SAT scores are normally distributed with μ=500 and σ=100. Let X correspond to a random students SAT score. If P(X> 810) = 0.0001, interpret this as a porportion. A.) Only about 1 out of 1,000 test takers will score below an 810 on the SAT. B.) Only about 1 out of 1,000 test takers will score above an 810 on the SAT. C.) Only about 1 out of 1,000 SAT tests were selected for our sample. D.) If a sample of 1,000 test takers is taken, exactly one is guaranteed to score above an 810 on the SAT.
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!
SAT scores are
A.) Only about 1 out of 1,000 test takers will score below an 810 on the SAT.
B.) Only about 1 out of 1,000 test takers will score above an 810 on the SAT.
C.) Only about 1 out of 1,000 SAT tests were selected for our sample.
D.) If a sample of 1,000 test takers is taken, exactly one is guaranteed to score above an 810 on the SAT.
Trending now
This is a popular solution!
Step by step
Solved in 2 steps
