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From YouTube: Praise Quant 17 - Review Session
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A
B
A
B
Yeah,
it
was
very,
very
smooth,
I,
don't
have
I,
don't
have
problems
at
all
nice.
B
I
guess
we'll
just
I
just
want
to
know
how
this
call
what
this
call
is
about
and
yeah.
Oh.
A
Great
well
basically,
this
call
is
like
a
little
bit
informal,
but
we
have
all
these
reports
that
are
made
from
the
round
and
we
also
have
another
report
that
shows
us
like
a
comparison
of
all
the
data
from
the
last
year.
A
So
it's
a
cool
way
to
see
like
what
was
like
the
highlights
of
the
last
two
weeks
and
then
like
kind
of
see
the
overall
health
of
Praise
over
the
last
year.
I
guess
so:
they're
pretty
cool-
and
we
can
just
jump
in
here
and
I-
can
I
can
show
you
some
stuff.
A
A
Going
down
here,
you
can
see.
The
first
thing
is
the
rating
distribution.
So
it's
like
the
amount
of
each
score
that
was
given,
because
you
remember
like
on
the
slider.
You
can
go
from
from
zero
to
144.
B
B
How
many
people
give
the
the
highest
the
highest
amount.
A
144
showed
up
four
times
yeah
the
highest.
The
most
common
one
was
three,
then
thirteen
which
is
cool,
usually
like
the
highest
one,
is
like
one
or
five.
So
it's
cool
that,
like
you
know,
13,
was
second
and
I.
Think
the
last
round,
like
there
wasn't
a
score
over
89,
so
it's
cool
to
see
that
we're
giving
some
higher
scores.
B
A
A
A
A
Praise
reward
distribution
so
that
you
can
see
who
will
be
getting
the
most
rewards
during
this
round,
so
nte
acid,
laser
em,
Rex,
Christopher,
Mount,
Manu,
Gideon,
Chewie,
myself,
Mateo,
and
then
it
keeps
going
down
there.
You
are
Miguel.
A
A
A
Praise
flows
so,
like
you
can
see
like
exactly
who
dish
praised
to
who
and
like
what
the
the
average
score
of
that
praise
was,
and
so
you
can
see
like
the
bigger
bars
here.
The
people
who
gave
score
that
was
worth
more
or
gave
praise
that
was
scored
higher
and
then
to
who
exactly.
A
A
A
A
A
B
55
55,
okay,
so
like
the
idea,
is
also
give
amount
bigger,
bigger
amounts.
A
A
B
A
Yeah,
there
we
go
and
then
it
kind
of
like
goes
down
down,
and
then
we
bottom
out
at
like
89.
I,
think
that
was
when
most
people
were
on
vacation
or
like
at
Burning
Man
or
something
and
then
back
up
to
176..
A
So
21
people
dish
praised
to
60
different
people
in
the
last
last
two
weeks.
A
Next
one
here
you
can
see
how
many
quantifiers
were
assigned
to
each
round
like
when
we
were
getting
going.
We
used
up
a
lot
of
people,
it
was
like
yeah,
20,
22
4,
here
some
crazy
amount
and
then
the
last
like
four
rounds,
have
been
like
pretty
low,
so
we
only
needed
eight
people.
A
And
then
this
is
like
the
tendency
to
to
underscore
overscore
compared
to
other
people,
but
this
is
like
all
of
the
quantifiers
over
the
last
52
weeks.
So
over
the
last
year.
B
A
A
And
this
one's
cool,
it's
like
the
system,
Health
evaluation.
So
it's
like
number
of
new
Tec
members
involved
in
Praise,
so
we
can
see
new
people
that,
like
showed
up
in,
like
the
praise
data
that
weren't
there,
the
previous
round,
people
that
were
in
the
previous
round
that
weren't
involved
in
Praise
this
round
and
then
the
net
difference
which
you
can
see,
went
up
by
17..
A
That's
cool
so
that's
like
basically
just
measuring
like
involvement
in
in
the
praise.
A
And
then,
for
this
thing
here
this
thing's
a
little
bit
crazy.
This
is
like
the
minimum
amount
of
people
receiving
50
of
the
total
rewards.
So
it's
like
how
many
people
does
it
take
to
receive
over
half
of
the
rewards,
so
it's
like
if
the
number
is
lower.
That
means
like
the
rewards,
are
more
concentrated
to
fewer
people,
and
if
it's
higher,
it's
mean
the
rewards
are
spread
out
among
more
people
right,
because
it's
like
this
one
here
at
six,
that
means
six
people
are
receiving
half
of
the
of
the
rewards
from
that
period.
A
A
And
then
there's
this
one
here,
which
is
like
praise
categorization,
which
is
just
like
we
use
all
these
like
keywords
like
we
have
categories,
and
then
they
have
like
keywords
attached
to
them
and
then
every
time
they
show
up
in
the
data.
Like
those
keywords,
we
like
count
them
in
a
category
so
like
attendance,
so
it's
like
showing
up
to
meetings
or
like
attending
a
call
or
a
conference
or
something
like
that
and
like
the
average
score
is
three
the
highest
is
73
and
the
minimum
is
0.3.
A
A
B
B
A
B
Okay
base
it
on
these
I
think
the
next
time
I'm
gonna
give
higher
higher
like
scores.
I,
don't
know
how
to
say
it.
Mm-Hmm.
A
B
A
Well,
yeah,
that's
pretty
much
it
I'm
gonna,
just
like
write
some
things
down
and
then
like,
if
there's
any
ways
to
improve
or
whatever,
but
like
that's
it.
The
point
of
the
beating
is
just
to
like
look
at
the
data.
Make
sure
like
nothing,
weird
is
happening
and
then
like
write
down
any
ways
that
we
can.
We
can
make
praise
more
useful
for
the
community.
A
A
B
Nice
yeah
man
any
other
questions.
No,
if
if
he,
if
we
need
like
I,
it
can
be
a
quantifier
again
this
period.
If,
if
you
want
yeah.