Dun & Bradstreet reports, among other things, information about new business incorporations and number of business failures over several years. Shown here are data on business failures and current liabilities of the failing companies over several years. Use these data and the following model to predict current liabilities of the failing companies by the number of business failures. Discuss the strength of the model. y=b0bx1y=b0b1x Now develop a different regression model by recoding x. Use Tukey's four-quadrant approach as a resource. Compare your models.

Rate of Business Failures (10,000s)	Current Liabilities of Failing Companies ($ millions)
44	1,888
43	4,380
42	4,635
61	6,955
88	15,611
110	16,073
107	29,269
115	36,937
120	44,724
102	34,724
98	39,126
65	44,261

Appendix A Statistical Tables

The regression model is solved for in the computer using the values of x and the values of log y where x is failures and y is liabilities. The resulting regression equation is: *(Round your answer to 4 decimal places.) **(Round your answer to 3 decimal places.) ***(Round your answer to 2 decimal places.) log liabilities = enter an appropriate value rounded to 4 decimal places * + enter an appropriate value rounded to 4 decimal places * failures F = enter an appropriate value rounded to 2 decimal places *** with p = enter an appropriate value rounded to 3 decimal places **, s_e = enter an appropriate value rounded to 4 decimal places *, R² = enter an appropriate value rounded to 3 decimal places **, and adjusted R² = enter an appropriate value rounded to 3 decimal places **. This model has modest predictability.