Before lending someone money, banks must decide whether they believe the applicant will repay the loan. One strategy used is a point system. Loan officers assess information about the applicant, totaling points they award for the person's income level, credit history, current debt burden, and so on. The higher the point total, the more convinced the bank is that it's safe to make the loan. Any applicant with a lower point total than a certain cutoff score is denied a loan. Think of this decision as a hypothesis test. Since the bank makes its profit from the interest collected on repaid loans, their null hypothesis is that the applicant will repay the loan and therefore should get the money. Only if the person's score falls below the minimum cutoff will the bank reject the null and deny the loan. Complete parts a through c below. ... a) In this context, what is meant by the power of the test? O A. The power is the probability that the bank denies a loan that would have been repaid. O B. The power is the probability that the bank denies a loan that would not have been repaid. O c. The power is the probability that the bank approves a loan that will be repaid. O D. The power is the probability that the bank approves a loan that will not be repaid. b) What could the bank do to increase the power? O A. The bank could hire additional loan officers to assess each applicant's information. O B. The bank could scrap the point system. O cC. The bank could lower the cutoff score. O D. The bank could raise the cutoff score. c) What is the disadvantage of taking the action part b)? O A. A larger number of trustworthy people would be denied credit, and the bank would miss the opportunity to collect interest on those loans. O B. The bank would have to spend more money on the additional loan officers. OC. The bank would have to spend additional time and money developing a new system. O D. A larger number of untrustworthy people would have their loans approved, and the bank would lose money from those unpaid loans.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
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