Greetings,
In an effort to compare two sets of N observations (A and B) at a point in time (t). I have computed the following statistics:
mean(A)
std_dev(A)
error_upper(A) = mean(A) + ( 1.96 * ( std_dev(A) / sqrt(N) ) )
error_lower(A) = mean(A) - ( 1.96 * ( std_dev(A) / sqrt(N) ) )
mean(B)
std_dev(B)
error_upper(B) = mean(B) + ( 1.96 * ( std_dev(B) / sqrt(N) ) )
error_lower(B) = mean(B) - ( 1.96 * ( std_dev(B) / sqrt(N) ) )
I wish to plot these results with error bars using gnuplot, which can be acheived if the data has the form:
t Y_val Y_err
My qusetion relates to the correct calculation of the error value (Y_err). To plot the error bars for the first set of observations (A) should I use:
t mean(A) ( error_upper(A) - error_lower(A) )
or, should it be
t mean(A) ( error_upper(A) - error_lower(A) ) / 2
??
The goal is to visually depict a 95% confidence interval.
Any help on this matter would be hugely appreciated.
Many thanks,
dan