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sas code代写 assignment IntroSAS

2019-07-28 10:28 星期日 所属: 作业代写 浏览:113

sas code代写 To receive credit for this assignment the following criteria must be met.

You must submit your complete program summary as a pdf in
It must contain the entire code, log, and results
It must not contain any unnecessary output in the

To receive credit for this assignment the following criteria must be met.

  1. You must submit your complete program summary as a pdf in
    1. It must contain the entire code, log, and results
    2. It must not contain any unnecessary output in the
  2. You must submit your complete SAS code as a .SAS
  3. The assignment must be turned in on or before the due
sas code代写
sas code代写

Templates and output data sets for comparison are located at: /courses/df6689e5ba27fe300/IntroSAS/MISC/HW5/

Part I: Modify hwdata.shell to match the other files.

  • This part should contain one DATA
  • Create two numeric variables current and capacity using input() and scan() to pull the information from the amount variable.
  • Remove the variable amount from the output data
  • Name the modified data set‘shell_mod’.

 

Part II: Concatenate hwdata.nat, shell_mod, and hwdata.ogg in that order.

  • This part should contain one DATA
  • Create a new variable prop, which is current /
  • Create a new numeric variable time from the variable pulled using timepart(), apply the timeampm
  • Create a new variable timegrp fromtime:
    • 00:00 up to and including 10:00:Dawn
    • Greater than 10:00 up to and including 15:00:Midday
    • Greater than 15:00 and including 24:00:Evening
  • Only keep location, timegrp, time, and prop in the new data set. Order is not
  • Use data set options to make sure all sets have matching variable

 

Part III: Calculate the average value of prop within location and timegrp

  • This part should contain one procedure step.
  • All output from this procedure to the results tab should be
  • The output set should be named mymeans and contain only the variables location, timegrp, n, average, and stdev. Order is not
  • Use the data set options rename and drop to rename _freq_ to n and drop _type_ from the final

 

Part IV: Merge work.stacked and work.mymeans (in that order) on location and timegrp.

  • This part should contain one DATA step and two procedure
  • The output set should be named‘merged’.

 

 

 


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