Three students were applying to the same graduate school. They came from schools with different grading systems. Table 2.74 Student GPA School Average GPA School Standard Deviation Thuy 2.5 2.9 0.8 Vichet 87 79 10 Kamala 8.3 8.1 0.5
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!
Three students were applying to the same graduate school. They came from schools with different grading systems.
Table 2.74
Student | GPA | School Average GPA | School Standard Deviation |
---|---|---|---|
Thuy | 2.5 | 2.9 | 0.8 |
Vichet | 87 | 79 | 10 |
Kamala | 8.3 | 8.1 | 0.5 |
How many standard deviations is each student away from hiir school average? If the student GPA is higher than his school average, enter this as a positive number. If the student GPA is lower than his school average, enter this as a negative number.
Thuy is standard deviations from Thuy's school average.
Vichet is standard deviations from Vichet's school average.
Kamala is standard deviations from Kamala's school average.
Which student had the best GPA when compared to other students at his school?
Thuy |
||
Vichet |
||
Kamala |
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