Here is the solution to Problem #2.14 in Levenspiel.

<< Statistics`LinearRegression`

gasConst = 8.314    ;

Clear[data]

x[1] = 1/((60 - 32)/9*5 + 273);   
y[1] = 
        Log[20/15];   
x[2] = 1/((65 - 32)/9*5 + 273);
y[2] = Log[25/15];
x[3] = 1/((70 - 32)/9*5 + 273);
y[3] = Log[30/15];
x[4] = 1/((75 - 32)/9*5 + 273);
y[4] = Log[35/15];
x[5] = 1/((80 - 32)/9*5 + 273);
y[5] = Log[40/15];
data = Table[{x[i], y[i]}, {i, 1, 5}]

dataPlot = 
        ListPlot[data,  PlotStyle -> PointSize[0.03]];

plot = 
      Regress[data, {1, x}, x, 
        RegressionReport -> {BestFit, 
            RSquared}]
plot = Fit[data, {1, x}, x]
Plot[%, {x, 0.0033, 0.0035}];

Show[%, dataPlot];

Exp[18.920812157918583]   
5368.586070546675*gasConst/
        1000

Note that many kinetic processes in nature obey the Arrhenius rate law (exponential temperature dependence)...