I need help with these questions.I did part A with the regressional analysis and got 92.5% for the coefficient determination. Q. 1. Mary is concemed over how she should use credit ratings in making these loans. She hasgathered sample data on credit rating and loan delinquencies which are provided for your use.Loans delinquent beyond 90 days are likely candidates for foreclosure. Mary believes that thebank is willing to accept a minimum credit score that has an expected foreclosure rate of tenpercent.a. What is the relationship between days delinquent and credit scores? Use simple regression.Determine and interpret the coefficient of determination.b. What credit score is expected to yield an average delinquency of 90 days? credit scoresdays del.400914259052070$40885108555565535755655557550640366214365040647296303562437648446204567940682386653668035695257052271215730187201379576074515800

Number of observations n = 30 Let X be the credit score and Y be the days delinquent X Y X2 Y2 XY…

a. What is the relationship between days delinquent and credit scores? Use simple regression. Determine and interpret the coefficient of determination. b. What credit score is expected to yield an average delinquency of 90 days?

a. What is the relationship between days delinquent and credit scores? Use simple regression. Determine and interpret the coefficient of determination. b. What credit score is expected to yield an average delinquency of 90 days?

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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Concept explainers

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.

Question

I need help with these questions.

I did part A with the regressional analysis and got 92.5% for the coefficient determination.

Q. 1. Mary is concemed over how she should use credit ratings in making these loans. She has
gathered sample data on credit rating and loan delinquencies which are provided for your use.
Loans delinquent beyond 90 days are likely candidates for foreclosure. Mary believes that the
bank is willing to accept a minimum credit score that has an expected foreclosure rate of ten
percent.
a. What is the relationship between days delinquent and credit scores? Use simple regression.
Determine and interpret the coefficient of determination.
b. What credit score is expected to yield an average delinquency of 90 days?

credit scores
days del.
400
91
425
90
520
70
$40
88
510
85
555
65
535
75
565
55
575
50
640
36
621
43
650
40
647
29
630
35
624
37
648
44
620
45
679
40
682
38
665
36
680
35
695
25
705
22
712
15
730
18
720
13
795
760
745
15
800

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