MATLAB: Help with Linear Regression

linear regression

I'm trying to conduct a simple linear regression fitting using fitlm, but the results that is provided when I plot the curve with the original data and the linear equation line found through fitlm is really off. I'm just using the first 20 data points from the list
    mdl = fitlm(time(1:20),price(1:20))
  mdl = 
Linear regression model:
    y ~ 1 + x1
Estimated Coefficients:
                    Estimate       SE        tStat      pValue  
                   __________    _______    _______    _________
      (Intercept)    2.4736e+05      42743     5.7871    1.748e-05
      x1                -5.7654    0.99663    -5.7849    1.756e-05
Number of observations: 20, Error degrees of freedom: 18
Root Mean Squared Error: 0.0178
R-squared: 0.65,  Adjusted R-Squared 0.631
F-statistic vs. constant model: 33.5, p-value = 1.76e-05
Then I prepped for plot using.
   x=time(1:20)
   y1=2.4736e+05+(x*-5.7654)
   plot(time(1:20),price(1:20),x,y1)
I would get this plot attached. I've also attached the data. Please help with a better fit or explanation as to why it is so far off. I'm not sure what I'm doing incorrectly.

Best Answer

This works:
d = load('liu James Linear .mat');
Price = d.Price;
time = d.time;
mdl = fitlm(time, Price, 'linear')
ypred = predict(mdl, [min(time) max(time)]');
figure(1)
plot(time, Price, '+')
hold on
plot([min(time) max(time)]', ypred, '-r')
hold off
grid
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