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Want To Know What Analysis You Need? Just Ask the Data Analysis Director (DAD) (2023-EU-30MP-1204)

When analyzing data, scientists and engineers often know what they want to accomplish but are unsure which statistical test is needed. This talk introduces a new Add-in, the Data Analysis Director (DAD). This Add-in was designed to make it easier to find the proper statistical test in JMP® based on the analysis task, goal, and type of data you have. DAD provides a guided flow to help you find the right analysis and run it in JMP. It includes built-in examples, links to JMP Help, demo videos, and even lets you launch the analysis on your data. As you will see, DAD is a useful tool that can help guide you along your analytic journey.

 

 

Thank  you  for  the  introduction.  My  name  is  Mia  Stephens,  and  I  am  a  JMP  product  manager.  And  I'm  also  the  lead  developer  of  STIPS,  which  is  our  free  online  course  that  we'll  talk  about  in  a  few  moments.

And  my  name  is  Peter  Hersh.  I'm  part  of  the  JMP  Global  Technical  Enablement  team,  and  I  did  a  lot  of  work  finishing  up  and  developing  the   Data Analysis Director,  which  we're  going  to  be  covering  today.

I'm  going  to  get  us  started.  We'll  start  by  talking  about  STIPS —Statistical  Thinking  for  Industrial  Problem  Solving —and  how  the  development  of  STIPS  was  really  the  beginning  of  the   Data Analysis Director  or  DAD.  If  you're  familiar  with  STIPS,  this  is  our  free  online  course.  If  you  were  at  the  Discovery  in  Frankfurt  a  few  years  ago,  you  heard  us  talk  about  this  for  the  first  time.

STIPS  is  30 -35  hours  of  online  training  for  anyone  who  wants  to  learn  how  to  build  a  foundation  in  statistical  thinking.  It  covers  the  basics,  from  learning  how  to  define  a  problem;  exploratory  tools,  and  how  to  communicate  the  message  in  your  data,  how  to  prepare  your  data  for  analysis;  quality  methods,  SPC  capability,  measurement  systems  analysis;  basic  inferential  statistics  like  hypothesis  testing  and  sample  size;  correlation  and  regression; fundamentals  in  design  of  experiments;  predictive  modeling,  and  text  mining.  This  is  just  an  introduction  of  these  topics.

All  in  all,  it's  about  30 -35  hours.  As  we  set  out  to  develop  this  course,  we  wanted  to  make  sure  that  we  included  the  right  topics  and  topics  that  are  most  commonly  used  in  the  industry.  And  we  also  wanted  to  make  sure  that  we  understood  the  challenges  that  users  face  in  industry.

Before  we  started  developing  any  content,  we  did  a  survey.  One  of  the  questions  we  asked  was,  what  are  the  most  common  analysis  tasks  and  methods  that  you  use  in  industry?  SPC  was  at  the  top  of  the  list  with  some  of  the  other  quality  methods,  DOE  and  hypothesis  testing.   This  part  of  the  survey  allowed  us  to  identify  the  general  groupings  of  topics  that  we  would  include  in  STIPS.

And  relevant  to  this  talk,  the  second  question,  what  are  the  biggest  challenges  you  face  when  you're  using  data  to  make  decisions?  We  weren't  very  surprised  to  see  data  preparation  at  the  top  of  this  list,  but  something  that  was  a  little  bit  surprising  was  understanding  which  method  to  use  and  how  to  use  it.

As  we're  developing  STIPS,  there  are  a  lot  of  topics  included  in  STIPS,  and  if  you're  learning  statistics  for  the  very  first  time,  we  knew  that  this  could  be  a  little  bit  overwhelming.  We  developed  this  concept  of  a  tool  that  would  help  you  understand,  "Well,  which  method  do  I  want  to  use  based  on  what  it  is  that  I  want  to  know,  what  it  is  I  want  to  do  with  data,  and  what  type  of  data  that  I  have?"

A t  the  time,  we  call  this  the  Data  Analysis  Assistant.   It  was  basically  an  unfolding  utility  where  it  started  with  just  a  general  statement.  In  general,  what  is  it  that  you  want  to  do?  And  then  based  on  how  you  answer  this  question,  it  allowed  you  to  drill  down.

If  I  chose,  "I  want  to  describe  a  group  or  groups,"  and  then  the  next  question  I  answered,  "I  want  to  explore  relationships  between  two  variables  and  my  data  is  continuous,"  then  it  gave  a  recommendation.  A  statistical  technique  that  might  make  sense  is  scatter  plots.  You  can  find  this  in  the  Graph  Builder  or  in  Fit  Y -by -X.  And  we  provided  a  link  to  some  data  sets  that  were  used  in  STIPS.

Our  original  plan  was  that  we  would  have  this  really  as  part  of  STIPS  to  accompany  STIPS  so  that  people  could  refer  back  to  it  after  the  fact.  But  STIPS  took  several  thousand   man-hours  to  develop  and  time  got  away  from  us.  Fortunately,  Peter  was  on  the  STIPS  development  team  and  he  saw  the  value  of  a  utility  like  this.  I'm  going  to  turn  it  over  to  Pete  and  Pete's  going  to  talk  about  how  this  original  concept,  this  data  analysis  assistant,  ultimately  became  DAD.

Thanks,  Mia.  Let  me  share  my  screen  here.  There  we  go.  The  motivation  from  this  actually  really  came  from  a  couple  of  customers  reaching  out  and  asking  exactly  what  Mia  found  in  that  survey.  When  they  had  new  users  coming  to  them,  they  weren't  quite  sure  where  to  go  into  JMP  to  do  the  analysis  they  were  after,  so  they  didn't  know  what  technique  to  use  when.   Several  of  our  customers  were  communicating  through  their  training  organizations  that,  "Hey,  it'd  be  great  if  there  was  some  way  to  direct  people  to  the  analysis  they  wanted."

I  reached  out  to  Mia,  and  she  had  already  laid  the  groundwork  with  that  data  analysis  assistant  and  developed  all  of  the  tasks  that  most  people  were  needing  to  navigate  to,  and  all  I  did  was  take  that  and  finish  it  off.   Let's  get  in  and  actually  look  at  what  this   Data Analysis Director  looks  like.

When  you  launch  it,  it's  going  to  look  like  this,  and  this  is  just  an  application  that  is  inside  of  JMP,  and  we  have  it  deployed  as  an   add-in.  And  we'll  share  the  link  on  where  you  can  get  that   add-in.  But  you'll  notice  here  that  as  I  pick  a  task  from  this  side,  it  will  give  me  several  different  options  for  goals  for  that  specified  task.  And  then  when  I  pick  a  goal,  it  will  let  me  know  if  there's  different  types  of  data  that  might  have  that  same  goal.   Once  I  do  that,  then  all  of  these  buttons  down  here  become  active  and  I  can  do  different  things.

So  to  give  you  an  idea  here,  let's  say  I  wanted  to  compare  groups.  I  have  two  or  more  independent  populations,  and  then  there's  only  one  type  of  data  that  I'm  looking  for.  If  I  then  launch  an  example,  you'll  see  JMP  will  automatically  launch  this  sample  data  set  and  run  that  example.  T his  is  a  great  start  and  this  is  where  we  started  with  JMP  16  was  the  ability  to  do  that.  We  can  also  take  you  right  to  the  help  menu  for  that  specific  test,  the  launch  analysis,  which  will  allow  you  to  just  bring  up  that  analysis,  and  then  also  a  demo  video.

This  demo  video  just  links  to  our  learning  library,  which  is  this  great  resource  that  is  basically  answering  a  question  of  how  do  I  do  X  task  in  JMP?   In  this  case,  the   Data Analysis Director  just  allowed  me  to  figure  out  that  what  I  wanted  to  do  was  a  two -sample  T -test, and  here's  a  quick  2- 5  minute  video  on  how  to  do  that.

The  new  thing  with  JMP  17  that  we  added  was  this  workflow.  This  is  really  nice  for  people  who  maybe  don't  have  a  ton  of  statistical  background  and  maybe  don't  know  what  they're  looking  for  inside  a  JMP.  When  I  open  the  workflow...  This  is  a  new  feature  in 17.  So  if  you're  operating  in  JMP  16  or  older,  you  won't  have  workflows.  But  with  JMP  17,  this  is  a  nice  new  feature.

When  I  hit  play,  what  JMP  does  is  it  opens  that  data  set,  just  like  the  example  I  had  launched  before,  but  now  it  has  some  extra  capability  in  there.   It's  highlighting  some  of  the  reports   where  I  should  look.  It's  telling  me  about  that  report.  It's  also  stepping  through  and  telling  me  what  each  one  of  these  reports  means.  Then  at  the  end,  I've  done  that.  That's  great.  You  could  probably  get  there  with  scripting  as  well  to  be  able  to  recreate  this,  but  workflow  makes  this  a  lot  easier.  And  then  it  also  allows  for  a  generalizable  aspect  to  this.

This  is  key,  especially  with  this   Data Analysis Director.  We  encourage  folks  to  go  ahead  download  this   add-in,  but  you  can  make  it  your  own.  And  how  you  might  make  it  your  own  is  by  taking  a  look  at  the  things  that  come  with  it.

First  off,  with  workflows,  if  I  do  not  prompt  JMP  to  open  a  data  set,  so  I'm  going  to  just  remove  this  data  set,  and  I  hit  play...   I  forgot  to  close  that  behind  the  scenes.  Excuse  me  one  second.  I f  this  data  set  isn't  open  and  I  am  looking  for  a  specific  analysis,  so  here  I'll  just  open  a  different  data  set.  If  I  hit  play  here,  JMP  is  going  to  tell  me,  "Hey,  I  don't  have  that  data  set  you  are  looking  for,  but  unlike  a  script,  I'm  not  going  to  crash.  I'm  just  going  to  go  ahead  and  prompt  you  to  pick  a  data  set."

I'll  hit  okay,  and  then  it  says,  "Hey,  pick  a  continuous  variable  in  that  data  set."   Again,  unlike  a  script,  if  it  doesn't  find  that  column  that  you're  prompting  it  to  find,  it  just  won't  run.  For  this  workflow,  it's  saying,  "Oh,  okay,  pick  a  continuous  Y.  All right, now  pick  a  column  to  replace  gender."  And  now  it's  running  through  that  same  analysis,  it's  giving  me  that  same  report.  T his  makes  this  very  generalizable. T hat's  the  nice  thing  here  with  that  workflow.

If  you  want  to  make  this  your  own,  with  the   add-in,  you  get  this  nice  easy  table  that  has  is  all  of  the  scripts  behind  the  scenes  that  you  can  edit.  You  can  use  your  own  sample  data  set  that  is  maybe  more  relevant  to  your  company.  You  can  use  different  workflows.  We  have  our  demo  videos,  but  maybe  you  have  demo  videos  that  you'd  like  to  use  instead.  This  is  very  easy  to  tweak.  This  will  be  installed  right  with  the   add-in.   Without  having  to  go  in  and  script  things,  the  add -in  is  just  looking  for  a  certain  row  in  this  data  set,  so  very  easy  to  change  that.

One  thing  you  might  be  asking,  and  maybe  you've  heard  of  this,  is  with  JMP  17,  we  also  got  a  new  feature  called   Search JMP.  You  might  be  asking,  "Well,  when  would  I  use  DAD  instead  of   Search JMP?  What  is  the  difference?"

We  did  a  nice  job  here  of  laying  out  the  main  differences.  Search JMP  is  built  right  into  JMP,  and  I'll  show  you  what  this  looks  like  here  in  a  minute,  whereas  the   Data Analysis Director  or  DAD  is  installed  as  an  add-in,  so  you  won't  have  Dad  by  default,  you'll  have  to  go  and  install  it.

And  the   Data Analysis Director  is  really  directed  for  new  users,  maybe  people  who  aren't  as  familiar  with  JMP  or  aren't  as  familiar  with  statistics  in  general,  where   Search JMP  can  be  used  by  anybody.  You  just  need  to  know  what  you're  looking  for.  So  maybe  if  you  don't  know  the  technique,  the   Data Analysis Director  is  a  better  place  to  go.  But  if  you  happen  to  know  the  name  of  the  analysis  you  want  to  do,   Search JMP  is  an  easier  way  to  find  that.  You  also  get  those  example  videos,  example  methods,  and  those  workflows  inside  of  JMP.

For   Search JMP,  this  is  not  example -based.  This  will  launch  the  analysis  for  you,  but  it  will  not  walk  you  through  an  example.  It  is  also  more  comprehensive,  the   Search JMP.   Data Analysis Director,  we  picked  some  of  the  things  JMP  can  do  and  highlighted  that.   Search JMP  will  look  through  everything  inside  of  JMP,  including  the  help,  the  sample  data,  the  scripting  index,  all  of  that.

If  I  am  inside  of  JMP  here,  any  window  open  under  Help,  it's  the  second  thing  on  the  Help  menu,  and  it's   Search JMP.   For  folks  who  haven't  seen  this  before,  if  I  start  typing  in  something  like   T-test,   Search JMP  will  automatically  open  this  up,  and  I  can  go  to  Topic  Help,  I  can  go  to  Go,  I  can  launch  this.   You  can  see  it's  a  lot  like  that  launch  analysis  inside  of  the   Data Analysis Director.  Again,  the  difference  is  I  just  need  to  know  the  name  of  the  technique  I'm  looking  for.   That's  the  difference  between  these  two  tools  and  when  I  might  use  DAD  versus   Search JMP.

To  summarize  what  we've  talked  about  here,  really,  the  whole  point  and  motivation  of  the   Data Analysis Director  is  to  help  new  users  determine  which  tool  to  use  when.   This  all  dates  back  to  that  survey  Mia  was  using  to  figure  out  what  people  need  the  most  help  with,  and  that  was  a  surprise  result  of  that  survey  that  came  out  of  the  S TIPS  development.

And  then  we  want  to  help  new  users  navigate  JMP,  so  get  over  that  initial  hurdle  of  coming  from  either  a  different  statistical  tool  or  just  not  being  as  familiar  with  statistics.  And  really,  I  think  Mia  put  this  great  when  she  said  we  really  want  to  just  help  democratize  statistics,  help  scientists  and  engineers  who  maybe  haven't  taken  many  stats  classes  be  able  to  find  what  analysis  they  need  more  easily.  And  we  do  this  with  examples,  applications  of  different  methods.

And  like  I  showed,  you  can  customize  DAD  to  make  it  your  own.  So  put  in  your  own  examples.  If  there's  something  very  relevant  to  you  and  your  company,  put  it  in  there.  You  can  tweak  the  workflows,  you  can  adjust  the  examples,  the  example  data  sets,  all  of  that's  really  straightforward.

And  when  we  compare  that  to   Search JMP,   Search JMP  is  a  great  tool  to  find  what  you're  looking  for  when  you  know  the  name  of  the  test  you're  looking  for.

We  will  post  this  in  the  JMP  user  community.  This  is  a  free   add-in.  Here's  the  link  to  that   add-in.   You  can  also  just  search   Data Analysis Director  JMP  in  Google,  and  it'll  be  your  top  result.  A lso  for  anyone  who  hasn't  taken  STIPS,  we  strongly  encourage  you  to  do  it.  It's  a  free  online  course,  really  gets  to  the  core  of  how  to  use  statistics  in  general,  not  just  in  JMP.  It  will  walk  through  the  examples  in  JMP,  but  it's  a  great  course  for  folks  who  are  familiar  with  JMP  or  not.

A  couple  of  people  we'd  like  to  thank.  Julian  Parris  helped  a  lot  on  the  front  end  with  this.  And  then  Don  McCormack  was   really  instrumental  in  us  finishing  off  the   add-in.  He  developed  a  lot  of  that  application  and  interface  you  see  there.  We  also  had  many  other  people  who  have  tested  and  provided  feedback.  And  of  course,  Evan  for  the  lead  developer  of  Search JMP,  and  he's  right  here  at  the  conference.  So  if  you  have  questions,  please  stop  by  the  developer  booth  and  talk  to  him.

Thank  you  for  your  time.  Hopefully,  you  found  this  useful  and  you  will  go  and  check  out  our   Data Analysis Director  inside  the  community  and  provide  any  feedback  for  any  future  development  we  might  want  to  do  on  this.  Thank  you.  And  Mia,  any  last  thoughts?

No.  Great  job.  Thank  you.

Thanks.

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