Hi there,
this is the code/ data I have. Please note I have already taken the logs so that the data is scaled appropriately.
Log_N = [1.09861228866811,1.09861228866811,1.79175946922806,2.56494935746154,3.61091791264422,4.23410650459726,4.65396035015752];Log_R = [-2.50000000000000,-2,-1.50000000000000,-1,-0.500000000000000,0,0.500000000000000];plot(Log_R,Log_N,'o')hold on title('Correlation Dimension')xlabel('Log R')ylabel('Log Nd')hold on [P, S,] = polyfit(Log_R,Log_N,1); % Evaluate the fitted polynomial p and plot:
f = polyval(P,Log_R);plot(Log_R,Log_N,'o',Log_R,f,'-')legend('data','linear fit')
I have created my line of best fit using polyfit and polyval. All I am wanting to do is fit a straight line to my data and would like to know my gradient of the line/ slope and the associated error.
Any advice would be much appreciated.
I tried using 'fit'
[curve, ~] = fit(Log_R, Log_N,'poly1');
but the errors I got were:
>> correlation_attempt_2Error using fit>iFit (line 127)X must be a matrix with one or two columns.Error in fit (line 108)[fitobj, goodness, output, convmsg] = iFit( xdatain, ydatain, fittypeobj, ...Error in correlation_attempt_2 (line 72)[curve, ~] = fit(Log_R, Log_N,'poly1');
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