Based on past experience, a bank believes that 12% of the people who receive loans will not make payments on time. The bank has recently approved 100 loans. Answer the following questions. a) What are the mean and standard deviation of the proportion of clients in this group who may not make timely payments? HP = 0.12 SD p) = 0.032 (Round to three decimal places as needed.) b) What assumptions underlie your model? Are the conditions met? A. With reasonable assumptions about the sample, all the conditions are met. O B. The randomization and success/failure conditions are not met. O C. The success/failure condition is not met. O D. The 10% and success/failure conditions are not met. O E. The randomization condition is not met. O F. The 10% condition is not met. O G. The randomization and 10% conditions are not met. O H. Without unreasonable assumptions, none of the conditions are met. c) What is the probability that over 13% of these clients will not make timely payments? P(p>0.13) = (Round to three decimal places as needed.) Enter your answer in the answer box and then click Check Answer. Clear All All parts showing 31566 MAY 10 W 14
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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