title: Fitting a multiple linear regression in R
body: <p>So I have data like this -</p>
  
  <pre><code>##      V2   V3     V4   V5   V6   V7    V8
  ## 2  27.0 41.3 2948.0 26.2 51.7 42.7  89.8
  ## 3  22.9 66.7 4644.0  3.0 45.7 41.8 121.3
  ## 4  26.3 58.1 3665.0  3.0 50.8 38.5 115.2
  ## 5  29.1 39.9 2878.0 18.3 51.5 38.8 100.3
  ## 6  28.1 62.6 4493.0  7.0 50.8 39.7 123.0
  ## 7  26.2 63.9 3855.0  3.0 50.7 31.1 124.8
  </code></pre>
  
  <p>I want to do a multiple linear regression - </p>
  
  <pre><code>model1 = lm(cigarette.data$V8 ~ cigarette.data$V2 + cigarette.data$V3 + cigarette.data$V4 + cigarette.data$V5 + cigarette.data$V6 + cigarette.data$V7, data = cigarette.data)
  </code></pre>
  
  <p>But this gives me -</p>
  
  <pre><code>    ## 
  ## Call:
  ## lm(formula = cigarette.data$V8 ~ cigarette.data$V2 + cigarette.data$V3 + 
  ##     cigarette.data$V4 + cigarette.data$V5 + cigarette.data$V6 + 
  ##     cigarette.data$V7, data = cigarette.data)
  ## 
  ## Residuals:
  ## ALL 51 residuals are 0: no residual degrees of freedom!
  ## 
  ## Coefficients: (186 not defined because of singularities)
  ##                         Estimate Std. Error t value Pr(&gt;|t|)
  ## (Intercept)                   19         NA      NA       NA
  ## cigarette.data$V223.1         20         NA      NA       NA
  ## cigarette.data$V223.9         23         NA      NA       NA
  ## cigarette.data$V224.8        -16         NA      NA       NA
  ## cigarette.data$V225.0         21         NA      NA       NA
  ## cigarette.data$V225.1         25         NA      NA       NA
  ## cigarette.data$V225.9         -9         NA      NA       NA
  ## cigarette.data$V226.2          8         NA      NA       NA
  </code></pre>
  
  <p>Which seems wrong. What's going on? </p>