It was like the business school at Yale.

Uh, and there, uh, I
came across a problem.

It was kinda like.

The one arm bandit where you, uh, ask
yourself, should I keep playing this game?

Should I keep pulling the one arm?

Um, and so, uh, you, but you learn over
time and you learn, uh, you know, when

you've, when you've had enough and you're
convinced that you're never gonna win

at this, so you go to do something else.

Uh, and so I.

I said, you know, the two armed
version is even more interesting.

And so I started working on it,
did some dynamic programming,

did some computations, and I
really became, uh, interested.

Um, and so I got Savage interested

Scott Berry: Did, did you
think about ANCO as an advisor?

Don Berry: I did.

And I, I, you know, I, I, I thought
he was, uh, an amazing mind.

I thought he was, um, a, he was an amazing
mind, and a, and a great person, and

a, and a wonderful person to work with.

But I was, so,

so one of the things I said,
uh, in my comments about,

uh, Savage, it, it, I said.

It was like the world around you.

When you're with Savage, the world around
you is tingling with intellect and it,

it, it, it, that was so attractive.

And so, I mean, I just, and I
knew he was interested in strategy

and I knew that this problem
would really interest him.

I didn't know the, the name Bandit.

Eventually I knew that
it was called Bandits.

It's a very hard problem.

Uh, suffice to say that the computer
scientists call it NP-hard Uh, suffice to

say that, uh, Peter Whittle, who was uh.

Uh, uh, worked in World War ii.

It was a, a statistician, uh, worked in
World War II on, uh, strategic things.

Said that, um, they talked in,
in the UK about out making a one

sheet description of the bandit
problem and dropping it on Germany.

So that the mathematicians would
get hold of it and waste their

time trying to solve this problem.

Scott Berry: Uh,

Don Berry: Uh, so it was really hard.

Uh, but it was, so I thought it
was, I was doing clinical trials

Scott Berry: yeah.

Don Berry: and um, of course I wasn't.

And that was the, you know,
that's the rest of my story.

Um.

So the, what else did I want to

Scott Berry: So, so, uh, that,
interestingly, it ties into the, my

comment earlier of, uh, academic brothers.

So, Jay Cade was part of your
committee, uh, within this Jay Cade.

Uh, interestingly, Moy DeGroot
was a student of his, and Jay

Cade went to Carnegie Mellon.

Uh, I went to Carnegie Mellon and
became a student, uh, of j Cade,

and he was my thesis advisor.

So I I, in some ways I'm almost your
academic brother in this and, um, my

daughter Lindsay, um, interestingly
her last two choices were CMU and Duke.

And if had she gone to CMU, she may
have been j Kade student, and so it, it

may have been that much more twisted.

And interestingly, Lindsay.

Was an honorable mention for
the LJ Savage Award for her

dissertation In Bayesian statistics.

Don Berry: It's wonderful.

Scott Berry: Yeah.

Don Berry: So I, I, I have to mention, um.

The dissertation and,
uh, Savage's role in it.

He was, I showed him my first draft.

My first draft had only the beta
distribution and I had some really

nice theorems, uh, when the prior
distribution is the beta distribution.

It was 10 pages long.

And he said, well, this is fine.

This is a dissertation, but
let's try a little bit more.

And let's try to, you know,
understand more generally.

And so it ended up going through five
drafts and I tell you that every single

one of them, he looked at every single
word he recorded what he was doing.

You have to understand it's a
little bit delicate 'cause you

know, of his writing and, and.

Uh, eyesight.

Uh, but he would record his, what
he was reading and explaining to me.

He taught me how to write.

Scott Berry: Wow.

Don Berry: Um, and it, it, uh,
it, it, it sort of carried over.

I mean, you've learned a little
bit of things from me for writing,

and it's, it comes from Savage.

Um, it was, the end was so well written.

That when I submitted it to the Annals
of Mathematical Statistics, it was

published in the last year of the
Annals of Mathematical Statistics.

After that, it split into two Annals of
Statistics, annals of Probability, uh, and

it, the associate editor was Tom Ferguson,
a very famous decision theorist, and

Ferguson didn't send it out for review.

He read it himself, he
approved it himself.

It was published 27 pages and there
were no revisions at the journal level.

Um, and it was J it was, it was
impeccable because of Jimmy who was.

Uh, uh, he was a perfectionist.

It was his downfall.

Some you mentioned, uh, some other
people that might not have been.

So, I mean, I loved Savage.

I mean, he was like a father figure.

He was a father figure for me.

Um, and I'd have done anything for him.

Um, uh, but other people had been
in conversations with him that.

Uh, we're not all that positive.

I know Herbert s Shernoff, who
I think is an amazing person.

I, and I love him too.

He's still alive.

He's 101.

Um, and, uh, so I, I said to him he's
interested in, in sequential things.

Uh, he was Jake Kaine's advisor,

Scott Berry: Yeah.

Yeah.

Don Berry: um, uh, and, and.

Uh, so I, I was ex we were talking
about things, mutual interest

and, and sequential things, and
he was interested in bandits.

I don't, uh, turn off that is, I don't
think he ever published on Bandits,

but he was very interested in them and
he had done some calculations on them.

So the subject came up of Jimmy Savage.

And so I mentioned, you know, something
about Savage and he said some very

disparaging things about Savage.

He and I said, well, but Herman,
he, he was human and Chernoff said

he had some human characteristics.

So it, it, it, and, and, you know,
everything comes back to the.

The, the eyesight and
the way he was treated.

Uh, let me just mention, and I said I was
gonna say something about Bill Cleveland.

Uh, Janice Cleveland was his wife.

We had a party one night at, at, at, uh.

Uh, Savage's house and, uh, there
were the, the, the women, the, the

wives mostly, uh, were talking.

Um, and Jimmy came up and, uh, entered
the conversation and, uh, uh, Janice

Cleveland said, uh, uh, professor Savage
we're talking about children and, you

know, what are the good ages for children?

What's your favorite age for children?

And he said, your age.

And now people laughed.

But it was real from his, it was from,
he was serious from his experience.

Uh, he didn't want to be exposed
to these people that had really

done some, uh, nasty things.

I mean, you can imagine
the bullying and the like.

Uh, so it's a Sergeant Freud.

It was a, a very good story.

Uh, he died too soon.

He died at age 53 from angina.

Scott Berry: Yeah, it was, it's incredible
all he accomplished to work in the war

and economics and the, the, the two books,
uh, the students he had and he was 53.

Uh, it's unbelievable how much
he accomplished in that time.

Don Berry: yeah.

Scott Berry: Yeah.

Don Berry: I, I, I haven't told you.

Maybe we can do another one.

Uh, can, can I tell you about,
um, my experience with, uh,

teaching and, and, and with Savage?

Uh,

Scott Berry: let's end it with that.

So make it a bang.

Make it a bang.

Don Berry: Alright.

Here's a bang.

So, uh, I had experience with.

With, uh, Jimmy in his class,
we, I, I took where he said,

if ever I don't show up.

To class.

He told me, he said, you take
the class and, and uh, just, uh,

you know, uh, continue to where
you think we should be going.

So I was hoping and hoping that wouldn't
happen, but one day it did happen.

Uh, and so I got up and I said
to the class, which was mostly

undergraduate math majors at, uh, Yale.

Uh, so we had homework last night.

Anybody have questions about the homework?

And, uh, there was a question
and the guy asked, uh, really the

hardest question in, in the homework.

Uh, and it had to do with the acidotic,
uh, tail of the normal distribution.

And so I showed him how to do it.

I started to show him how to do it,
and then Savage came in and, um.

I went up and I handed the chalk to him.

He said, no, you continue.

So I continued and uh, at, I showed
him how, how to do the problem, but

then I related the problem to some
real things and this impressed Savage.

Um, uh, and he then asked me, uh, if
I would be willing to teach a course.

Uh, at Albertas Magnus College, a
Albertas Magnus College was in New Haven.

Still is.

It was, uh, all girls co-ed now.

Uh, but they had a statistics
course that had not, um,

Scott Berry: um,

Don Berry: uh, they lost the teacher
and so they asked Savage if he could

provide somebody that would do this.

And so he asked me if I would
do it, and he said it's $400.

This is a whole semester for $400.

Uh, uh, and I said, sure, of course.

I, and, you know, in
part because of Savage.

Um, and then I bought a car, um,
a 58 Chevrolet with the money.

And, um, I would give Savage a
ride home, uh, with, with the car.

And so one night he got into the
car and he said, so how's Big Al?

I said Big L.

Who's Big L?

And he said, Albertas Magnus.

The car, the car's name is Big L.

And so that's part of the story.

But he, and then he kept calling
it Big L but then we had a very

famous guy, and you've probably
heard of him, um, Fred Mueller.

Scott Berry: Oh yeah,

Don Berry: Uh, I think it was
Feinberg's, uh, uh, advisor,

uh, very famous guy.

Bayesian didn't write
a lot about Bayesian.

He did the Bayesian thing of the
Federalist, Federalist papers.

You know, the authorship, the
Federalist paper, uh, uh, that was

Bayesian and that was, uh, him and, uh.

Uh, somebody else.

Uh, anyway, so Fred Moeller visited
and, uh, lots of people visited, uh,

new Haven when, uh, Savage was there.

You know, Dennis Linley,
um, George Barnard.

Uh, uh, uh, Jerry Kornfield, I
mean, it was a mecca to go to.

Um, and so, uh, when he was going
back, Savage asked me if I would take

him back to the airport, and he wanted
to go along with, because they had

worked together, he and, and Ello.

So the.

Scott Berry: in the car with
Jimmy Savage and Fred Mosell is

they're, they're, they're chatting.

That's awesome.

Don Berry: It's chit chatting
and they started to talk

about some scientific problem.

And the, i, I, I was lucky on
that, uh, thing where I talked

about the asymptotic distribution,
the asymptotics of the normal,

uh, I.

Scott Berry: Mill, Mills ratio I'm sure
came into that, but, but, but, but, yep.

Don Berry: but here I was lucky too.

Uh, they were talking about the
scientific thing and I kept, uh,

adding things and commenting on
what the scientific problem was.

And so, uh, Jimmy says to me, Don,
how do you know so much about this?

And I said, well, I, I read the
article in the science encyclopedia

in the stat library, and his
eyes lit up and he was delighted.

He said, you know, I, I worked so hard.

I had to convince.

Yale to let me buy those, that thing.

And so what you've said now
makes it all worthwhile.

That it is a useful thing and
it, it hearkens back to the

encyclopedia that he read.

You know, I mean, he was really.

A human encyclopedia, but
that's too technical a thing.

I mean, it isn't, he wasn't technical.

He was brilliant and innovative and,
uh, uh, uh, I'm, I'm, I'm, I'm glad

we had him in the Bayesian world.

We probably wouldn't exist,
Scott, if it were not for him.

Scott Berry: So Berry consultants,
uh, has a lot to thank for,

for, uh, Jimmie Savage.

And so let's end it with, uh, three
statisticians and a 58 Chevy named Big Al.

Alright, so, so Dad, thanks a lot.

Appreciate it.

Until next time, in the interim.

Don Berry: Thank you.

Thanks everybody.

Bye.