Hello  everyone. My  name  is  Steve  Hampton.

I  work  at  Precision  Castparts.

I'm  the process  control  manager  there and  I'm  here  today

to  talk  about  unleashing  your  productivity  with  JMP  customization.

I  live  with  my  family in  Vancouver,  Washington.

I  have  been  in  castings  my  entire  career.

The  last  15, I ha ve  been  with  PCC,   which  is  investment  castings,

and  I  am  a  self- proclaimed  stat  nerd.

I  think  this  little  post-it  note,

it briefly   describes   a  lot  of  my  conversation

I  have  with my  wife,

where  she  just  gives  me   a  very  strange  look  as  I  try  and  explain

why  I  am  not  watching  TV   and  I'm  playing  around  on  JMP  on  Saturday,

because  I  have  a  tasty  beer   to  go  along  with  it.

So  when  I'm  not  nerding  out  on  stats,

my  other  thoughts   usually  focus  around  work

if it's  not  around  fun  activities  outside,

and  work  is  pretty  cool.

We  make  a  lot  of  different  products, but  the  one  that  I  really  like  to  show  off

is  this  6  foot  in  diameter one- piece  titanium  casting.

It's  called  an  engine  section  stator.

It  goes  on  the  Trent  XWB  engine   which  goes  on  the  A 350  airplane,

if  you're  keeping  track.

And  you  can  actually  see  it  tucked   right  behind  those  main  fan  blades

in  this  second  picture,

as  the  first  thing  that  the  air  will  see

before  it  enters   into  the  core  of  the  engine.

So  just  a  really  cool  industry  to  be in,

aerospace  and  some  high- tech   investment  castings.

So  why  am  I  here?

Well,  I  love  JMP,

I  love  talking  to  people  that  love  JMP,

and  I  love  talking to  people  that  love  stats.

So  great  to  be  around  like  minded  people.

And  I  hate  clicking  buttons to  get  things  accomplished.

So  if  you  remember  back  in  the  day,

there  is  a  little  known  Christmas  movie   called   The  Grinch,  [inaudible 00:02:02],

and  he  had  a  scene  where  he's  just  saying,  "The  noise,  the  noise, the  noise,"

and  I  feel  like  that's  how  I  am   a  lot  of  times  when  I'm  in  JMP.

It's  the  clicks,  the  clicks,  the  clicks,   they  just  drive  me  insane.

And  I'm  here  because  I  like  flexibility, and  I  think  most  people  do.

So  I  like  to  share  some  things   that  I've  done

to  increase  my  flexibility  with  JMP.

Interesting  note, when  I  thought  about  this  presentation,

this  mindset  actually  started way  back  in  the  day.

I  remember  loving  my  NES, but  the  controller,  very  quickly,

I  had  the  thoughts  on,  "Well,   why  can't  I  have  Jump be  B  and  Run  be A?"

Because  that  worked  better  for  me.

And  then  that  only  got  worse.

The  controllers  got  more  buttons, which  was  great.

Added  to  my  need  for  flexibility

but  it  took  a  long  time  for  them  to  start to  allow  us  to  customize  things.

Now  they're  pretty  good.

But  before  the  consoles  got  pretty  good, I  really  found  my  benchmark

for  life  of  interfacing  with  a  program   in  computer  games,

because  not  only  do  I  have a  keyboard  that  had  tons  of  buttons

so  I  could  just  immediately  cause an  action  to  take  place,

but  I  could  remap  all  of  them.

So  that's  been  my  baseline

when  I  compare  everything  that  I  interact with  that's  electronic  to  that.

So  there  is  hope,  though,

because  we  have  the  humble  toolbar, at  least  you  think  it's  humble,

and  the  scripting,

which  is  everyone  that's  involved   with  it  knows it's  incredibly  powerful.

Real  quick,  our  first  efficiency  power  up  is  the  toolbar.

So  it's  like  Mario  getting   a  little  mushroom  there.

He goes  from  a  small  little  guy   to  a  bigger  guy.

A  toolbar  is  by  default  pretty  limited,   but  it's  really  easy.

Just  go  turn  on  things   and  you  immediately  have  a  lot  of  access

to  things  you  can  do with  just  one  click  on  actions

that  you'll  probably  do  a  lot   during  data  manipulation.

So  I  recommend  you  keep  on  Reports, Tables,  Tools,  Analyze,  and  Data  Table,

which  I  marked  up  here in  red  boxes  on  the  right.

Another  tip  is  that  you  can  actually  turn on  toolbars

for  these  windows  differently   or  independently,

and  you  can  move  them   around  independently,

which  is  really  nice  if  you  want   to  have  a  custom  set  for  each  window,

but  be  careful,   if  you  move  around  too  much,

you' ll  lose  some  of  your  efficiency   as  your  hunt  for  where  the  icon is,

has  changed  from  one  window  to  another.

Even  better,  you  can  make  your  own.

So  if  you  go  into  the  customizing  toolbars and  new  toolbar,  you  can  make  your  own.

You  see  all  those  blue  ones are  ones  that  I've  made.

I  think  I've  actually  now  made   more  toolbars  for  myself

than  come  in  JMP.

So  w inner winner chicken dinner,  I  guess.

And  the  black  ones  are  actually  ones

that  I've  added   some  additional  icons  to  as  well.

So  I  think  that  combination  gets  you  to  raccoon  Mario,

which  I  thought  was  a pretty  neat  stuff   back  in  the  day.

Always  wanted  to  be  raccoon  Mario.

Just  some  real  quick  other  little  things before  we  get  into  JMP

is  you  can  link frequently  used  buttons   if  you  use  the  built in  command.

This  really  works  well   if  you  still  want  to  be  able  to  undo

when  you  click  something.

If  you  link  to  a  script  and  you  run  it, you  can't  undo  it,

which  is  a  little  bit  annoying,

but  I  usually  put  my  script   as  a Run JSL  in  this  file  so  it's  linked,

not  embedding  it  in  the  toolbar,

because  then  I  can  change  the  file   outside  of  the  toolbar

and  update  the  functionality

without  having  to  dig  back   into  this  toolbar  menu.

You  can  use   built in  icons.

I  use  PowerPoint  to  just   give a  shorthand  of  what  the  icon  does

and  then  save  it  as  bitmap  and  upload  it.

It's  not  great.

If  anyone  has  any  better  way  of  doing  it, I'd  love  to  talk  to  you  at  some  point.

But  then  you  can  also  assign  shortcuts, you  can  hide   built in  toolbar  icons

that  you  don't  really  want   to  be  interested  in.

You  can  also  add   to  your  standard  toolbars.

So  really  scripting  in JMP  is  super  powerful,

and  then  when  you  combine  it with  the  toolbar,

you  get  a  pretty  legendary  efficiency  team that  I  think   looks  like  this.

That's  how  it  appears   when  I  think  about  the  combination.

So  let's  get  into  JMP.

So  I  have  this  data  table  here, and  it's  got  a  lot  of  columns.

Normally,  this  would  take a  fair  amount  of  cleaning  up.

First  thing  I  do  is  just  understand,

is  there  the  right  column  types and  the  right  column  amounts?

So  I  can  immediately  see   these  two  columns  that  are  highlighted,

that  they're  supposed  to  be  continuous.

You  normally  could  right  click,

go  into  column  info  and  change  things  up  here.

It's  already  bothering  me because  that's  too  many  clicks.

I  can't  change  it  to  continuous  here because  it's  a  categorical  base.

So  I  made  myself  a  little  macro   that  I  can  go  ahead  and  click

and  it's  done.

No  matter  how  many  I  select,  it's  done.

It kind of  is  a  combination.

It's  a  one  click  standardized  attribute,  which  is  great.

You  can  also  see  over  here

I  have  this  column  that's  the  date   and it's  messed  up.

Once  again,  I  don't  want  to  right  click and  dig  into  subfolder.

I  just  want  to  click  and  go.

So  I  have  made   myself a  two  date  function  here.

So  now  I  have  a  two  date.

I  also  have  this  batch,  which  is  right, it  is  technically  continuous,

but  a  lot  of  ways  I  want   to  use  it  would  be  more  ordinal,

but  I  want  to  have  both.

I've  made  myself  a  script   that  just  throws  out  another  column

called  Batch  Nom and  it's  now  a  nominal  column.

And  the  reason  that  you  might  want   to  use  this,

if  I  select  these  guys   and  go  into  a  filter,

maybe  I  want  to  filter  being  able  to  drag,

but  if  I  want  to  grab  just  a  single   or  just  a  couple  batches,

then  it's  a  lot  easier  to  do  it   in  the  nominal  state.

And  also  the  way  it  shows  up   on  some  of  the  graphs

can  be  better i n  one  way  or  the  other.

Then  the  next  thing  we  can  do  is  see  that  this  date  is  individual  date  for  a  day.

A  lot  of  times  we  roll  things  up  by  weeks.

So  I  could  use   the  awesome  built  in  formula  columns

and  go  and  get  a  year  week  column  as  well,

but  it  doesn't  really  mean  a  lot for  most  people  because  it's  not  a  date.

It's  like,   "What  does  the  week  five  2020  mean?"

So  I  have   built in  a  function   where  I  take  the  date

and  it  will  return the  next  Sunday  after  that  date.

And  so  now  I  have  a  weekend  column   where  I  can  bin  it  by  weeks

and  it's  really  easy  for  people to  understand

and  it's  continuous  versus  the  other  way  of  doing  it  makes  it  nominal.

So  a  lot  of  advantages  to  me  in  that.

So  I  have  just  a  lot  of  things that  helps  me  clean  up.

The  last  thing  is  since  this  came from  the  categorical  to  numeric,

then  it  has  some  missing  things  in  here.

I  know  these  missings  are  actually  zeros

because  if it  doesn't  have  any  data, it  means  there  wasn't  any  defect.

So  since  I  do  this  a  lot,

I  actually  have  this  recode  missing to zeros  and  recode  zeros  missing.

So  recode  missing  to  zeros, there  we  go.

So  I  haven't  had  to  actually  go  in  here, recode  and  then  do  more.

Once  again,  already  too  much  typing.

For  data  manipulation  steps  that  you  do,

adding  in  some  scripting  really  can  make you  super  effective  in  the  data  cleanup,

and  so  you  don't  have  to  think   about  scripting  just  for  analysis

that  you're  running  a  lot.

Just  think  about  it  in  more  micro steps to  get  some  efficiency  gains.

The  next  thing  is,

I'm  going  to  take  us  into  Graph  Builder, and  let's  bring  this  up.

And  so  I  spend  a  ton  of  time   in  Graph  Builder

because  it's  one  of  my  favorite  platforms.

You  really  get  a  feel  for  your  data and  it's  easy  to  get  people

that  maybe  aren't  as  deep  into  stats to  understand  what's  going  on.

So  this  is  probably  the  main  platform  I  live  in.

And  as  I  bring  this  up, immediately  you  can  see  like,

"Oh  well,  since  defect  one   is  not  in  the  right  condition,

the  graph  doesn't  look  great."

But  the  nice  thing  is  that  I  don't have  to  go  to  the  data  table.

When  I  first  started,

I  hated  going  back to  the  analysis   or in the  data  table.

Or  I  put  them  side  by  side,   but  then  everything  gets  crunched  up.

So  what  the  win  was  here   is  that  by  learning  about  the  report  layer

and  being  able  to  pull  out  the  state of  different  reports,  in  this  case,

I  can  pull  up  the  state  of  what is  selected  in  this  box,

I  can  actually  select it  in  the  data  table.

So  now  that  is  selected  in  the  data  table,

and  I  could  use  my  Go  To  Continuous, and  now  I'm  back  in  business.

So  I  call  this  staying  in  the  workflow.

I  learned  about  that  term  from  watching an  on  demand  webinar  about  formulas

and  they  were  talking  about  staying  in  the  workflow  as  far  as  staying  in JMP.

Don't  go  to  Excel,  do  some  formulas   and  bring  it  back  into  JMP.

Like  learning  this  use  of  formulas  in JMP because  its  formula  maker  is  amazing

and  you're  staying  in  the  workflow.

So  I'm  saying  you're  staying   in  the  workflow

of staying  in  your  analysis  window, and  that's  where  you  want  to  live.

I  don't  want  to  have  to  go  back   to  the  data  table.

So  I'm  going  to  use  a  standard  toolbar to  put  a  column  switcher  on

and  we're  going  to  get  all  of  these...

Oh  my  goodness, all  of  these  columns  here.

So  we  got  a  column  switcher,

and  I  also  have  put  in  another  script  here

where  I  can  now  select  from  the  data  table with my  column  switcher,  which  is  great.

And  it  opened  up  another  world of  using  a  script  that  Jordan  Hiller

had  helped  me  with  when  I  was  just  starting  down

my  scripting  path   of  what  we  called  newcome.

So  it  was  a  way  of  taking  data,

this  data  is  not  good  data, it's  not  fully  completed  parts.

So  I  want  to  get  rid  of  this, but  I  don't  want  to  just  hide  and  exclude.

If  I  use  my  little  shortcut,  Ctlr+Q, that  I  remapped,  that's  gone.

That's  what  I  wanted  on  this  slide,

but  now  I  lose  all  the  information on  that  row.

And  I  don't  want   to  have  to  use  Row E ditor,

I  don't  want  to  have to  use  subsect  with  linking.

That's  all tuny c licking.

So  what  I  have  here,

I'm  on  the  right  response   in  the  column  switcher,

I  can  select  these  guys and  I  can  run  my  newcome  script

and  now  those  data  points  are  removed.

So  very  quickly,  you  can  go  through with  the  column  switcher  and  the  newcome

and  be  able  to  remove  data   that  is  either  an  outlier

that  you  know  shouldn't  be  in  the  data, or  is  causing  problems,

or  is  actual  bad  data  that  should  be  out.

And  I  see  a  lot  of  bad  data in  the  form  of,

it's  out  of  place  in  the  sequence  of  time.

So  this  one's  obvious,  right?

That's  obviously  bad  data.

It's  obvious  to  me.

So  I'm  just  going  to  blow  it  out.

So  here's  an  interesting  one.

This  is  my  interesting  one  at  first.

So  you  can  see  that  the  A,

it's  got  some  really  crazy  ones  here,  and  these  are  all  bad  data.

So  another  way  you  can  look   at  that  is  I'm  going  to  use...

This  toolbar  is  actually  something   you  can  just  select  as  a  standard  script.

You  can  just  select this  function   in  JMP  to   redo.

So  now  I  have  my  new  column.

I  can  take  this  out   and  I  can  do  a  box  spot

and  I  can  say, "Okay,  cool,  here's  outliers."

So  that's  a  way  to  blow  things  out.

You  can  see  I  had  a  lot  of  them, but  these  guys  are  not  outliers.

And  really,  I'm  using  outliers   in  place  of  bad  data

because  bad  data usually  shows  up  as  an  outlier.

But  these  ones  were  not.

[inaudible 00:14:40]  show  up  as  an  outlier  in the  box  spot.

They  are  not  bad  data.

So  I'm  going  to  nuke  out  all  these  guys.

And  you  can  see  now,

I  don't  have  anything  on  the  low  side that's  saying  is  an  outlier,

but  I  do  know  that  I  have  outliers  still

and  they' re  outliers   that  I'm  going  to  call  in  time.

So  this  is  so  far  away   from  the  other  data  points

that  I  know  from  my  experience and  looking  at  the  [inaudible 00:15:10]

that  these  are  not  real  data  points, they  are  data  that  we  have  jacked  up.

So  I  can  go  in  here   and  select  all  these  points

that  are  bad  data  because  of  where  they  are  in  time

and  get  rid  of  those.

And  you  will  never  see  that   from  a  standard  outlier  analysis.

So  now  I  have  a  very  nice  looking  curve, everything  is  cleaned  up,

and  I  was  able   to  do  that  pretty  darn  fast.

So  it's  a  really  powerful  tool.

If  we  go  back  along  here, this  is  an  interesting  one.

So  I  can  see  that  I  have this  outlier  right  here.

I'm  going  to  nuke  it.

But  you  can  see  that  there  is  a  shift,

and  I  unfortunately  in  my  data  table   try to  label  it  as  a  trial.

So  I  could  use  the   right  click row, name  selection  and  column,

but  there's  still  a  lot  of  steps  in  there, so  I'm  just  going  to  select.

And  I've  made  myself  a  binning  column.

So  when  I  click  this, whatever  was  selected  is  now  binned.

So  I  can  very  easily  see  what's  going  on.

I  can  now  even  add  in  my  text  box and  see  the  differences  of  the  means.

That's  really  useful.

I  mean,  you  can  bin  things as  trial,  not  trial.

I  use  good,  bad  a  lot.

So  if  my  continuous  data  isn't  great because  of  the  measurement  system,

but  it  does  do  an  okay  job, it's  just  saying  the  part  is  good  or  bad,

I  can  bin  it  with  this

and  then  do  an  analysis   with  the  pass,  fail,

like a  logistics  analysis.

So  that's  great. I  also  really  like  the  dynamic  selection.

So  if  I  were  to  go  back  here,

I'm  going  to  take  the  binning  off.

And  now  I  have  this  selected  column

where  it  just  changes  it  to a  one if  I  select  it.

Now,  I  can  dynamically  go  through   and  select  different  things,

and  I  can  see  the  mean.

[inaudible 00:17:16]  j ust  real  quickly.

Okay,  this  grouping  right  here, its  mean  is  100  and  above  it  is  288.

And  it's  really  useful for  poking  a  data.

Let's  say  right  here,  what's  going  on  with  this  data?

One,  I  can  select  it   and  see  what  differences  and  means  are.

But  then  two,  I  could  see  what  the  trend would  have  been  like

if  this  had  not  happened.

So  I  can  do  a  little bit  investigation.

And  then  I  actually  use  inverse  selection  a  lot,

which  is  buried  in  the  row  menu.

So  I  just  have  a  toolbar  here, so  now  I  can  inverse  it.

Everything  basically is  the  same

except  for  that  now   the  bulk  of  the  data  is  highlighted,

which  sometimes  makes  it  easier.

So  that's  great  to  use  to  analyze.

The  other  thing  I  have   is  sometimes  you  might  want  to,

say  based  upon  what's  selected  here,   what  else  is  selected?

So  I  call  this  my  selected  other  columns.

And  then  we're  going  to  go  and  say,

for  this  little  grouping   that  was  different,

what else  shared  the  equipment one that  this  grouping  used.

And  when  I  click  that,   you  can  see  that  barely  any  of  the  rest

of  the  B  product  used  equipment  one  level,

but  a  lot  of  item  A  did, and A  is  actually  higher  here.

So  it  might  be  something  that  if  we  wanted to  possibly  not  have  this  higher  level,

maybe  we  need  to  look   at  using  the  same  equipment

that  the  rest  of  B is  using.

A  lot  of  different  ways  to  slice and  dice  and  learn  things.

The  last  thing  is  it  could  be   I  have  two  products  here,

but  let's  say  I  don't  want   to  do  two  products,

so  I  want  to  subset  it.

So  I  would  go  in,   I  have  these  subsetting  icons,

because  once  again, I  just  want  to  do it in  one  click

and  I  do  a  lot  of  subsetting   so  it  makes  sense.

So  now,  I  have  this  new  table.

But  what  if  I  want  to  have  the  same graph  though,  and  build  that?

I  don't  necessarily  want   to  have  to  rebuild  it  from  scratch,

and  there's  some  other  ways   to   copy  and  paste  some  scripts  over,

but  I  do  this   enough  that  I  actually

am  going  to  save  the  script to  the  clipboard

and  then  I  can  bring  this  back

and  I  can  actually  run  the  script   from  my  clipboard.

Hey,  now  I  have  a  graph

and  it's  all  built  up  the  exact  same  way   I  had  before.

So  this  is  a  really  nice  way

to keep  the  efficiency  you  had from  a  previous  table  with  a  new  table.

Now,  you'll  see  here, I'm  going  to  close  this

and  it  pops  up  a  window   because  it's  saying,

"What  do  you  want  to  do   with  your  other  windows that's open?"

And  then  if  I  were  to  click   what  to  do  with  that,

it  [inaudible 00:20:24]  say,

"Hey,  you  didn't  save  this,   what  do  you  do  with  that?"

And  it's  like  a  lot  of  times   I  have  subset  windows

just  because  I  want to  be  exploring  things.

And  so  all  the  clicking to  close  things is  driving  me  crazy.

So  I  actually  made  myself  a  little close  everything  around  that  table.

And  if  you're  in  a  window, it'll  go  close  the  base  table

and  it  doesn't  ask  you  anything.

So  I  can  do  real  quick  little  explorations on  little  data  sets  and  then  close  it  down

and  just  stay  in  the  workflow  and  go  fast.

If  I  did  want  to  save  something, I  made  this  little  macro

where  it's  going  to  save  out   in  a  generic  name

to  a  standard  file  location.

And  so  I  don't  have  to  think  about  like,

where  am  I  going  to  save  it   and  dive  into  a  bunch  of  save  menu.

So  if  I  want  to  move   it  a  later  time,  I  can,

but  I  know  at  least  where  all my  main  things  I  want  to  keep  are.

And  then  if  I  do  change  something,  say I change something...

Actually,  let's  even  say   I  change  something  from  the  graph.

So  I'm  going  to  blow  out  all  these  guys.

And  if  I  wanted  to  now  save  this, I  can't  just  click  save

because  that's  going  to  try   and  save  this  window.

So  I  found  it  really  useful   to  just  have  the  save  data  table  button

that  shows  up  so  I  can,  once  again,

stay  in  the  workflow  of  the  analysis  window

and  save  my  base  data  table.

And  once  I'm  done, I  can  close  and  get  out  of  there.

All  right.

That's  everything I  wanted  to  cover  for  there.

So  let's  move  on  to  a  real  quick  example for  functional  data.

This  will  be  super  quick.

For  functional  data, the  one  thing  I  use  a  bunch  is,

if  I  have  functional  data   that  has  a  timestamp,

you  can  see  that's  not  super  useful   if  I'm  trying  to  look  at  all   my  lots

because  there's  a  big  gap   between  the  times.

I  could  possibly  step  through

and   see  what  the  shape  is  looking  for.

That's  not  super  fun.

And  so  what  I  have  is  I  have  this.

I make  a  counter  column   which  just uses  the  cumulus  sum  function.

I  can  say,  "What  do  I  want  to  do  it  by?"

And  I  can  add  up  to  four  items that  I   subgroup  the  cumulative  sum.

I'm  just  going  to  do  pieces

because  that's  really   the  only  thing  that  matters,

and  what  I  get  out  of  that   is  I  get  a  counter  column

that  now  everything  shows  up  nice   on  one  graph.

And  this  is  really  good,

but  it  only  works  well   if  the  timestamps  are  pretty  comparable.

If the  timestamps  are  all  over  the  place

because  it's  assuming   the  timestamps  are  the  same,

then  you  have  to  get a  little  bit  more  creative.

Okay.

So  back  to  the  presentation.

So  we  got  through  all  these  things, but  what  I  really  want  to  show

as we tail out  of  here  is,

for  the  ultimate   in  freedom  and  efficiency,

you  need  to  use  scripts to  expand  JMP's  functionality

to  fit  your  exact  needs.

So  there's  a  lot  of  times,

and  hopefully  you're  putting them into  the  wished  lists  on  the  community,

but  there's  a  lot  of  simple  ones   you  can  actually  take  care  of  yourself.

So  you  can  see a  nuclear  Godzilla  up  there

and  we  all  know  that  a  nuclear  bomb  plus Godzilla  makes  him  king  on  the  monsters.

And  so  it's  a  little  known  fact  probably

that  JMP  plus  scripting  of  functions makes  you  the  king  of  data  analysis.

And  I've  gotten  a  lot  of  value from  the  scripting  index,

the  two  JMP  books  that  are  listed  here and  the  user  community,

especially  these  two  guys   who  I  owe  massive  amounts  of  beer

as  gratitude  for  the  time  they  saved  my  bacon

and  probably  thousands of  other  people  as  well.

So  let's  get   into  what  we're  going  to  do  here.

So  the  first  thing  is, we'll  go  back  to  this  table.

If  I'm  just  doing  more   of  an  exploratory  analysis

or  trying  to  get  an  explanation  model versus  predictive  model,

I'll  use  partition without  a  validation  column.

And  this  is  nice  because  people that  don't  have  JMP  pro,

they  can  use  this  as  well.

And  what  I  do  is...

Yeah,  we'll  just put  all  this  stuff  in,  that'll  be  fine.

And  we're  going  to  go  click O kay.

And  now  I  can actually...

I like  to  split  by  LogW orth,   so  I  can  actually  split  by  LogW orth

and  it's  showing  the  minimum  LogW orth  out  of  this  tree.

And  so  I'll  just  split until  I  get  below  two.

Okay,  there's  two. Go  back,  and  here's  my  model.

Our  square  is 44.9.

Now,  whenever  counts  get  low,

I  do  think  that  I  might  be overfitting  a  little  bit,

which  is  why  I  like   this  minimum  split  size,

so  I  can  prune  back.

Let's  just  say  minimum  split  size  is  way  too  low.

So  I'm  going  to  go  15

and  then  okay.

So  definitely  left  splits.

Our  square  is  still  not  too  bad,  and  we  can  see  our  main  factors

that  are  contributing  to  our  defects.

These  top  three,

I  really  like  using   the  assess  variable  importance

since  it  reorders  what  you're  looking  at   into  the  main

or  the  first  boxes  in  the  order.

And  I  love  the  optimize  and  desirability.

Once  again,  you  have  to  keep  clicking into  the  red  box  to  run  this.

So  I  came  up  with  a  little  macro to  control  the  profiler .

So  I  can  actually  come  in  here  and  say, "All  right,  I  want  to  first  maximize

because  it  defaults  to  max

and  I  can  now  remember  the  settings and  we'll  say  max,

and  then  I  can  alter  the  desirability to  make  it  to  the  min

and  I  can  maximize  and  remember  settings and  we  could  say  min.

I  could  copy  the  paste  settings,  set  to  a  row.

I  could  link  profilers   and  it's modal.

Or  non-modal,  I  apologize.

So  it  can  just  stay  up and  out  of  the  way  when  I  don't  need  it,

but  yeah,  it  makes  using  the  profiler,

which  is  already  just  super  powerful, super  efficient  as  well.

That's  what  I  really  like, and  I  suggest  you  grab

from  when  I  put  them  onto  my  page   for  this  presentation.

Then  the  next  thing  is,  I  got  to  go  back  here.

I'm  going  to  do  some  neural  net  stuff.

So  I  definitely  want  to  make a  validation  column.

So  I  have  these   built in  ones of  the  splits  that  I  like,

so  it  automatically  creates  it  for  me.

So  now  I  have  my  validation

and  I  have  a   normal  random  uniform  one

in  case  I  wanted  to  do any  prediction  screeners.

And  that  helps  with   looking   at  cut  out  points,

but  in  this  case,   we're  just  looking  at  neural  nets.

And  where  I  got  from  here   is  I  really  like  the  Gen  Reg,

how  it  has  this  model  comparison,

and  I  really  like  in  Bootstrap  Force how  you  have  a  tuning  table.

When  you're  using  a  neural  net, it  can  be  very  painful

to  feel  like  you're  getting   the  right  model

because  every  step   you  have  to  change  it,  rerun  it,

and  then  look  to  see  what's  going  on.

And  sometimes  it  just  feels  like you're  spinning  wheels.

So  through  time,   I  found  some  models  that  I  really  like,

and  so  I  just  built  this  platform   where  I'm  going  to  recall.

Here's  everything,

and  I  put  down  the  number  of  boosts,

number  of  tours is  really  low   just  so this  run  faster.

And  I  can  go  ahead  and  run  this.

And  so  what  it's  going  to  do  now,

is for  the  models   that  I've  put  into  my  tuning  table,

ideally  down  the  road,

I  like  to  have  a  tuning  table  be   a  little  bit  more  in  that  first  menu,

but  not  there  yet.

So  what  I  will  get   is  I'll  get  this  nice  preto

showing  my  test,  my  training  validation and  the  different  models.

And  so  I  can  go   through  [inaudible 00:28:45]  cool.

Which  one  got  me  the  closest

without  having  to  run   these  each  individually?

So  I  do  see  that  it  looks  like this  TanH(10)Linear(10)Boosted(5),

overall,  the  average  of  all  the  R  squares puts  it  at  the  highest,

and  it  looks  like  everything's   pretty  close.

So  let's  just  start  with  this  one.

And  the  next  thing  I  like  to  do is  actually  look  at  the  min  and  maxes,

and  see  did  it  actually  predict in  the  range  that  I  was  expecting?

So  let's  see,   what  did  we  say?

I said 10, 10  and  5  boost.

So 10, 10 and boost five. There  we  go.

So  I'll  look  at  the  min  and  max.

So  it predicted  5- 112.

It's good,  it  didn't  predict  negative.

That's  definitely  something  I  look   for  a  model  with  defects  or  hours,

because  you're  not  supposed   to  have  zero  on  any  of  those

or  negatives  on  any  of  those.

And  the  defects  we  had   was  1- 51.

So  yeah, it did okay.

It's  predicting  on  the  high  side,

so  I  might  go  in  here  and  be  like,

is  there  anything  else  that  was  actually  predicting  on  the  lower  side  or  closer

and  still  had  good  test  values?

So  this  is  a  really  powerful  tool

because  then  I  can  just  go into  my  actual  window  here

and  I  can  go  down  here   and  this  is  my  model.

And  I  could  save  my  model  out.

I  could  save  this  first  formula  out, I  can  save  this  neural,

just  a  certain  one  to  my  data  table and  then  just  use  that  from  here  on  now.

And  it's  already  got  built in  my  minimaxes  here.

Let's save  from  there.

I  find  this  to  be  a  very  powerful improvement  for  the  neural  net  platform,

which  I  already  think  is  pretty  powerful.

And  then  also  if  you're  just   in  standard JMP,

the  last  thing  I'll  show  is,

I started  trying  to  give  some  additional functionality  for  standard  JMP  people.

And  so  here,  you  can...

It contains   how  many  initial  nodes  you  have,

what's  the  number   that  you  want  to  step  the  nodes  up,

how  many  loops  you  want   to  go  through

with  your  validation  percent,

and  if  you  wanted  to  do  assess  importance,  you're  going  to  click  Okay.

And  what  it  does  is,

it  runs  all  your  models

and  it  does  the  same  thing   except  for...

I  had  a  chance  here  to  work  on  getting the  min  max  improved.

So  here  I  can  see.

Here's  my  min  max, is  what  I  was  actually  predicting,

and  then  here  I  can  see my  training  and  validation.

So  ideally  you  want  them  to  be as  close  together  and  as  high  as  possible

and  then  predict  well.

So  here  I'm  looking  at  TanH(8), which  puts  me  here.

So  that's  pretty  good.

So  that's  probably the  one  I  would  go  with.

They're  the  closest, it  doesn't  overpredict.

This  one  actually  is  predict...

Even though it has  a  higher  training, this  one  has  a  higher  training,

they're  actually   predicting  negative  values

and  then  this  one  seems like  it's  getting  over complex.

So  that's  what  I  would  go  with.

It's  pretty  useful  for  more  standard  users to  get  some  more

out  of  the  neural  net  platform  for  them.

Finally,  let's  just  go  quickly   to some  dim  data  stuff.

We  have  the  dim  data  example   of  get  specs.

So dim data example.

So  if  our  process  that  we  do   at  our  plant

is  we'll  get  a  bunch  of  data   and  then  we  will  calculate

a  spec  limit  from  that.

Usually  it's  either  three   or  four  sigma spec limit,

so  PPK  of  1  or  1.33,

and  then  we'll  present   that  to  the  customer.

That  can  take  a  long  time  in  old  days where  we  would  manually  run  analysis

and  then  best  fit and  then  write  it  down

or  just  use  the  normal  distribution   for  everything

and  then  calculate  it  in  Excel.

You  have  this  option  in  JMP  to  do  process  capability

and  you  can  change  it   to  calculate  it  off  of  a  multiplier.

And  that's  great   because  then  you  get  your  specs.

The  problem  is  you  have  a  lot.

Even  if  you  hit  the  broadcast  button, you  have  to  enter  that  for  each  one.

So  what  I  did

was  definitely  with  help   from  a  bunch  of  other  people,

because  this  got  above  my  pay  grade  and  scripting  very  quickly,

is I  went  in  and  made  this  macro where I could say,

what  do  you  want  the  signal number to  be?

Click  Okay  and  it  goes  through

and  it  will  spit  out  this  for  everyone or  every  distribution.

Now  I  can  right  click,   go  into  make  combined  data  table.

I  have  my  data  table.

Then I  can  go  here, select  all  for  lower- up  spec  limit,

use  my  Subset  button,  and  this  here,

now  I  can  submit  that  to  the  customer.

Here's  my  upper- lower  spec  limits  for  all  these  things.

I  did  that  in  hopefully  less  than  a  minute

and  it  used  to  take  someone   to  do  that  half  their  day,  if  not  more.

So  using  scripting  to  improve   what  you  want  to  do,

and  the  functionality   and  flexibility  is  great.

Dim data  unstacked  table, where  is  that?

Dim data unstacked table.

Coming  in  at  the  home,

here  we  have  a  bunch   of  dimensional  data  done  by  parts.

The  thing  is,  some  of  it  is  subgrouped

and  some  of  it   is  [inaudible 00:34:57]  data.

By  using  my  subgrouping  macro,

I  can  select  all  my  Ys, say  what  I  want  to  check,

and  it  will  then  put  it  as  a  subgroup or  as  an  individual.

And  that  allows  me  to  go  in   and  use  my  Control  Chart  Builder.

So  I  can  say  these  are  individuals, these  are  subgroups,

and  I'm  going  to  subgroup  by  this.

Click  Okay, and it  takes  a  little  bit  to  run.

So  I  have  one  here, and  it  will  actually  put  all  the  mixed

control  chart  types  all  in  one  window,

which  is  really  nice  because  then I  can  now  actually  make  a  combined  table

of  everything  of  the  control  limits   in  one  table,  which  you  can't  do.

You'd  have  to  do  a  lot  more  steps

of  concatenating   individual  tables  together.

So  that's  great.

You  can  also  do  the  same  thing with  Process  Screener,

where  I  can  put  in  individual  and  IMR  here and  then  XB ar  stuff  here,

and  I  can  output  a  table  here

that  shows  for  mixed   subgrouping  types  IMR  and  XBar,

and  I  can  see  the  PPK  of  them

and  their  out  of  spec  rates   and  their  alarm  rates  all  in  one.

So  it's  nice  to  be  able   to  keep  everything  together

and  have  multiple  windows  open  depending  on  their  subgrouping  type.

And  finally,  the  gauge  R&R.

Gauge R&R,  especially  something  like  a  CMM,

where  you  can  have  a  lot  of  codes   to  do  [inaudible 00:36:44]   on,

so  it  can  be  a  lot  of  work.

So  I  made  a  macro.

The  first  thing  you  got  to  do   to  make  this  work  really  well

is  you  got  to  add  in  specs.

So  I  have  this  little  script  I  made   where  I  can  select  columns

and  then  I  can  append  columns  if  I  need  to.

If  I  forgot  one,  I'm  going  to  load   from  a  spec  table,

click  Okay,

and  then  I  will  save  this to  the  column  properties.

And  I  can  actually  use  this  as  non-modal,

so  I  can  just  keep  it  off  the  side in case you  want  to  change  something,

and  then  I  can  go  in   and  run  my  selected  column  gauge  R&R.

We're  not  going  to  go  too  crazy, but  I'll  just  select  these  guys.

It says,  "Hey,  you're  going   to  run  a  gauge  R&R in these.

A re  you  okay  with  that?"

Click  Okay.

We'll  say  part  and  operator  and  go.

It  won't  take  too  long.

And  why  this  is  nice?

Is  because  you  can  see   that  if  I  go  to  connect  the  means,

that  connects  really  nicely  like  you'd  expect.

If  I  were  to  pull  up   a  traditional  gauge R&R ,

then  it  gaps   because  I  don't  have   for  each  hit  number,

because  the  hit  number for  different  codes  are  different.

I'm  missing  data.

So  these  don't  apply   to  this  actual  item

and  it  makes  the  charts  get  all  messed  up.

But  by  using  my  macro,

I  can  have  a  local  data  filter   for  each  item.

And  when  I  select  that  local  data  filter, then  all  the  things  I'm  not  using  go  away.

Now  the  charts  look  great.

That  adds  a  lot  of  how   those  charts  look  improvements.

All  the  data  down  below  is  the  same.

Okay,   that  got  us  through  everything.

So  I'm  going  to  move   on  to  some  final  thoughts.

Okay,   final  thought.

So  I  definitely  encourage  you  to  use  the  toolbar.

Consistent  layout, icon  use  and  naming  conventions

are  key  for  your  effectiveness.

Get  into  scripting.

Here's  some  things  I  suggest   that  you  focus  on,

and  definitely  use  the  log  now that  it  will  record  your  steps  for  you.

It  saves  you  a  lot  of  typing.

And  really  think  beyond   what  JMP  currently  does

and  try  and  see  if  you  can  actually  add   that  functionality  yourself.

For  developers,   I  like  to  keep  moving

to  keeping  commands  as  flat  as  possible   to  get  things  out  of  submenus.

And  for  me,  I'm  working  on  getting  better at  making  icons,

learning  how  to  reference and  pull  data  from  the  analysis  window,

which  is  called  the  report  layer, and  always  including  a  recall  button.

So  there  are  some  statistical  jokes   for  you,  some  of  my  favorite,

and  that's  what I got.

So  thank  you  very  much  for  your  time and  do  we  have  any  questions?