Logistic regression is linear when the parameter, $\pi$, that controls the behavior of the Bernoulli response is transformed into a log odds:  
$$
\ln\left(\frac{\pi_i}{1-\pi_i}\right) = \beta_0 + \beta_1x_i
$$
Your variable `PASS` is a vector of predicted probabilities.  These can be converted into log odds using the LHS of the equation above.  Once there, these should form a straight line as a function of `RIT`.  Here is some `R` code to do this:  

    oPASS = PASS / (1-PASS)
    loPASS = log(oPASS)

A plot of these values shows that there was some rounding in the predicted probabilities that you were given:  

![enter image description here][1]

You can also see the issue if you look at the `loPASS` variable:  

    > loPASS
     [1]       -Inf       -Inf       -Inf -4.5951199 -4.5951199 -4.5951199
     [7] -3.8918203 -3.1780538 -2.7515353 -2.1972246 -1.7346011 -1.2083112
    [13] -0.7081851 -0.2006707  0.2818512  0.8001193  1.3249254  1.8152900
    [19]  2.3136349  2.7515353  3.1780538  3.8918203  4.5951199  4.5951199
    [25]        Inf        Inf        Inf        Inf        Inf        Inf
    [31]        Inf        Inf        Inf        Inf        Inf        Inf
    [37]        Inf

Thus, we will work with the 7th & 23rd data points to get a reasonably accurate result.  

Once we have these values, we can calculate the slope using [the point-slope formula][2], and the intercept, by algebraically rearranging the equation of the line:  

    b1 = (loPASS[23]-loPASS[7]) / (RIT[23]-RIT[7])
    b0 = loPASS[7] - b1*RIT[7]

That yields the parameter estimates that had been used to generate the predicted probabilities that you were given:  

    > b0
    [1] -19.80483
    > b1
    [1] 0.1060868

For more information about logistic regression, it may help you to read my answer here: [difference-between-logit-and-probit-models](https://stats.stackexchange.com/questions/20523//30909#30909).  


  [1]: https://i.sstatic.net/4j0Nw.png
  [2]: http://www.montereyinstitute.org/courses/Algebra1/COURSE_TEXT_RESOURCE/U04_L1_T4_text_final.html