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new Scriptio({script:'c1ta.txt', soundtrack:'c1ta.ogg', width:392,
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script: c1ta.txt
:set title to "What Is (Are) Data?" :set background to black :display "Data" color blue size 32 with center at 0 wipe .7 direction iris Statistics is the science of data. ~300 +3.5 :display "42" color white size 12 at {215,118} style bold label "d11" :display "$42,750" at {65,223} label "d12" wipe .7 direction left :display "10159" at {144,174} label "d3" wipe .7 direction right By data, +4.3 :display "31" at {256,156} label "d5" fade .8 :display "$35,643" at {92, 94} label "d6" fade .9 :display "10025" at {166,246} label "d9" wipe .8 direction squeeze we usually mean +5.3 :display "47" at {219,208} label "d17" fade .7 :display "$54,875" at {315,177} label "d18" wipe .7 direction squeeze :display "10101" at {356,124} label "d15" wipe .6 direction iris numerical information. ~900 +8.6 :display "Alan Ott" color white at {247,254} label "d1" grow .7 :display "10/13/92" at {296,223} label "d2" wipe .7 direction right Tags, +9.4 :display "M" at {24,246} label "d4" fade .5 :display "Jennifer Jones" color white at {39,199} label "d7" wipe .6 direction iris :display " 4/16/86" at {110,155} label "d8" fade .8 such as peoples' names, +11.4 :display "F" at {9,146} label "d10" wipe .6 direction squeeze :display "Brian Long" at {292, 96} label "d13" grow .6 :display " 6/2/80" at {134,126} label "d14" wipe .7 direction up :display "M" at {298,136} label "d16" fade .4 are also important information.<br/> But unorganized information such as we see here cannot be used as data. ~300 +21.2 :recolor "d3" to violet A number like 10159 may count something, or it may be an identification number. +28.7 :recolor "d3" to white Either way, it might be data, but if we do not know, we cannot use it as data. ~200 To be used as data, information must be -display "Name Date ID Gender Age Salary" at {45, 65} size 14 color gray +37.8 :display "Name" at {35, 65} size 14 color yellow wipe .2 direction right label "heads1" +38.0 :display "Date" by {48,0} wipe .2 direction right label "heads2" +38.2 :display "ID" by {30,0} wipe .2 direction right label "heads3" +38.4 :display "Gender" by {15,0} wipe .2 direction right label "heads4" +38.6 :display "Age" by {3,0} wipe .2 direction right label "heads5" +38.8 :display "Salary" by {9,0} wipe .2 direction right label "heads6" :group {"heads1","heads2","heads3","heads4","heads5","heads6"} as "heads" recorded systematically, +39.6 :display "Employees of DataCo" with center at 40 size 16 grow .7 -:display "Employees of DataCo" with center at 40 style bold grow .7 :line at {47, 59} to {354, 59} wipe .7 direction iris and must have a context.<br/> +42.4 :display "" style plain ~300 +42.8 :slide "d1" to "heads1" by {-10,20} duration .7 :slide "d7" to "d1" by {0,15} duration .7 :slide "d13" to "d7" by {0,15} duration .7 :slide "d12" by {30,35} duration .6 :slide "d6" by {-15,40} duration .6 Data values may be as simple as the names of individuals, +46.8 :slide "d2" to "heads2" by {-8,20} duration .5 :slide "d8" to "d2" by {0,15} duration .5 :slide "d14" to "d8" by {0,15} duration .5 or dates of an event, such as when a person was hired. +51.4 :slide "d6" to "heads6" by {4,20} duration .7 :slide "d12" to "d6" by {0,15} duration .7 :slide "d18" to "d12" by {0,15} duration .7 Many data values are numbers +53.5 :slide "d5" to "heads5" by {8,20} duration .6 :slide "d11" to "d5" by {0,15} duration .6 :slide "d17" to "d11" by {0,15} duration .6 that record a measurement or amount. +56.7 :slide "d4" to "heads4" by {18,20} duration .7 :slide "d10" to "d4" by {0,15} duration .7 :slide "d16" to "d10" by {0,15} duration .7 Others record a category +58.3 :slide "d3" to "heads3" by {-4,20} duration .6 :slide "d9" to "d3" by {0,15} duration .6 :slide "d15" to "d9" by {0,15} duration .6 or tag.<br/> ~750 +60.6 :display "Data Table" with center at 175 color blue size 20 A data table, such as we see here, +63.3 :recolor "heads" to green records the same information, +65.4 :recolor "heads" to yellow about each +66.1 :recolor {"d1", "d2", "d3", "d4", "d5", "d6"} to green member of +66.8 :recolor {"d1", "d2", "d3", "d4", "d5", "d6"} to white :recolor {"d7", "d8", "d9", "d10", "d11", "d12"} to green a group of +67.4 :recolor {"d7", "d8", "d9", "d10", "d11", "d12"} to white :recolor {"d13", "d14", "d15", "d16", "d17", "d18"} to green individuals, in a structured +69.6 :recolor {"d13", "d14", "d15", "d16", "d17", "d18"} to white layout. ~300 Information about the +72.7 :recolor "heads4" to green same characteristic +73 :recolor "d4" to green of each individual +73.8 :recolor "d10" to green is gathered +74.2 :recolor "d16" to green together +75 :arrow at "d4" by {-6,-4} size {0,60} width 3 wipe .7 direction down label "varAr" into a variable.<br/> +75.1 :display "variable" under "varAr" by {-20,-4} label "var" In a data table such as the arrangement shown here, each variable is in a column. +84.6 :recolor {"d4", "d10", "d16"} to white :recolor "heads4" to yellow :clear {"varAr", "var"} Each row of a data table +86.4 :recolor {"d7", "d8", "d9", "d10", "d11", "d12"} to green holds information for a single +88.1 -:arrow at {42,112} to {360,112} width 2 wipe .8 direction right label "casAr" :arrow under "d7" by {2,1} size {335,0} width 2 wipe .8 direction right label "casAr" individual or case. +90.3 -:display "case" at {368,105} size 14 label "Case" :display "case" after "casAr" by {-4,4} size 14 label "case" In any data table, you should be able to identify the +93.1 :clear {"casAr", "case"} :recolor {"d7", "d8", "d9", "d10", "d11", "d12"} to white variables and cases. +94.7, clear :clear :display "Summary" at 10 with center style underline size 18 color green fade .5 +95 :display "Data are systematically recorded information with<br/> a context." with bullet at {20,48} size 14 fade .5 label "b1" +95.3 :display "Variables hold the same information about many<br/> individuals." with bullet under "b1" by {0,10} fade .5 label "b2" +95.6 :display "Cases hold all the information for a single individual." with bullet under "b2" by {0,10} fade .5 label "b3" ~100 -{"d1","d2","d3","d4","d5","d6","d7","d8","d9","d10","d11","d12"} -Name, hire date, employee ID, gender, age, salary -Jennifer Jones 4/16/86 10025 F 31 35600 -Alan Ott 10/13/92 10159 M 42 42750 -Brian Long 6/2/80 10101 M 47 54875 -Stan Liu 12/10/91 10023 M 28 32760 -Corina Hayes 3/3/93 10096 F 24 28576 -Celia Morales 5/25/89 10134 F 33 37654 -Edward Moss 5/11/81 10067 M 40 40326 -Peggy Ordway 11/3/86 10164 F 38 45243