Joseph.D.Warner
Dec14-04, 05:35 AM
<jabberwocky><div class="vbmenu_control"><a href="jabberwocky:;" onClick="newWindow=window.open('','usenetCode','toolbar=no, location=no,scrollbars=yes,resizable=yes,status=no ,width=650,height=400'); newWindow.document.write('<HTML><HEAD><TITLE>Usenet ASCII</TITLE></HEAD><BODY topmargin=0 leftmargin=0 BGCOLOR=#F1F1F1><table border=0 width=625><td bgcolor=midnightblue><font color=#F1F1F1>This Usenet message\'s original ASCII form: </font></td></tr><tr><td width=449><br><br><font face=courier><UL><PRE>Strong_Field wrote:\n> "davidmerritt" <davidoff@davidmerritt.co.uk> wrote in message\n> news:davidmerritt.1gysyi@physicsforums.com...\n>\n >\n>>Models created in the physical sciences often have their methodolgy\n>>routed in experimental data, not observed data as in the social\n>>sciences....\n>\n>\n> This is a well established view but I am interested in analysing it\n> further. For instance, in physical sciences a characteristic\n> experimental data is the measurement of an oscillator. Let\'s say we have\n> a vertical pendulum P and we measure its period. We measure the distance\n> from one extreme point A to the other extreme point B. We get a set of\n> numbers, like, x1, x2, x3, and so on. By using these numbers we can\n> model the behavior of the pendulum within the experimental error.\n>\n> In social sciences, let\'s say we measure the density of people entering\n> the Wall Street subway station at 5 PM.\n>\n> We do this, for instance, by counting the number of people whose feet\n> touch the first step of the entrance at exactly 5 PM. We get a series of\n> numbers y1, y2, y3 and so on. Given these numbers I can model the\n> density of people entering subway station within the experimental error\n> as well as the motion of the pendulum.\n>\n> How are these two data set differ?\n\nThey differ because in that the case of pendulum you set up the initial\nconditions and then observe the behaviour. In the case of the people\nentering the subway at 5 PM, you can\'t not control the initial\nconditions. You can only observe. In the former case you can change the\nintitial conditions and make all type of observervations and then\npredictions. You can understand how the observed changes with the\ninitial conditions. But in the later case, initial conditions can change\nwithout you knowing about them. A large office building lost power at 10\nAM and everyone there went home early. So for that day you would observe\nless people at 5 PM. You may call it random, but it isn\'t random as in\nthe former case as there is a real reason for the decrease and could\nhave been predicted if you had more knowledge. But for the case of the\npendulum there isn\'t any knowledge that would take away the randomness\nof the measurement. Only more accurate and precise measurements could do\nthat.\n\n\n>Why one is an experimental data and\n> the other observed data?\n\nSometime these terms are used lossly. But I would define them as:\n\nExperimental data is data collected through observation of an experiment\nwhere I control the conditions of the experiment.\n\nObserved data is data that is collected through observation of some\nevent without control of the event or the conditions affecting the\nevent. In physical science all most all astrophysics data is observed data.\n\n</UL></PRE></font></td></tr></table></BODY><HTML>');"> <IMG SRC=/images/buttons/ip.gif BORDER=0 ALIGN=CENTER ALT="View this Usenet post in original ASCII form"> View this Usenet post in original ASCII form </a></div><P></jabberwocky>Strong_Field wrote:
> "davidmerritt" <davidoff@davidmerritt.co.uk> wrote in message
> news:davidmerritt.1gysyi@physicsforums.com...
>
>
>>Models created in the physical sciences often have their methodolgy
>>routed in experimental data, not observed data as in the social
>>sciences....
>
>
> This is a well established view but I am interested in analysing it
> further. For instance, in physical sciences a characteristic
> experimental data is the measurement of an oscillator. Let's say we have
> a vertical pendulum P and we measure its period. We measure the distance
> from one extreme point A to the other extreme point B. We get a set of
> numbers, like, x1, x2, x3, and so on. By using these numbers we can
> model the behavior of the pendulum within the experimental error.
>
> In social sciences, let's say we measure the density of people entering
> the Wall Street subway station at 5 PM.
>
> We do this, for instance, by counting the number of people whose feet
> touch the first step of the entrance at exactly 5 PM. We get a series of
> numbers y1, y2, y3 and so on. Given these numbers I can model the
> density of people entering subway station within the experimental error
> as well as the motion of the pendulum.
>
> How are these two data set differ?
They differ because in that the case of pendulum you set up the initial
conditions and then observe the behaviour. In the case of the people
entering the subway at 5 PM, you can't not control the initial
conditions. You can only observe. In the former case you can change the
intitial conditions and make all type of observervations and then
predictions. You can understand how the observed changes with the
initial conditions. But in the later case, initial conditions can change
without you knowing about them. A large office building lost power at 10
AM and everyone there went home early. So for that day you would observe
less people at 5 PM. You may call it random, but it isn't random as in
the former case as there is a real reason for the decrease and could
have been predicted if you had more knowledge. But for the case of the
pendulum there isn't any knowledge that would take away the randomness
of the measurement. Only more accurate and precise measurements could do
that.
>Why one is an experimental data and
> the other observed data?
Sometime these terms are used lossly. But I would define them as:
Experimental data is data collected through observation of an experiment
where I control the conditions of the experiment.
Observed data is data that is collected through observation of some
event without control of the event or the conditions affecting the
event. In physical science all most all astrophysics data is observed data.
> "davidmerritt" <davidoff@davidmerritt.co.uk> wrote in message
> news:davidmerritt.1gysyi@physicsforums.com...
>
>
>>Models created in the physical sciences often have their methodolgy
>>routed in experimental data, not observed data as in the social
>>sciences....
>
>
> This is a well established view but I am interested in analysing it
> further. For instance, in physical sciences a characteristic
> experimental data is the measurement of an oscillator. Let's say we have
> a vertical pendulum P and we measure its period. We measure the distance
> from one extreme point A to the other extreme point B. We get a set of
> numbers, like, x1, x2, x3, and so on. By using these numbers we can
> model the behavior of the pendulum within the experimental error.
>
> In social sciences, let's say we measure the density of people entering
> the Wall Street subway station at 5 PM.
>
> We do this, for instance, by counting the number of people whose feet
> touch the first step of the entrance at exactly 5 PM. We get a series of
> numbers y1, y2, y3 and so on. Given these numbers I can model the
> density of people entering subway station within the experimental error
> as well as the motion of the pendulum.
>
> How are these two data set differ?
They differ because in that the case of pendulum you set up the initial
conditions and then observe the behaviour. In the case of the people
entering the subway at 5 PM, you can't not control the initial
conditions. You can only observe. In the former case you can change the
intitial conditions and make all type of observervations and then
predictions. You can understand how the observed changes with the
initial conditions. But in the later case, initial conditions can change
without you knowing about them. A large office building lost power at 10
AM and everyone there went home early. So for that day you would observe
less people at 5 PM. You may call it random, but it isn't random as in
the former case as there is a real reason for the decrease and could
have been predicted if you had more knowledge. But for the case of the
pendulum there isn't any knowledge that would take away the randomness
of the measurement. Only more accurate and precise measurements could do
that.
>Why one is an experimental data and
> the other observed data?
Sometime these terms are used lossly. But I would define them as:
Experimental data is data collected through observation of an experiment
where I control the conditions of the experiment.
Observed data is data that is collected through observation of some
event without control of the event or the conditions affecting the
event. In physical science all most all astrophysics data is observed data.