Leave all probabilities as percentages, define x on all problems with data. Simple random samples of high interest (8.9%) and low interest (6.3%) mortgages were obtained. For the 40 high interest mortgages, the borrowers had a mean FICO credit score of 594.8 and a standard deviation of 12.2. For the 40 low interest mortgages, borrowers had a mean FICO credit score of 785.2 and a standard deviation of 16.3. Use an alpha level of 0.01, and a two tailed test of hypothesis to test the claim that the mean FICO score borrowers with a high interest mortgage is the same as the mean FICO score of borrowers with the low interest mortgage
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!
Leave all probabilities as percentages, define x on all problems with data.
Simple random samples of high interest (8.9%) and low interest (6.3%) mortgages were obtained. For the 40 high interest mortgages, the borrowers had a
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