Let\({Y_2}\)be the time after one student to complete the examination.
Therefore,
\({Y_2}\) has the exponential distribution with parameter \(4\beta \)
Since, the mean of the distribution is 80.
\(\begin{array}{c}4\beta = 4 \times \frac{1}{{80}}\\ = \frac{4}{{80}}\\ = \frac{1}{{20}}\end{array}\)
Therefore,
Probability that at least one other student will complete the examination before 10 a.m. is\({\rm P}\left( {{Y_2} < 35} \right)\)
Since,
\({\rm P}\left( {x < X} \right) = 1 - F\left( x \right)\)
Therefore,
\(\begin{aligned}{}{\rm P}\left( {{Y_2} < 35} \right) &= 1 - {{\mathop{\rm e}\nolimits} ^{\left( { - 35 \times \frac{1}{{20}}} \right)}}\\ &= 1 - {{\mathop{\rm e}\nolimits} ^{\left( { - \frac{7}{4}} \right)}}\end{aligned}\)
\({\rm P}\left( {{Y_2} < 35} \right) = 0.8262\)
Hence, Probability that at least one other student will complete the examination before 10 a.m. is 0.8262.