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5k&1aS14ɽ$hd=ITIIi$ǐ&1詊Lj=$kidIKboAbSXe#mӽ?${u2Cz;yhwBo^k hOS2_\.㤜H&qb]ID0#Mr Ч9So"dO:G2_+@JƦ> *R>*h%]߮kԶh'BB4C9 Ƕؑ&Ҏ:I;EC4*vdݱؑrɊL,wS3=7qQ瓱\MG8M{L;tDtD"G#pŀOE|tNO%nfл*e/ H-?5Z:!󢖟[-JhC|ԟ`0A/j՚flS Ͽz7[-fDݬwTaMӒ%{<[_Yfj/VUZթnY)S \K, t[If[[njyuW3O` 7'靈NVٜm]#|&sخf)G$4u Yݴߚ toVRr E=t  *?9yw{d9K'qI=g;%_#8/kIp@Nprtvxz'p''( ))P**.++D,,--f.$/|/0011\22:33P4455r607788x9l:z:v??&@TBVBXBZB\B^B`BbBdBfBhBjBlBnBpBrBtBvBxBzB|B~BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBCCCCC C CCCCCCCCCC C"C$C&C(C*C,C.C0C2C4C6C8C:CC@CBCDCFCHCJCLCNCPCRCTCVCXCZC\C^C`CbCdCfChCjClCnCpCrCtCvCxCzC|C~CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCY'{E6CDBC66-A2F8-4E25-AD82-6304F0511141} Continue; Gh> 'h5 RR   ;intialize a list we will use later565 &*Hd ]y  y  y  yyyyyyyyyy#yF F E #y  %y ףp= ? ףp= ?      $ *0 4  : F ) L###  X (djt A z#6##   @2 Y #N##   XJ q #f##   pb  #~##   "z,  2###  > JPZ  `###  l x~  ###     ###     ###      ###  $ 0 6  :FL  P#&##  \ 4 bnt  "    #C##   ]          ? "   (4:  >  D#u##  P  JV \   bnt   z      %               ".  4@  q!]y!&&&&&&;re-intialize the list to clear old data5656;a list called 'dist' gets populated with all the responses.;so if you said 50 black men are extremely likeable,;then there will be 50 tens in the list.;do this for all 11 categories.*  0 + . 2  1 3   !y!& 0 - .- **  0 + . 2  1 3   !y!& 1 - .- **  0 + . 2  1 3   !y!& 2 - .- ** 0 + . 2  1 3  !y!& 3 - .- ** 0 + . 2  1 3  !y!& 4 - .- ** 0 + . 2  1 3  !y!& 5 - .- ** 0 + . 2  1 3  !y!& 6 - .- ** 0 + . 2  1 3  !y!& 7 - .- ** 0 + . 2  1 3  !y!& 8 - .- ** 0 + . 2  1 3  !y!& 9 - .- ** 0 + . 2  1 3  !y!& 10 - .- *;how many are in the list, should be 100 if they are following directions!y!;add together all the values in the 'dist' list, I could have used the sum function, but I didn't.. 2 1 3  56- .;divide by the number of datapoints to get the mean;find the deviation from the mean for each datapoint, square it, then add it to a running total. 2 1 3  56  - .;variance equals the sum of squares divided by the number of datapoints;the standard deviation equals the square root of the variance!#y!;this is the code to crank-out the numbers that we will use to draw the normal curve;I only have 11 intervals worth of data, but that isn't enough for a nice distribution;I found that 80 was the minimun # of intervals for it to look smooth;So I interpolate values between the intervals, that is why 'j' is divided by 8 for 'temp';hence we have a 80 values in 'NormalDist' list,;if you want to know what each step below means, google the phrase 'normal distribution' and check out the formulas;I just broke down that formula into manageable parts1. 2 0 3 80 8  2 F % 1!#y!2E     !%y! & 5 *  .97 +  .97 56 174 1- .; Return%%0 0  0 %%/ /  / 5 %* b yy    My  My  {   & , 2 8 > D J P V \   b    h#3##   Wnt  z      /b !y!& !y!123&153&225;running total of how many you are up to.    ;draw evenly spaced tick-marks on the graph 75627511. 2 0 3 11 !My!2&275 &400&275 &403 !My!2&275 &225&275 &222- .i%%5    %% %% %% %% 33$y !y!%% %%    %%    %%    %% %% %% %% %% %% %% %% hK1 Yh5 g77( d y !y! 5 ii8. . Zy< !Zy!1& 278& 399& 316& .  5  l . ףp= ? %y     &,  399. 1.74 !%y! &0 Yh5 g77( Y y !y! 5 ii8. . ZyBg !Zy!1& 322& 399& 359& . 5  l . ףp= ? %y     &,  399. 1.74 !%y! &0 Yh5 g77( Y y !y! 5 ii8. . Zym !Zy!1& 365& 399& 403& . 5  l . ףp= ? %y     &,  399. 1.74 !%y! &0 Yh5 g77( Y y !y! 5 ii8. . Zy !Zy!1& 409& 399& 447& . 5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y y !y! 5 ii8. . Zy !Zy!1& 453& 399& 491& . 5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y y !y! 5 ii8. . Zy !Zy!1& 497& 399& 534& . 5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y y !y! 5 ii8. . ZyB !Zy!1& 540& 399& 578& . 5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y "y !y! "5 ii8. . ZyHn !Zy!1& 584& 399& 622& . !5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y %y !y! %5 ii8. . Zyt !Zy!1& 628& 399& 666& . $5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y (y !y! (5 ii8. . Zy !Zy!1& 672& 399& 709& . '5  l. ףp= ?%y     &, 399. 1.74!%y!&0 1h5 g77( Y +y !y! +5 ii8. . Zy !Zy!1& 715& 399& 753& . *5  l. ףp= ?%y     &, 399. 1.74!%y!&05 Py!Py!;EraseAll();Initialize(item0, item1, item2, item3, item4, item5, item6, item7, item8, item9);Initialize(item10)5 y!y!;Initialize(item0, item1, item2, item3, item4, item5, item6, item7, item8, item9);Initialize(item10)77(  d  100  h5 I!yy @yy$ $$$ $$$$Myyy     $###  O =)06  <H  )T`   fr  x|!y!& !y!0&0&0;interval is the number of pixels between [the midpoint of 10 - the midpoint of 0], which is 437, divided by 80 5.4625;draw 80 different lines to approximate the normal curve;this code is set to make a gradient with a fade-in effect;repeat with i:=0 to 7;SyncPoint(0);SyncWait(.05);SetFrame(TRUE, RGB(123-i*15.4,153-i*19,225-i*28.1)); repeat with w:=0 to 79; Line(8-i, 297+(interval*w), 396-NormalDist[w+1], 297+(interval*(w+1)), 396-NormalDist[w+2]); end repeat;end repeat;this is the non-fancy curve!y!& !y!0&0&0. 2 $0 3 79 !My!1& 297 $& 3965$16& 297 $1& 3965$26- .!y!& !y!0&0&015 77( 0 0y !y! 05 OOCy;AppendExtFile(FileLocation^"data.txt", dist)!Cy!5  ;This example was built by Mike Stalkfleet. michael-stalkfleet@uiowa.edu http://mike-stalkfleet.com;It was built as a psychological tool that measures the perceived variability in a group.;It is meant to replace inferior pencil and paper versions of the same tool.;The data of interest was the standard deviation and the mean, all the other stuff I did just for fun.;I have been haunted by the possibility of drawing a normal distribution in authorware for some time, and I finally figured out how to do it.@D@.@o@$@L  %@CC0|@g&@zj4@  @J%@ @ @>6v @)5 @3RVc@gX@!,54@yd[(@3@5L4@zd'@?c4@ C/4@J 5 @4@H $4@G M4@|x :4@ @4@ 4@ ww4@& 4@5 Y 4@7 (_!4@J_d"4@J@)#4@LEQ$4@KV%4@{dn&4@/'@c(4@zdc)4@{dE*4@X+"@J^,w,4@y-4@ .4@ J/4@ o@04@ Q14@ "24@ )34@&p044@&B754@&>64@ D74@wdK+ -:#C:\Documents and Settings\Mike\Desktop\Recent Authorware\"$+ 70#{ +!%% %%    %%    %%    +0do ... while (condition) \"Area calculationsition)%Enction name() { | } Nnam +0do ... while (condition) \"Area calculationsition)%Enction name() { | } Nnam@o@$@L  %@EEr@E&@z4@  @J%@ @ @Vu @g @3RVc@gX@!,(4@yd[(@3@5Lv4@zd'@4@ C/4@J 5 @4@H $4@G M4@|x :4@ @4@ 4@ ww4@& 4@5 Y 4@7 (_!4@J_d"4@J@)#4@LEQ$4@KV%4@{dn&4@/'@:w(4@zdc)4@{dE*4@X+"@J^Ub,4@y-4@ .4@ J/4@ o@04@ Q14@ "24@ )34@&p044@&B754@&>64@ D74@wdK+ -:#C:\Documents and Settings\Mike\Desktop\Recent Authorware\"$+ 70#{ +!%% %%    %%    %%    +0do ... while (condition) \"Area calculationsition)%Enction name() { | } Nnam . 2  1 3  !y!& 8 - .- ** 0 + . 2  1 3  !y!& 9 - .- ** 0 + . 2  1 3  !y!& 10 - .- *;how many are in the list, should be 100 if they are following directions!y!;add together all the values in the 'dist' list, I could have used the sum function, but I didn't.. 2 1 3  56- .;divide by the number of datapoints to get the mean;find the deviation from the mean for each datapoint, square it, then add it to a running total. 2 1 3  56  - .;variance equals the sum of squares divided by the number of datapoints;the standard deviation equals the square root of the variance!#y!1. 2 0 3 80 8  2 F % 1!#y!2E     !%y! & 5 56 226 1- .5  Tt t data.txtlyCy  #!'+!ly!t #data.txt& !Cy! 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(5 ii8. . Zy !Zy!1& 672& 399& 709& . '5  l. ףp= ?%y     &, 399. 1.74!%y!&0 1h5 g77( Y +y !y! +5 ii8. . Zy !Zy!1& 715& 399& 753& . *5  l. ףp= ?%y     &, 399. 1.74!%y!&05 ..y  ]y]y    " ( . 4 : @F JP!y!!]y! &  &  & & & & & & & !]y!5 y!y!;Initialize(item0, item1, item2, item3, item4, item5, item6, item7, item8, item9);Initialize(item10)77(5  d  100  xcfb`d`g`bd`\ `Qx lx]lUϙ]Tk-.FmiKAb "m$fڝٝ:kmZK|0>k "uJ\j1qRQuʳy[*s&4I mMbRu &)OBA|&&YIf0M![e#$a$jȺO!e#٥I0m 4zV} jZ.$#Ƭr$ IkamG4.*<+ i 'Mn$F? 딍d&y8ۅYhaFR$$6jzP1$Ol^I Mbq؋$ 9 $U"95f4?njȐ2 iwig_z*Na _#A8 Jb<^|{%;inEnw"/<! D{9x }ÓW0#d$CX Wz9auKW9߳Uhvw<c#2jUSU9z3r 1>GIFhǬXg*Pu䐪`b0.6vs)G2]]RG֣=:ӑs&M~ΈDVv&qf:}/Mt{yΥLLvخ#LrX'mgzEwS>T& X/. 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"   (4:  >  D#u##  P  JV \   bnt   z      %               ".  4@  q!]y!&&&&&&;re-intialize the list to clear old data5656;a list called 'dist' gets populated with all the responses.;so if you said 50 black men are extremely likeable,;then there will be 50 tens in the list.;do this for all 11 categories.*  0 + . 2  1 3   !y!& 0 - .- **  0 + . 2  1 3   !y!& 1 - .- **  0 + . 2  1 3   !y!& 2 - .- ** 0 + . 2  1 3  !y!& 3 - .- ** 0 + . 2  1 3  !y!& 4 - .- ** 0 + . 2  1 3  !y!& 5 - .- ** 0 + . 2  1 3  !y!& 6 - .- ** 0 + . 2  1 3  !y!& 7 - .- ** 0 + . 2  1 3  !y!& 8 - .- ** 0 + . 2  1 3  !y!& 9 - .- ** 0 + . 2  1 3  !y!& 10 - .- *;how many are in the list, should be 100 if they are following directions!y!;add together all the values in the 'dist' list, I could have used the sum function, but I didn't.. 2 1 3  56- .;divide by the number of datapoints to get the mean;find the deviation from the mean for each datapoint, square it, then add it to a running total. 2 1 3  56  - .;variance equals the sum of squares divided by the number of datapoints;the standard deviation equals the square root of the variance!#y!;this is the code to crank-out the numbers that we will use to draw the normal curve;I only have 11 intervals worth of data, but that isn't enough for a nice distribution;I found that 80 was the minimun # of intervals for it to look smooth;So I interpolate values between the intervals, that is why 'j' is divided by 8 for 'temp';hence we have a 80 values in 'NormalDist' list,;if you want to know what each step below means, google the phrase 'normal distribution' and check out the formulas;I just broke down that formula into manageable parts1. 2 0 3 80 8  2 F % 1!#y!2E     !%y! & 5 *  .97 +  .97 56 174 1- .; Return%%0 0  0 %%/ /  / 5 %* b yy    My  My  {   & , 2 8 > D J P V \   b    h#3##   Wnt  z      /b !y!& !y!123&153&225;running total of how many you are up to.    ;draw evenly spaced tick-marks on the graph 75627511. 2 0 3 11 !My!2&275 &400&275 &403 !My!2&275 &225&275 &222- .i%%5    %% %% %% %% 33$y !y!%% %%    %%    %%    %% %% %% %% %% %% %% %% hK1 Yh5 g77( d y !y! 5 ii8. . Zy< !Zy!1& 278& 399& 316& .  5  l . ףp= ? %y     &,  399. 1.74 !%y! &0 Yh5 g77( Y y !y! 5 ii8. . ZyBg !Zy!1& 322& 399& 359& . 5  l . ףp= ? %y     &,  399. 1.74 !%y! &0 Yh5 g77( Y y !y! 5 ii8. . Zym !Zy!1& 365& 399& 403& . 5  l . ףp= ? %y     &,  399. 1.74 !%y! &0 Yh5 g77( Y y !y! 5 ii8. . Zy !Zy!1& 409& 399& 447& . 5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y y !y! 5 ii8. . Zy !Zy!1& 453& 399& 491& . 5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y y !y! 5 ii8. . Zy !Zy!1& 497& 399& 534& . 5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y y !y! 5 ii8. . ZyB !Zy!1& 540& 399& 578& . 5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y "y !y! "5 ii8. . ZyHn !Zy!1& 584& 399& 622& . !5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y %y !y! %5 ii8. . Zyt !Zy!1& 628& 399& 666& . $5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y (y !y! (5 ii8. . Zy !Zy!1& 672& 399& 709& . '5  l. ףp= ?%y     &, 399. 1.74!%y!&0 1h5 g77( Y +y !y! +5 ii8. . Zy !Zy!1& 715& 399& 753& . *5  l. ףp= ?%y     &, 399. 1.74!%y!&05 Py!Py!;EraseAll();Initialize(item0, item1, item2, item3, item4, item5, item6, item7, item8, item9);Initialize(item10)5 y!y!;Initialize(item0, item1, item2, item3, item4, item5, item6, item7, item8, item9);Initialize(item10)77(  d  100  h5 I!yy @yy$ $$$ $$$$Myyy     $###  O =)06  <H  )T`   fr  x|!y!& !y!0&0&0;interval is the number of pixels between [the midpoint of 10 - the midpoint of 0], which is 437, divided by 80 5.4625;draw 80 different lines to approximate the normal curve;this code is set to make a gradient with a fade-in effect;repeat with i:=0 to 7;SyncPoint(0);SyncWait(.05);SetFrame(TRUE, RGB(123-i*15.4,153-i*19,225-i*28.1)); repeat with w:=0 to 79; Line(8-i, 297+(interval*w), 396-NormalDist[w+1], 297+(interval*(w+1)), 396-NormalDist[w+2]); end repeat;end repeat;this is the non-fancy curve!y!& !y!0&0&0. 2 $0 3 79 !My!1& 297 $& 3965$16& 297 $1& 3965$26- .!y!& !y!0&0&015 77( 0 0y !y! 05 OOCy;AppendExtFile(FileLocation^"data.txt", dist)!Cy!5  ;This example was built by Mike Stalkfleet. michael-stalkfleet@uiowa.edu http://mike-stalkfleet.com;It was built as a psychological tool that measures the perceived variability in a group.;It is meant to replace inferior pencil and paper versions of the same tool.;The data of interest was the standard deviation and the mean, all the other stuff I did just for fun.;I have been haunted by the possibility of drawing a normal distribution in authorware for some time, and I finally figured out how to do it.xc`Atj &vH<ӗBh{nY0 43 Qu8T U$TM\*j T\*M*>M *5& @sA'AWg@ !܃C@CBCDCFCHCJCLCNCPCRCTCVCXCZC\C^C`CbCdCfChCjClCnCpCrCtCvCxCzC|C~CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCY'{E6CDBC66-A2F8-4E25-AD82-6304F0511141} Continue; Gh> 'h5 RR   ;intialize a list we will use later565 &*Hd ]y  y  y  yyyyyyyyyy#yF F E #y  %y ףp= ? ףp= ?      $ *0 4  : F ) L###  X (djt A z#6##   @2 Y #N##   XJ q #f##   pb  #~##   "z,  2###  > JPZ  `###  l x~  ###     ###     ###      ###  $ 0 6  :FL  P#&##  \ 4 bnt  "    #C##   ]          ? "   (4:  >  D#u##  P  JV \   bnt   z      %               ".  4@  q!]y!&&&&&&;re-intialize the list to clear old data5656;a list called 'dist' gets populated with all the responses.;so if you said 50 black men are extremely likeable,;then there will be 50 tens in the list.;do this for all 11 categories.*  0 + . 2  1 3   !y!& 0 - .- **  0 + . 2  1 3   !y!& 1 - .- **  0 + . 2  1 3   !y!& 2 - .- ** 0 + . 2  1 3  !y!& 3 - .- ** 0 + . 2  1 3  !y!& 4 - .- ** 0 + . 2  1 3  !y!& 5 - .- ** 0 + . 2  1 3  !y!& 6 - .- ** 0 + . 2  1 3  !y!& 7 - .- ** 0 + . 2  1 3  !y!& 8 - .- ** 0 + . 2  1 3  !y!& 9 - .- ** 0 + . 2  1 3  !y!& 10 - .- *;how many are in the list, should be 100 if they are following directions!y!;add together all the values in the 'dist' list, I could have used the sum function, but I didn't.. 2 1 3  56- .;divide by the number of datapoints to get the mean;find the deviation from the mean for each datapoint, square it, then add it to a running total. 2 1 3  56  - .;variance equals the sum of squares divided by the number of datapoints;the standard deviation equals the square root of the variance!#y!;this is the code to crank-out the numbers that we will use to draw the normal curve;I only have 11 intervals worth of data, but that isn't enough for a nice distribution;I found that 80 was the minimun # of intervals for it to look smooth;So I interpolate values between the intervals, that is why 'j' is divided by 8 for 'temp';hence we have a 80 values in 'NormalDist' list,;if you want to know what each step below means, google the phrase 'normal distribution' and check out the formulas;I just broke down that formula into manageable parts1. 2 0 3 80 8  2 F % 1!#y!2E     !%y! & 5 *  .97 +  .97 56 174 1- .; Return%%0 0  0 %%/ /  / 5 %* b yy    My  My  {   & , 2 8 > D J P V \   b    h#3##   Wnt  z      /b !y!& !y!123&153&225;running total of how many you are up to.    ;draw evenly spaced tick-marks on the graph 75627511. 2 0 3 11 !My!2&275 &400&275 &403 !My!2&275 &225&275 &222- .i%%5    %% %% %% %% 33$y !y!%% %%    %%    %%    %% %% %% %% %% %% %% %% hK1 Yh5 g77( d y !y! 5 ii8. . Zy< !Zy!1& 278& 399& 316& .  5  l . ףp= ? %y     &,  399. 1.74 !%y! &0 Yh5 g77( Y y !y! 5 ii8. . ZyBg !Zy!1& 322& 399& 359& . 5  l . ףp= ? %y     &,  399. 1.74 !%y! &0 Yh5 g77( Y y !y! 5 ii8. . Zym !Zy!1& 365& 399& 403& . 5  l . ףp= ? %y     &,  399. 1.74 !%y! &0 Yh5 g77( Y y !y! 5 ii8. . Zy !Zy!1& 409& 399& 447& . 5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y y !y! 5 ii8. . Zy !Zy!1& 453& 399& 491& . 5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y y !y! 5 ii8. . Zy !Zy!1& 497& 399& 534& . 5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y y !y! 5 ii8. . ZyB !Zy!1& 540& 399& 578& . 5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y "y !y! "5 ii8. . ZyHn !Zy!1& 584& 399& 622& . !5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y %y !y! %5 ii8. . Zyt !Zy!1& 628& 399& 666& . $5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y (y !y! (5 ii8. . Zy !Zy!1& 672& 399& 709& . '5  l. ףp= ?%y     &, 399. 1.74!%y!&0 1h5 g77( Y +y !y! +5 ii8. . Zy !Zy!1& 715& 399& 753& . *5  l. ףp= ?%y     &, 399. 1.74!%y!&05 Py!Py!;EraseAll();Initialize(item0, item1, item2, item3, item4, item5, item6, item7, item8, item9);Initialize(item10)5 y!y!;Initialize(item0, item1, item2, item3, item4, item5, item6, item7, item8, item9);Initialize(item10)77(  d  100  h5 I!yy @yy$ $$$ $$$$Myyy     $###  O =)06  <H  )T`   fr  x|!y!& !y!0&0&0;interval is the number of pixels between [the midpoint of 10 - the midpoint of 0], which is 437, divided by 80 5.4625;draw 80 different lines to approximate the normal curve;this code is set to make a gradient with a fade-in effect;repeat with i:=0 to 7;SyncPoint(0);SyncWait(.05);SetFrame(TRUE, RGB(123-i*15.4,153-i*19,225-i*28.1)); repeat with w:=0 to 79; Line(8-i, 297+(interval*w), 396-NormalDist[w+1], 297+(interval*(w+1)), 396-NormalDist[w+2]); end repeat;end repeat;this is the non-fancy curve!y!& !y!0&0&0. 2 $0 3 79 !My!1& 297 $& 3965$16& 297 $1& 3965$26- .!y!& !y!0&0&015 77( 0 0y !y! 05 OOCy;AppendExtFile(FileLocation^"data.txt", dist)!Cy!5  ;This example was built by Mike Stalkfleet. michael-stalkfleet@uiowa.edu http://mike-stalkfleet.com;It was built as a psychological tool that measures the perceived variability in a group.;It is meant to replace inferior pencil and paper versions of the same tool.;The data of interest was the standard deviation and the mean, all the other stuff I did just for fun.;I have been haunted by the possibility of drawing a normal distribution in authorware for some time, and I finally figured out how to do it.@D@.@o@$@L  %@CC@g&@zj4@  @J%@ @ @>6v @)5 @3RVc@gX@,,w4@yd[(@3@6L4@zd'@?c4@ C/4@J 5 @4@H $4@G M4@|x :4@ @4@ 4@ ww4@& 4@5 Y 4@7 (_!4@J_d"4@J@)#4@LEQ$4@KV%4@{dn&4@/'@22b(4@zdc)4@{dE*4@X+"@J^6c,4@y-4@ .4@ J/4@ o@04@ Q14@ "24@ )34@&p044@&B754@&>64@ D74@wdK+ -:#C:\Documents and Settings\Mike\Desktop\Recent Authorware\"$+ 70#{ +!%% %%    %%    %%    +0do ... while (condition) \"Area calculationsition)%Enction name() { | } NnamF F E #y  %y ףp= ? ףp= ?      $ *0 4  : F ) L###  X (djt A z#6##   @2 Y #N##   XJ q #f##   pb  #~##   "z,  2###  > JPZ  `###  l x~  ###     ###     ###      ###  $ 0 6  :FL  P#&##  \ 4 bnt  "    #C##   ]          ? "   (4:  >  D#u##  P  JV \   bnt   z      %               ".  4@  q!]y!&&&&&&;re-intialize the list to clear old data5656;a list called 'dist' gets populated with all the responses.;so if you said 50 black men are extremely likeable,;then there will be 50 tens in the list.;do this for all 11 categories.*  0 + . 2  1 3   !y!& 0 - .- **  0 + . 2  1 3   !y!& 1 - .- **  0 + . 2  1 3   !y!& 2 - .- ** 0 + . 2  1 3  !y!& 3 - .- ** 0 + . 2  1 3  !y!& 4 - .- ** 0 + . 2  1 3  !y!& 5 - .- ** 0 + . 2  1 3  !y!& 6 - .- ** 0 + . 2  1 3  !y!& 7 - .- ** 0 + . 2  1 3  !y!& 8 - .- ** 0 + . 2  1 3  !y!& 9 - .- ** 0 + . 2  1 3  !y!& 10 - .- *;how many are in the list, should be 100 if they are following directions!y!;add together all the values in the 'dist' list, I could have used the sum function, but I didn't.. 2 1 3  56- .;divide by the number of datapoints to get the mean;find the deviation from the mean for each datapoint, square it, then add it to a running total. 2 1 3  56  - .;variance equals the sum of squares divided by the number of datapoints;the standard deviation equals the square root of the variance!#y!;this is the code to crank-out the numbers that we will use to draw the normal curve;I only have 11 intervals worth of data, but that isn't enough for a nice distribution;I found that 80 was the minimun # of intervals for it to look smooth;So I interpolate values between the intervals, that is why 'j' is divided by 8 for 'temp';hence we have a 80 values in 'NormalDist' list,;if you want to know what each step below means, google the phrase 'normal distribution' and check out the formulas;I just broke down that formula into manageable parts1. 2 0 3 80 8  2 F % 1!#y!2E     !%y! & 5 *  .97 +  .97 56 174 1- .;5 oo Ht t data.txtly  #!'!ly!t #data.txt&  Return%%0 0  0 %%/ /  / 5 %* b yy    My  My  {   & , 2 8 > D J P V \   b    h#3##   Wnt  z      /b !y!& !y!123&153&225;running total of how many you are up to.    ;draw evenly spaced tick-marks on the graph 75627511. 2 0 3 11 !My!2&275 &400&275 &403 !My!2&275 &225&275 &222- .i%%5    %% %% %% %% 33$y !y!%% %%    %%    %%    %% %% %% %% %% %% %% %% hK1 Yh5 g77( d y !y! 5 ii8. . Zy< !Zy!1& 278& 399& 316& .  5  l . ףp= ? %y     &,  399. 1.74 !%y! &0 Yh5 g77( Y y !y! 5 ii8. . ZyBg !Zy!1& 322& 399& 359& . 5  l . ףp= ? %y     &,  399. 1.74 !%y! &0 Yh5 g77( Y y !y! 5 ii8. . Zym !Zy!1& 365& 399& 403& . 5  l . ףp= ? %y     &,  399. 1.74 !%y! &0 Yh5 g77( Y y !y! 5 ii8. . Zy !Zy!1& 409& 399& 447& . 5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y y !y! 5 ii8. . Zy !Zy!1& 453& 399& 491& . 5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y y !y! 5 ii8. . Zy !Zy!1& 497& 399& 534& . 5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y y !y! 5 ii8. . ZyB !Zy!1& 540& 399& 578& . 5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y "y !y! "5 ii8. . ZyHn !Zy!1& 584& 399& 622& . !5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y %y !y! %5 ii8. . Zyt !Zy!1& 628& 399& 666& . $5  l. ףp= ?%y     &, 399. 1.74!%y!&0 Yh5 g77( Y (y !y! (5 ii8. . Zy !Zy!1& 672& 399& 709& . '5  l. ףp= ?%y     &, 399. 1.74!%y!&0 1h5 g77( Y +y !y! +5 ii8. . Zy !Zy!1& 715& 399& 753& . *5  l. ףp= ?%y     &, 399. 1.74!%y!&05 Py!Py!;EraseAll();Initialize(item0, item1, item2, item3, item4, item5, item6, item7, item8, item9);Initialize(item10)5 y!y!;Initialize(item0, item1, item2, item3, item4, item5, item6, item7, item8, item9);Initialize(item10)77(  d  100  h5 I1hyy @y?y.@<@yy$ $$$ $$$$Myyy    ###   `"&.{28  @  FL  TX \#9##  O ^b )nt  z  )     5!y!& !y!0&0&0;interval is the number of pixels between [the midpoint of 10 - the midpoint of 0], which is 437, divided by 80 5.4625;draw 80 different lines to approximate the normal curve;this code is set to make a gradient with a fade-in effect. 2 0 3 7!y!0!y!.05!y!& !y!12315.4&15319&22528.1 . 2 $0 3 79 !My!8& 297 $& 3965$16& 297 $1& 3965$26 - .- .;this is the non-fancy curve;SetFrame(TRUE, RGB(150,150,150));repeat with w:=0 to 79; Line(2, 297+(interval*w), 396-NormalDist[w+1], 297+(interval*(w+1)), 396-NormalDist[w+2]);end repeat!y!& !y!0&0&015 77( 0 0y !y! 05  Tt t data.txtlyCy  #!'+!ly!t #data.txt& !Cy!5  ;This example was built by Mike Stalkfleet michael-stalkfleet@uiowa.edu;It was built as a psychological tool that measures the perceived variability in a group.;The data of interest was the standard deviation and the mean, all the other stuff I did just for fun.;I have been haunted by the possibility of drawing a normal distribution in authorware for some time, and I finally figured out how to do it. 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