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error bars when presenting data as (% of control)

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#1 yobou

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Posted 26 February 2013 - 10:52 PM

Dear All
when presenting data as (% of control) how can we add error bars in this case? I mean the error bars would represent what? If I make the error bars represent standard deviation, they are not visible on the chart because its value is small compared to the scale used. So what should be done in these cases?
thanks

Edited by yobou, 26 February 2013 - 10:53 PM.

#2 pcrman

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Posted 26 February 2013 - 10:57 PM

Error bars represent deviation (SD or SEM), but cannot represent % of control. Can you give some example data?

#3 yobou

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Posted 26 February 2013 - 11:25 PM

I want to send you an excel file. could you give your email

#4 pcrman

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Posted 26 February 2013 - 11:42 PM

you can PM me as attachment. thanks.

#5 yobou

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Posted 26 February 2013 - 11:51 PM

plz check ur PM

#6 doxorubicin

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Posted 27 February 2013 - 03:21 AM

The easy way:
When you convert to "% of control", you multiply all values by: 100/[control value]. Just multiply all of your standard errors by this same exact value. It's just changing the scale of your graph, like changing from inches to cms.

#7 hobglobin

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Posted 27 February 2013 - 09:01 AM

The easy way:
When you convert to "% of control", you multiply all values by: 100/[control value]. Just multiply all of your standard errors by this same exact value. It's just changing the scale of your graph, like changing from inches to cms.

but this won't solve the problem what the error bars finally show...

One must presume that long and short arguments contribute to the same end. - Epicurus
...except casandra's that did belong to the funniest, most interesting and imaginative (or over-imaginative?) ones, I suppose.

#8 pcrman

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Posted 27 February 2013 - 10:03 AM

From the data yobou passed me I know he(she) has done one experiment which includes a control, other 3 treatments with 3 repeats in each treatment. In this case, he can do a plot of the actual measurement with error bars. But if he wants to plot as value relative to control, he needs to repeat his experiment at least another time, so that he can SD for the %of control values.