Define population 1 as mortgages that are refinanced, and define population 2 as mortgages that are not refinanced. Let µ1 equal the mean FICO score of borrowers who refinance their mortgages, and let µ2 equal the mean FICO score of borrowers who don't refinance. Similarly, let o1 and ơ2 equal the standard deviations of borrower FICO scores for populations 1 and 2. Assume that o1 = 45 and o2 = 66. In a study, professor Michael LaCour-Little selected independent random samples of mortgages were refinanced and mortgages that were not refinanced, ang he collected data on borrower in Predicting Mortgağe 'Prěpayments," Journal'of Housing Research, Volume 10, Issue 1.) For the sample drawn from refinanced mortgages, the sample size n, = 124, and the sample mean š1 = 740. For the sample drawn from mortgages that were not refinanced, the sample size n2 = 124, and the sample mean x2 = 720. Histograms of the sample data suggest that the populations are not extremely nonnormal. sample sizes have been reducedpte: The sample means match those from the study, but the The point estimate of µ1 H2 is 20 ▼ In this study, the sampling distribution of š1 82 is approximated by a a mean of 20 normal distribution with and a standard deviation of 7.1735 Use the Distributions tool to help you answer the questions that follow.
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
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