In a given university, some scholarships were offered to students. This depends on the GPA the student gets and having his/her application submitted on time. 40.1% of the students applying have the required GPA. Given that the student has the required GPA, 77.56% of the students received a scholarship. And given that the student doesn’t have the required GPA, 6.51% of them received a scholarship. Knowing that a student got a scholarship and have the required GPA, 96.46% of them had applied before the due date. On the other hand, the probability that the student submitted his application on time knowing that he didn’t have the required GPA and he didn’t get a scholarship was 1.79%. Given that the student didn’t get a scholarship and had the required GPA, 2.22% of the applications were submitted on time. Of all applications, 3.4% of the applications were submitted on time, the student didn’t have the required GPA and the student got a scholarship. 1. Construct two tables (having the required GPA and Not having the required GPA) such that combining these two tables make a hypothetical 1000 table for the three events.
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
In a given university, some scholarships were offered to students. This depends on the GPA the
student gets and having his/her application submitted on time.
40.1% of the students applying have the required GPA. Given that the student has the required
GPA, 77.56% of the students received a scholarship. And given that the student doesn’t have
the required GPA, 6.51% of them received a scholarship.
Knowing that a student got a scholarship and have the required GPA, 96.46% of them had
applied before the due date. On the other hand, the probability that the student submitted his
application on time knowing that he didn’t have the required GPA and he didn’t get a
scholarship was 1.79%.
Given that the student didn’t get a scholarship and had the required GPA, 2.22% of the
applications were submitted on time.
Of all applications, 3.4% of the applications were submitted on time, the student didn’t have
the required GPA and the student got a scholarship.
1. Construct two tables (having the required GPA and Not having the required GPA) such that
combining these two tables make a hypothetical 1000 table for the three
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