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1.1 root 1: n� �*.KB�& H id n { id nam; sname; sum; n; v; index
2: nam { ,nam
3: sname { ((1YRname),Rnam)Yname
4: sum { +/v{^/sname=(Rsname)Rnam
5: n { 0
6: } (0=sum)/nfind
7: } (1#sum)/mfind
8: n { vI1
9: } (^/((1URname)Ynam)=name[n;])/0
10: L { ' ',' ','full name: ',name[n;]
11: }0
12: nfind: L { 'name not found'
13: } 0
14: mfind: L { 'ambiguous names'
15: sname { v/[1]name
16: } (0=^/^/((Rsname)Rsname[1;])=sname)/dfind
17: L { ' ',(NJ(((1YRsname),1)R index { v/I1YRname)),':',' ',sname
18: getidx: n { 'Enter index of desired name: ' getnum '-'
19: } (0=V/n=index,`1)/error
20: } 0
21: dfind: L { ' ',' ',sname
22: } 0
23: error: L { '*** illegal index, try again ***'
24: } getidx
25: dstat dstat x; z
26: z { stat x
27: ' '
28: ' '
29: 'sample size ';z[1]
30: 'maximum ';z[2]
31: 'minimum ';z[3]
32: 'range ';z[4]
33: 'mean ';z[5]
34: 'variance ';z[6]
35: 'standard deviation ';z[7]
36: 'mean deviation ';z[8]
37: 'median ';z[9]
38: summary summary; i
39: L{' '
40: L{' score summary'
41: L{' '
42: L { ((4+1URname),(`1+1YRlist)R4)fhead list
43: L { name,(5 0 NJ ((1YRname),1)RI1YRname),4 0NJ score
44: L { 3 1 R ' '
45: drop drop ;nam;idx;mask
46: L { 'Enter names (one per line) end with an empty line.'
47: getname: L'{'name: '
48: } (0=Rnam{L')/0
49: idx { id nam
50: } (0=idx)/getname
51: L { ((4 + 1URname),(`1+1YRlist)R4)fhead list
52: L { name[idx;],(5 0NJidx),4 0NJscore[idx;]
53: L'{'ok? (y/n): '
54: }('y'#'L)/nogo
55: mask { (1YRname)R1
56: mask[idx]{0
57: name {mask/[1]name
58: } ((`1YRssn)=0)/nossn
59: ssn { mask/[1]ssn
60: } ssnd
61: nossn: ssn { ((1YRname),0)R''
62: ssnd: } ((`1YRscore)=0)/noscore
63: score { mask/[1]score
64: } done
65: noscore: score { ((1YRname),0)R0
66: done: L{'drop completed'
67: } getname
68: nogo: L { 'nobody dropped'
69: } getname
70: stat z{stat x;r;max;min;mean;var;sd;md;med;mode;v;m;n
71: n{Rx
72: r{(max{x[n])-min{(x{x[|Hx])[1]
73: sd{(var{(+/(|x-nRmean{(+/x)%n)*2)%n-1)*0.5
74: md{(+/|x-nRmean)%n
75: med{0.5X+/x[(Sn%2),1+Dn%2]
76: z{n,max,min,r,mean,var,sd,md,med
77: & statname ` H number maximum minimum range mean variancestd dev mean devmedian newstat statscore { newstat data ;i
78: statscore { (9,1URdata)R0
79: i {1
80: next: statscore[;i]{stat data[;i]
81: } ((1URstatscore) & i{i+1)/next
82: statscore[1;]{+/[1]0#data
83: statsummary statsummary
84: L{' '
85: L{' statistics summary'
86: L{' '
87: L { (11,(`2+1YRlist)R4) fhead 1 0Ulist
88: L { statname,4 0 NJ D newstat score
89: L { 3 1 R ' '
90: newscore newscore ;pos;i;mask;listn;p;tp;it
91: L { 'current types are:'
92: L { type
93: L' { 'type ? '
94: p { type find it { L'
95: }(V/p)/oktype
96: L { 'type not found'
97: }0
98: oktype: tp { p/IRp
99: pos { (tp<scoretype)I1
100: mask { 1,(Rscoretype)R1
101: mask[pos] { 0
102: score { mask\score
103: scoremax { mask\scoremax
104: list { (1,mask)\[1]list
105: scoretype { mask\scoretype
106: scoretype[pos] { tp
107: scoremax[pos] { 'scoremax ? ' getnum '.'
108: listn { 2 0NJ+/,scoretype=scoretype[pos]
109: list[pos+1;] { (1URlist)Yit,listn
110: CJ now input new scores
111: i { 1
112: next: score[i;pos] { (name[i;],': ') getnum '-.'
113: }((1YRname)&i { i+1)/next
114: L { 'new score complete'
115: newname newname; nname; nssn
116: L { 'enter names (one per line) end with an empty line.'
117: getname: L' { 'name: '
118: }(0=Rnname{L')/done
119: name { name addrow nname
120: nssn { ''
121: } (~askedssn)/addssn
122: L' { 'ssn : '
123: nssn { L'
124: addssn: ssn { ssn addrow nssn
125: } getname
126: done: score { ((1YRname),`1YRscore)Yscore
127: L { 'newname complete'
128: analysis analysis; i; mk; n
129: n { 1YRname
130: means{ (n,1+1YRtype)R0
131: i{1
132: next: mk{ scoretype=i
133: }done XI 0=V/,mk
134: means[;i]{ 100X(+/mk/score) % +/mk/scoremax
135: done: }((1YRtype) >= i{ i+1 )/next
136: means[;i]{ (+/(means[;Ii-1]X(n,Rweight)Rweight)) %+/weight
137:
138: histgm title histgm data ; i;h;m50
139: m50 { 51 > S/data
140: data { S data%2-m50
141: h {51R0
142: i{0
143: loop: h[i+1] { +/data =i
144: }loop XI 50 & i {i+1
145: ''
146: ' histogram of ',title
147: ''
148: i { S/h
149: loop2: ' *'[1+ h&i]
150: }loop2 XI 0< i{i-1
151: '|----|----|----|----|----|----|----|----|----|----|'
152: }m50/low
153: '0 10 20 30 40 50 60 70 80 90 100'
154: }0
155: low:'0 5 10 15 20 25 30 35 40 45 50'
156:
157: find p { list find item
158: p { ^/list=(Rlist)R(1URlist)Y item,' '
159:
160: printstat printstat colnam;data
161: }(0=Rdata{ getcol colnam)/0
162: dstat data
163: printstat0 printstat0 colnam;data
164: }(0=Rdata{ getcol colnam)/0
165: data { (0#data)/data
166: dstat data
167: getcol data { getcol colnam;p
168: p { 1U list find colnam
169: }(~V/p)/snf
170: data { ,p/score
171: }0
172: snf:p { tlist find colnam
173: }(~V/p)/nnf
174: data {,p/means
175: }0
176: nnf:'column name ',colnam,' not found'
177: data { 0R0
178:
179: printhist printhist colnam;data
180: }(0=Rdata{ getcol colnam)/0
181: colnam histgm data
182: printhist0 printhist0 colnam;data
183: }(0=Rdata{ getcol colnam)/0
184: data { (0#data)/data
185: colnam histgm data
186: setup setup ;i;tt;nname;wt
187: } askedsetup/exit
188: L{ 'enter the score types (one per line) end with an empty line.'
189: type { 0 0 R' '
190: gettype: L' { 'type: '
191: }next XI 0=Rtt { 'L
192: type { type addrow tt
193: }gettype
194: next: L{ 'enter the weights for each type'
195: list{(1,Rlist)Rlist { (6S3+1URtype)Y'number'
196: i { 1
197: weight { (1YRtype)R0
198: nextweight: weight[i] { (type[i;],' = ') getnum '.'
199: }nextweight XI (1YRtype)&i { i+1
200: name { 0 0 R' '
201: L { 'enter names (one per line) end with an empty line.'
202: getname: L' { 'name: '
203: } next2 XI 0=Rnname { L'
204: name { name addrow nname
205: } getname
206: next2: score { ((1YRname),0)R0
207: scoretype { 0R0
208: scoremax { 0R0
209: ssn { 0 0R0
210: askedssn { 0
211: subs { 0
212: L { 'setup complete'
213: askedsetup { 1
214: } 0
215: exit: L { 'setup previously completed'
216: change change;nam;stype;idx;ip;ic
217: L' { 'Enter the item to be changed: '
218: stype { L',' '
219: ic { list find stype
220: newtype { nwscore
221: }(0#V/ic)/ok
222: newtype { nwname
223: }(^/stype=(Rstype)Y'name ')/ok
224: newtype { nwssn
225: }(^/stype=(Rstype)Y'ssn ')/ok
226: L{'type not found'
227: }0
228: ok:col { `1 + ic I 1
229: L { 'Enter names (one per line) end with an empty line.'
230: getname: L' { 'name: '
231: nam { L'
232: } (0=Rnam)/0
233: idx { id nam
234: }(0=idx)/getname
235: } newtype
236: nwscore: L{name[idx;],' - ',list[1+col;],'old score ',Bscore[idx;col]
237: }(1#R ip{'new score: ' getnum '-.')/nc
238: }(0>ip)/nc
239: score[idx;col]{ip
240: L { 'score change complete'
241: }getname
242: nwname: L' { 'new name: '
243: } (0=Rnam{L')/nc
244: name { name addrow nam
245: name[idx;] { name[1YRname;]
246: name { name[I`1+1YRname;]
247: L { 'name change complete'
248: }getname
249: nwssn: L { name[idx;],' - old ssn = ',ssn[idx;]
250: L' { 'new ssn: '
251: } (0=Rsin{L')/nc
252: ssn[idx;] { 9Y (~sinE' -')/sin
253: L { 'ssn change complete'
254: }getname
255: nc: L{'no change'
256: }getname
257:
258: analstats analstats
259: L {''
260: L {' analysis statistics'
261: L { ''
262: tlist { type,[1](1URtype)Y'total'
263: L{(11,(`1+1YRtlist)R4) fhead tlist
264: L { statname,4 0 NJD newstat means
265: L { 3 1 R ' '
266:
267: analprint analprint; rank ;tlist
268: tlist { type,[1](1URtype)Y'total'
269: rank { |V ,means[;1URmeans]
270: L { ' '
271: L { ' ranking of score totals'
272: L { ' '
273: L { ((3+1URname),(1YRtlist)R5) fhead ((1,1URtlist)R'rank '),[1]tlist
274: L { name[rank;],(4 0NJ(((Rrank),1)RIRrank)),5 1NJmeans[rank;]
275: L { 3 1 R' '
276: anal466 anal466; i; mk; ds; dt; dm; scoret; low
277: CJ assume types hw, test and final
278: means{ ((Rnumber),1+1YRtype)R0
279: scoret { tscore score
280: i{1
281: CJ for each student
282: loop: ds{ scoret[i;]
283: CJ homework
284: mk { scoretype=1
285: dt { mk/ds
286: dm { mk/scoremax
287: CJ drop lowest homework
288: low { (dtID/dt)#IRdt
289: means[i;1]{(+/low/dtXdm)%+/low/dm
290: CJ tests (skip if none)
291: }l1 XI ~V/mk{scoretype=2
292: dt { mk/ds
293: dm { mk/scoremax
294: low { dtID/dt
295: dt[low] { means[i;3] { S/dt[low],(scoretype=3)/ds
296: means[i;2]{(+/dtXdm)%+/dm
297: }loop XI (1YRmeans)&i{i+1
298: l1: means[;4]{ (+/(means[;1 2 3]X((Rnumber),Rweight)Rweight)) %+/weight
299: analprint
300: tscore res { tscore data; i; dt; mn; sd
301: CJ tscore computes the tscores for a vector
302: CJ or matrix <data>.
303: res { (Rdata)R0
304: i{1
305: }loop XI 2=RRdata
306: dt { data
307: }l1
308: loop: dt { data[;i]
309: l1: mn { (+/dt)%Rdt
310: sd { ((+/(dt-mn)*2)%`1+Rdt)*.5
311: dt { 50 + 10 X (dt-mn)%sd
312: }end XI 1=RRdata
313: res[;i]{dt
314: }loop X (1URres)&i{i+1
315: end: res{dt
316: tsummary tsummary
317: L{' '
318: L{' t-score summary'
319: L{' '
320: L { ((4+1URname),(`1+1YRlist)R4)fhead list
321: L { name,(5 0 NJ numc),4 0NJ D tscore score
322:
323: fhead r { f fhead list
324: r{((I+/f)E+\f)\O\ list
325:
326: addrow r { mx addrow row; l
327: CJ add a new row to a matrix
328: l { (Rrow)S1URmx
329: r { (((1YRmx),l)Ymx),[1]lYrow
330: lgrade lgrade
331: CJ compute lettergrade
332: L{'enter cutoff values'
333: L{' a b c d'
334: cut { L
335: letter { ((1YRmeans),1)R'fdcba'[1++/means[;1URmeans]J.>cut]
336: alphabetize alphabetize;cols;order;alphabet
337: CJ alphabetize the name list and reorder the scores
338: alphabet { ' ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz'
339: cols { I 10 D Rname[1;]
340: order { |H +/ (alphabetIname[;cols])X((Rname[;1]),10 D Rname[1;])RO|((Ralphabet)*cols)
341: name { name[order;]
342: score { score[order;]
343: ssn { ssn[order;]
344: askssn askssn ;i;sin
345: } askedssn/enter
346: CJ ask for a ssn for each person in the name list
347: i { 1
348: ssn { ((Rname[;1]),9)R ' '
349: loop: L' { name[i;],': '
350: sin { L', ' '
351: ssn[i;] { 9Y (~ sin E ' -')/sin
352: } ((1YRssn) & i { i+1)/loop
353: L { 'ssn entry complete'
354: askedssn { 1
355: } 0
356: enter: L { 'ssn previously completed.'
357: analgrin analgrin;i;means;mk;ds;dt;dm;low;n;w
358: n { 1YRname
359: w { Rweight
360: scoret { tscore score
361: rank { means { (n,1+1YRtype)R0
362: i { 1
363: } subs/loop2
364: loop1: }enter1 XI ~V/mk{scoretype=i
365: dm { mk/scoremax
366: means[;i] { \O(+/(mk/scoret)X((n,Rdm)Rdm))%+/dm
367: rank[;i] { \O|H|Gmeans[;i]
368: enter1: }loop1 XI (w&i{i+1)
369: rank[;1+w] { \O|H|G(+/means[;1 2 3]X(n,w)Rweight)%+/weight
370: } 0
371: loop2: ds { scoret[i;]
372: mk { scoretype=1
373: dt { mk/ds
374: dm { mk/scoremax
375: low { (dtID/dt)#IRdt
376: means[i;1]{(+/low/dtXdm)%+/low/dm
377: }enter2 XI ~V/mk{scoretype=2
378: dt { mk/ds
379: dm { mk/scoremax
380: low { dtID/dt
381: dt[low] { means[i;3] { S/dt[low],(scoretype=3)/ds
382: means[i;2] { (+/dtXdm)%+/dm
383: }loop2 XI (1YRmeans)&i{i+1
384: enter2: means[;4] { (+/(means[;1 2 3]X(n,w)Rweight)%+/weight
385: rank { |H[1]|G[1]means
386: grin grin;ss;n
387: ss { 'L,' '
388: ss { 9Y(ss#'-')/ss
389: n { (^/ssn=(Rssn)Rss)I1
390: } (n$1YRssn)/ok
391: L { 'invalid student id: ',ss
392: } 0
393: ok: L { (13,(`2+1YRlist)R4) fhead 1 0 U list
394: 'max score', 4 0 NJ scoremax
395: 'raw score', 4 0 NJ score[n;]
396: ' t score', 4 0 NJ scoret[n;]
397: ''
398: } (subs)/enter
399: 'Based on T scores but without using the substitution'
400: ' algorithm (i.e. - no scores have been droped or replaced yet)'
401: enter: 'The total number of students in class is ',(3 0NJ `1URssn),'.'
402: ''
403: ' homework test final total'
404: 'rank ', 8 0NJ rank[n;]
405: & Llx K & 7 7 'type ''describe'' for a description of this workspace' ssnprint ssnprint function ;name
406: name { ssn
407: BJ function
408: & askedsetup & &
409: getnum num { prompt getnum let;str
410: again: L' { prompt
411: str { L'
412: } (1<+/strE'.')/error
413: } (1<+/strE'-')/error
414: }goodnum XI ^/strElet,'0123456789'
415: error: L { '*** illegal number, try again. ***'
416: }again
417: goodnum: num { BJ str
418: } (1#R,num)/error
419: analize analize ;data;mean;didanal;tlist
420: didanal { 0
421: } ((RBN27)>1)/cont1
422: L' { 'do you want names or ssn to be listed? (n/s): '
423: } ('n'=1YL')/cont1
424: ssnprint 'analize'
425: }0
426: cont1: L' { 'do you want a score summary? (y/n): '
427: } ('n'=1YL')/cont2
428: summary
429: cont2: L' { 'do you want raw score statistics? (y/n): '
430: } ('n'=1YL')/cont3
431: statsummary
432: cont3: L' { 'do you want a mean score summary? (y/n): '
433: } ('n'=1YL')/cont7
434: analysis
435: analprint
436: didanal { 1
437: cont7: L' { 'do you want individual score type rankings? (y/n): '
438: } ('n'=1YL')/cont4
439: } (didanal)/analcont2
440: analysis
441: didanal { 1
442: analcont2: rankprint
443: cont4: L' { 'do you want mean score statistics? (y/n): '
444: } ('n'=1YL')/cont5
445: } (didanal)/analcont1
446: analysis
447: didanal { 1
448: analcont1: analstats
449: cont5: L' { 'do you want histogram and statistics for any specific score? (y/n): '
450: } ('n'=1YL')/0
451: L { 'enter score types (one per line) end with an empty line.'
452: cont6: L' { 'type: '
453: tp { L'
454: } (0=Rtp)/0
455: tlist { type,[1](1URtype)Y'total'
456: data { (0#data)/data { getcol tp
457: }(0=Rdata)/cont6
458: tp histgm data
459: L { 3 1 R' '
460: L { (3R' '),'statistics of ',tp
461: dstat data
462: L { 3 1 R' '
463: } cont6
464:
465: rankprint rankprint; av1; tlist
466: tlist { type,[1](1URtype)Y'total'
467: av1 { |H [1]|V [1]means
468: L { ' '
469: L { ' ranking for each score type'
470: L { ' '
471: L { ((3+1URname),(`1+1URav1)R4) fhead tlist
472: L { name,4 0 NJav1
473: L { 3 1 R' '
474: & describe � &syn n new apl score system spring 1982
475:
476: an apl workspace is available which is designed to maintain and perform
477: analysis on a set of class grades. the system is interactive in nature
478: allowing each user to select the set of functions suitable for his or her
479: needs.
480:
481: to obtain a frech copy of this system, type ')load ngradesys' after
482: entering apl.
483:
484:
485: setting up the system:
486: to set the system up for a new class, the function 'setup' is used.
487: 'setup' will respond by asking score types, score weights and student names.
488: names may be added or deleted at any time so an accurate name list is not
489: required to setup the system.
490:
491: the system is now setup. save a copy of this setup workspace by typing
492: ')save xxx'. the workspace will be saved in the file xxx and may be loaded
493: in the future with the load command. it is advisable to keep several backup
494: copies of an active grade workspace.
495:
496:
497: alphabetizing the name list:
498: to enter new scores into the system efficiently it is best to have the
499: names alphabetized both in the system and the stack of new scores. to
500: alphabetize the name list, type 'alphabetize'. this will also reorder the
501: previously entered scores and ssn. this function may be called any time after
502: the system is setup, ussually the function is called just after setup and
503: then each time a list of new names is added to the system.
504:
505:
506: entering the social security numbers (ssn):
507: social security numbers can be entered by typing 'askssn'. the system
508: will then prompt with a name and ask for the corresponding ssn. this
509: sequence will continue until all ssn are entered.
510:
511: entering a new set of grades:
512: to enter a new score, type 'newscore' and you will be promted for the
513: grade type and the maximum possible score. you will then be prompted for a
514: grade for each student.
515:
516:
517: adding and dropping students:
518: to add a list of students, type 'newname'. you will then be prompted
519: for a list of names. enter each on a new line and then terminate the list
520: with a null line. note, any old scores for these new students must be
521: inserted with the 'change' function. (described later)
522:
523: to drop a list of students, type 'drop'. you will then be prompted
524: for a list of names. enter each on a new line and then terminate the list
525: with a null line. for each name entered, the system will display all grades
526: recorded for that student and then request confirmation that you still want
527: to drop the student.
528:
529: changing names, scores, ssn:
530: to change the spelling of a name, change the grade of a student or
531: correct a students ssn, type 'change'. the function will then prompted
532: for the type of change needed. the available types include 'name', 'ssn',
533: or one of the previously entered score types. example, if the score types
534: available are 'hw', 'test', and 'quiz' and you are wanting to change the
535: second homework score, then enter 'hw 2' when prompted. next, the function
536: will prompt for a name, the function verifies the name exists and then
537: prompts for the new data (the name, score or ssn).
538:
539:
540: analizing the scores:
541: to analize the scores, type 'analize'. this function will guide the
542: user through the analysis sequence. just answer 'y' or 'n' for each of
543: the questions asked.
544: the following analysis functions are available:
545: 1) score summary - a list of raw scores for all score types and
546: all students. this is a convienent method of obtaining
547: a hardcopy back up of all scores for the current class.
548: 2) statistics summary - this function computes simple statistics
549: each set of scores and prints out the results.
550: 3) mean score summary - this computes the average percent grade
551: for each grade type for each student and also the total
552: percent grade based on the weights entered for the score
553: types.
554: 4) individual score rankings - this functions lists the students
555: ordered by their rank of the total and their ranking for
556: each score type is also listed.
557: 5) mean score statistics - this function will compute simple
558: statistics on the data generated by the mean score summary
559: (function 3 above).
560: 6) histogram and statistics for any specific score - this will
561: generate simple statistics and a histogram for and
562: individual score or any score type. example: if 'hw' is
563: a score type then 'hw' would generate data for the
564: combined homeworks and 'hw 2' would generate data for
565: just homework #2.
566:
567:
568: ***** notes on using the system
569: 1) at no time should a function be interrupted midway through
570: completion for this may cause inconsistencies in the workspace.
571: 2) the function which looks up names is able to look up a partial
572: name and match it. this implies that any time a name is required
573: to be typed in, only the first few letters which unambiguously
574: identify it are needed. if a partial match is found, then the full
575: name will be displayed so you can verify that the correct name was
576: matched. if you enter an ambiguous set of letters for a match,
577: then the system will display all names which matched correctly.
578: 3) three digit scores and fractional scores upset the printing
579: format of the score summary in analysis. therefore it is best to
580: limit maximum scores to 100.
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