A marketing professor is conducting research on college student behaviors. She is interested in the proportion of seniors who will graduate debt free. She surveyed n D 590 college seniors. She estimates, with a 95% confidence interval, that between 20% and 27% of college students will graduate debt free. Which of the following is a correct interpretation of her confidence interval? We can be 95% that a future sample will yield a sample proportion between 0.20 and 0.27. If this study were to be repeated with a sample of the same size, there is a 95% probability that the sample proportion would be between O.20 and 0.27. O There is a 95% probability that the proportion of college seniors who will graduate debt free is between 0.20 and 0.27. O We can be 95% confident that the proportion of college seniors in the sample who will graduate debt free is between 0.20 and 0.27. We can be 95% confident that the proportion of college seniors in the population who will graduate debt free is between 0.20 and 0.27.
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!
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