You are hired by a bank to help determine its lending standards. You decide to start by estimating asimple linear regression model to help predict whether a loan will become past-due (i.e. if any of thepayments are tate).You ask the bank to give you data on the following two random variables:PD is an indicator variable equal to 1 if the loan is past-due, and zero if all payments have been madeon time.credit score is the client's credit score at the time the loan was originated.The table below shows sample descriptive statistics for these variables:VariablePDcredit_scoreSample Mean0.1Sample Standard Deviation0.0855025The sample covariance between PD and credit score is -0.9Use OLS to estimate the following simple linear regression model: PD = Bo + Bicredit_score + uRound your answers to four decimals.What should be the average value of the credit score among the bank's clients if the banks wants tohave a predicted share of past due loans equal to 0.05 (i.e: 5%)? Round your answer to the nearestinteger. You realize that a person's credit score is affected when they default on aloan.If you estimate the following linear regression model insteadcredit_score =Bo + B1 PD+ u, then the value of the coefficientsestimated using OLS would be the same as those you estimated in theprevious question, because both models use the same random variables.O TrueO False

Given, Variable Sample mean Sample Standard deviation PD 0.1 0.08 credit_score 550 25…

You are hired by a bank to help determine its lending standards. You decide to start by estimating a simple linear regression model to help predict whether a loan will become past-due (i.e. if any of the payments are tate). You ask the bank to give you data on the following two random variables: PD is an indicator variable equal to 1 if the loan is past-due, and zero if all payments have been made on time. credit_score is the client's credit score at the time the loan was originated. The table below shows sample descriptive statistics for these variables: Variable PD Sample Mean 0.1 Sample Standard Deviation 0.08 credit_score 550 25

You are hired by a bank to help determine its lending standards. You decide to start by estimating a simple linear regression model to help predict whether a loan will become past-due (i.e. if any of the payments are tate). You ask the bank to give you data on the following two random variables: PD is an indicator variable equal to 1 if the loan is past-due, and zero if all payments have been made on time. credit_score is the client's credit score at the time the loan was originated. The table below shows sample descriptive statistics for these variables: Variable PD Sample Mean 0.1 Sample Standard Deviation 0.08 credit_score 550 25

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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