title: how can i draw a gaussian curve on datas which obey gaussian distribution by R language?
body: <p>I have some datas which looks like obeying gausssian distribution. So i use</p>
  
  <p><code>my.glm&lt;- glm(b1~a1,family=Gaussian)</code> </p>
  
  <p>and then use command </p>
  
  <p><code>summary(my.glm)</code>.</p>
  
  <p>The results are:</p>
  
  <pre class="lang-none prettyprint-override"><code>Call:
  glm(formula = b1 ~ a1, family = gaussian)
  
  Deviance Residuals: 
        Min         1Q     Median         3Q        Max  
  -0.067556  -0.029598   0.002121   0.030980   0.044499  
  
  Coefficients:
               Estimate Std. Error t value Pr(&gt;|t|)    
  (Intercept)  0.433697   0.018629   23.28 1.36e-12 ***
  a1          -0.027146   0.001927  -14.09 1.16e-09 ***
  ---
  Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 
  
  (Dispersion parameter for gaussian family taken to be 0.001262014)
  
  Null deviance: 0.268224  on 15  degrees of freedom
  Residual deviance: 0.017668  on 14  degrees of freedom
  AIC: -57.531
  
  Number of Fisher Scoring iterations: 2
  </code></pre>
  
  <p>I think they fit well. But how can i draw a gaussian curve on these datas?</p>