title: How to get probability from GLM output
body: <p>I'm extremely stuck at the moment as I am trying to figure out how to calculate the probability from my <code>glm</code> output in R. I know the data is very insignificant but I would really love to be shown how to get the probability from an output like this. I was thinking of trying <code>inv.logit()</code> but didn't know what variables to put within the brackets.</p>
  
  <p>The data is from occupancy study. I'm assessing the success of a hair trap method versus a camera trap in detecting 3 species (red squirrel, pine marten and invasive grey squirrel). I wanted to see what affected detection (or non detection) of the various species. One hypotheses was the detection of another focal species at the site would affect the detectability of red squirrel. Given that pine marten is a predator of the red squirrel and that the grey squirrel is a competitor, the presence of those two species at a site might affect the detectability of the red squirrel.</p>
  
  <p>Would this show the probability? <code>inv.logit(-1.14 - 0.1322 * nonRS events)</code> </p>
  
  <pre><code> glm(formula = RS_sticky ~ NonRSevents_before1stRS, family = binomial(link = "logit"), data = data)
  Deviance Residuals: 
      Min       1Q   Median       3Q      Max  
  -0.7432  -0.7432  -0.7222  -0.3739   2.0361  
  Coefficients:
                      Estimate Std. Error z value Pr(&gt;|z|)  
  (Intercept)              -1.1455     0.4677  -2.449   0.0143 *
  NonRSevents_before1stRS  -0.1322     0.1658  -0.797   0.4255  
  ---
  Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
     (Dispersion parameter for binomial family taken to be 1)
  Null deviance: 34.575  on 33  degrees of freedom
     Residual deviance: 33.736  on 32  degrees of freedom
    (1 observation deleted due to missingness)
     AIC: 37.736
    Number of Fisher Scoring iterations: 5*
  </code></pre>