Apologies ahead of time, this question is more stats related and less SAS. I have a data set with 700 gpas (and a few other factors but they're not relevant to my question) I want to produce a 98% confidence interval for the GPA, which I think I did successfully here:   libname soapy '\\Client\D$\SAS\Data'; data FINAL; infile '\\Client\D$\SAS\Data\finaldata.txt'; input ID GPA HSRANK ACT YEAR; run; proc means data= FINAL n mean stderr alpha=0.02 median p50 clm maxdec=2; var GPA; run; Giving the C.I. [2.92 and 3.03]. OK sounds good. Then I am testing that the average GPA is greater than 3.03, which well, based on my interval from the printout seems unlikely.   proc univariate data=FINAL alpha=0.02 cibasic mu0=3.03; var GPA; run; Since this is a test for Mu>0.03, I should subtract the p-value given in the printout by 1 and use that as the p-value right? p-value= 1-0.0278= 0.9722. which would cause me to reject the null hypothesis and conclude the mean is greater than 3.03, which conflicts with the CI above. Am I misinterpreting this or doing something wrong? Thanks (DATA attached) ... View more

Hello! I have a data set that looks like this:   ID H1 H2 H3 H4 H5 H6 H7 H8 H9 01 10 10 10 10 10 10 10 10 10 02 10 8 5 10 10 0 9 10 3 03 9 10 8 10 9 10 10 10 6 04 7 10 7 8 10 0 10 0 10 05 5 10 6 10 4 10 10 9 10   I need to drop the lowest 2 homework scores and create a variable for the overall homework score for a student. So say for student ID 04, the two zero grades would be dropped and a percentage for homework would be (7+10+7+8+10+10+10)/70 = 88.6 % (homework scores are out of 10.   Ive tried commands like this in the data step:   oops1= min(of Q1--Q9); if H1=min(of Q1--Q9) then drop H1; But I'm not sure where to go from here. Based on my research I think I might need to build an array? Hopefully not cause I have very little experience with that. Any advice would be greatly appreciated!       ... View more

Hello! I have a data set that I need separated into 10 observations. The data has 3 lines for each observation. part of my assignment is to separate observations by the section which is column 5 on the first line. The second two lines are HW and quiz scores. I would like to have SAS read everything as one big table, because from there I am fairly comfortable dividing the data up after that. Ive tried many things, but this is the closest Ive got:   data hw7; input coursename $1-4 section 5 ID 6-7 Name $9-16 #5 a 1-3 b 4-6 c 7-9 d 10-12 e 13-15 f #6 16-18 g 1-3 h 4-6 i 7-9 j 10-12 k 13-15 l 16-18; *input coursename $1-4 section 5@; datalines; M100101 Armann 10 10 10 10 8 9 13 15 10 M100102 Ellery 8 10 7 6 10 1 7 12 15 M100103 Anna 7 5 10 4 10 10 12 9 11 M100104 Tomo 9 8 10 5 10 5 10 14 12 M100301 Glenn 9 6 11 13 2 4 6 5 9 10 10 M100302 Duc 14 12 10 12 9 10 10 8 10 10 10 M100303 Woo 14 15 12 9 8 7 9 10 5 9 10 M100304 Olson 10 10 12 11 5 10 7 9 8 10 10 M100305 Ma 12 15 14 10 10 10 10 10 9 10 9 M100306 Garcia 14 13 15 11 9 10 8 10 10 6 10 ; run; proc print; title 'SAD FACE :('; run; At least SAS knows I have 10 observations now, but I would like sas to print line 2 as a, b, c, d, e, f and line 3 as g, h, i, j , k, l on one observation line in the final output. Please help! ... View more

Hello! I have three data sets. I would like to produce a table showing total sales by gender. I was able to get the correct results, but I'm concerned that If I had a larger data set, I can't use if statements. Here's my data so far:   data EMPLOY; length ID $ 2.; input ID Gender $ DOB MMDDYY10.; datalines; 01 F 10/21/46 02 F 09/02/44 03 M 04/23/55 04 F 11/11/38 ; run; proc sort data=EMPLOY; by ID; run; proc print data=EMPLOY; format DOB MMDDYY10.; run; data PARTS; input partno price; datalines; 123 15 234 25 327 20 355 28 789 55 ; proc print data=PARTS; run; data SALES; length ID $ 2.; input ID TRANS part_no Quantity; datalines; 03 1 234 5 03 1 123 9 03 2 237 4 01 1 355 5 01 1 234 3 01 1 123 9 01 2 355 5 02 1 237 11 ; run; proc sort data=SALES; by ID; run; proc print data=SALES; run; data partssales; merge SALES PARTS; if part_no=123 then price=15; if part_no=234 then price=25; if part_no=237 then price=20; if part_no=355 then price=28; if part_no=789 then price=55; total=Price*Quantity; drop partno; run; /**************************************************/ proc sort data=partssales; by TRANS; run; proc print data=partssales; sum total; by TRANS; run; proc print data=partssales; sum total; by ID; run; /**************************************************/ proc sort data=partssales; by ID; run; data alldata; set partssales; if ID=01 then gender='F'; if ID=02 then gender='F'; if ID=03 then gender='M'; if ID=04 then gender='F'; run; proc sort data=alldata; by gender; run; proc print data=alldata; sum total; by gender; run; Once again, my goal is to reach the same results, without the use of "if then" statements because if this was a larger data set, it would not be practical. Thanks in advance for any advice! ... View more