## Cumulative frequency in Maple?...

Hello I have this assignment. I will translate it (because it is not english)

This is the assignment: [IMG]http://i68.tinypic.com/2cgoby9.jpg[/IMG]

(if u cant click on the above link, then u can see it here http://tinypic.com/view.php?pic=2cgoby9&s=9)

So it says:

-------

In an examination of young pigs' birth weight 853 newborn pigs were weighted. The weighting is shown in the table down below.

[0,5-0,7] [0,7-0,9] [0,9-1,1] [1,1-1,3] [1,3-1,5] [1,5-1,7] [1,7-1,9] [1,9-2,1] [2,1-2,3] -> WEIGHT in kg

[26]            [43]       [102]       [145]        [171]      [196]     [119]       [42]          [9]      --> number of pigs

Draw a cumulative frequency curve of the weighting and determine the kvartils.

SO I usually do this in Maple, but this time I did a matrix but nothing happened.. I dont know how I should draw this curve? Help please.

[IMG]http://i68.tinypic.com/2cgoby9.jpg[/IMG]

## Weight a serie of values by another serie ...

Hi everyone! I need to weight a serie of values which x1 range go from 280 to 4000 by the factors provided by another serie of values, which x2 values go from 206.6 to 12400. In the graphs, the red curve is a listplot of the serie which y1 values I want to weight by the y2 values of the listplot of the serie in black. I want the resulting serie in the x1 range, but with the y3 values equal to y2*y1. How can I do that since the series have different intervals?

Serie in red=S and serie in black=t

S:=

...[417., .96392], [418., .92392], [419., .96354], [420., .88467], [421., 1.0067], [422., .99499], [423., .96531], [424., .96182], [425., .99312], [426., .96667], [427., .9355], [428., .94625], [429., .87766], [430., .70134], [431., .63779], [432., 1.0628], [433., .9905], [434., .91653], [435., 1.007], [436., 1.1061], [437., 1.1306], [438., .99368], [439., .95753], [440., 1.0993], [441., 1.0859], [442., 1.164], [443., 1.1823], [444., 1.1537], [445., 1.1992], [446., 1.0766], [447., 1.2257], [448., 1.2422], [449., 1.2409], [450., 1.2881], [451., 1.3376], [452., 1.2822], [453., 1.1854], [454., 1.273], [455., 1.2655], [456., 1.3088], [457., 1.3213], [458., 1.2946], [459., 1.2859], [460., 1.2791], [461., 1.3255], [462., 1.3392], [463., 1.3452], [464., 1.3055], [465., 1.2905], [466., 1.319], [467., 1.2616], [468., 1.3178], [469., 1.3247], [470., 1.2749], [471., 1.2975], [472., 1.3661], [473., 1.3144], [474., 1.3304], [475., 1.3755], [476., 1.3299], [477., 1.3392], [478., 1.3839], [479., 1.3586], [480., 1.3825], [481., 1.3836], [482., 1.3899], [483., 1.3742], [484., 1.3492], [485., 1.3457], [486., 1.0918], [487., 1.2235], [488., 1.3252], [489., 1.2492], [490., 1.3968], [491., 1.3435], [492., 1.2818], [493., 1.3719], [494., 1.3402], [495., 1.4238], [496., 1.3548], [497., 1.3788], [498., 1.3421], [499., 1.3429], [500., 1.3391], [501., 1.299], [502., 1.2991], [503., 1.3597], [504., 1.2682], [505., 1.3598], [506., 1.4153], [507., 1.3548], [508., 1.321], [509., 1.385], [510., 1.3497], [511., 1.3753], [512., 1.4125], [513., 1.3277], [514., 1.3003], [515., 1.3385], [516., 1.3514], [517., 1.1017], [518., 1.2605], [519., 1.2222], [520., 1.3349], [521., 1.3452], [522., 1.376], [523., 1.2976], [524., 1.3962], [525., 1.3859], [526., 1.3479], [527., 1.1795], [528., 1.3508], [529., 1.4142], [530., 1.3598], [531., 1.4348], [532., 1.4094], [533., 1.259], [534., 1.3491], [535., 1.3701], [536., 1.4292], [537., 1.3229], [538., 1.3896], [539., 1.3558], [540., 1.3096], [541., 1.2595], [542., 1.3714], [543., 1.3493], [544., 1.3971], [545., 1.3657], [546., 1.3536], [547., 1.3717], [548., 1.3331], [549., 1.3752], [550., 1.3648], [551., 1.3639], [552., 1.3923], [553., 1.3533], [554., 1.3802], [555., 1.3883], [556., 1.3651], [557., 1.3321], [558., 1.3613], [559., 1.2885], [560., 1.3118], [561., 1.3885], [562., 1.3225], [563., 1.3731], [564., 1.3466], [565., 1.3555], [566., 1.2823], [567., 1.3673], [568., 1.3554], [569., 1.3228], [570., 1.324], [571., 1.281], [572., 1.3534], [573., 1.3595], [574., 1.3527], [575., 1.3225], [576., 1.3118]...

t:=

[[206.6000, 0.9110470095e-3], [210.1000, 0.8504840202e-3], [213.8000, 0.8153191021e-3], [217.5000, 0.7517070516e-3], [221.4000, 0.7035057451e-3], [225.4000, 0.6694785180e-3], [229.6000, 0.6318423899e-3], [233.9000, 0.5994622965e-3], [238.4000, 0.5764355678e-3], [243.1000, 0.5331430203e-3], [248.0000, 0.4950946716e-3], [253.0000, 0.4422658739e-3], [258.3000, 0.4023846661e-3], [263.8000, 0.3732428357e-3], [269.5000, 0.3444825682e-3], [275.5000, 0.3307336604e-3], [281.8000, 0.3570645679e-3], [288.3000, 0.4052774535e-3], [295.2000, 0.4741877081e-3], [302.4000, 0.5345931300e-3], [310.0000, 0.6002211844e-3], [317.9000, 0.7217256785e-3], [326.3000, 0.9176207886e-3], [335.1000, 0.1271492339e-2], [344.4000, 0.1679935813e-2], [354.2000, 0.1976514731e-2], [364.7000, 0.2169413297e-2], [375.7000, 0.2420056977e-2], [387.5000, 0.2698356864e-2], [399.9000, 0.3092320191e-2], [413.3000, 0.3891714441e-2], [427.5000, 0.4875961623e-2], [442.8000, 0.6098167657e-2], [459.2000, 0.8645631738e-2], [476.9000, 0.1639763449e-1], [495.9000, 0.1611551307e-1], [516.6000, 0.1102654621e-1], [539.1000, 0.5287562153e-2], [563.6000, 0.3253578980e-2], [590.4000, 0.2176718340e-2], [619.9000, 0.1510939515e-2], [652.5000, 0.1117755662e-2], [688.8000, 0.8568924681e-3], [729.3000, 0.6693019750e-3], [774.9000, 0.5484788449e-3], [826.6000, 0.4632457834e-3], [885.6000, 0.3982461677e-3], [953.7000, 0.3505755460e-3], [1033.000, 0.3130972421e-3], [1127.000, 0.2814970511e-3], [1240.000, 0.2609345123e-3], [1305.000, 0.2500612658e-3], [1378.000, 0.2397447628e-3], [1459.000, 0.2312899569e-3], [1550.000, 0.2268792462e-3], [1653.000, 0.2197119097e-3], [1771.000, 0.2106962051e-3], [1907.000, 0.2046935228e-3], [2066.000, 0.2003490235e-3], [2254.000, 0.1974613611e-3], [2480.000, 0.1948841680e-3], [2755.000, 0.1957355188e-3], [3100.000, 0.1937027704e-3], [3542.000, 0.1867538618e-3], [4133.000, 0.1849393481e-3], [4959.000, 0.1835339010e-3], [6199.000, 0.1838769393e-3], [8266.000, 0.1869179329e-3], [12400.00, 0.1990760933e-3]]

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