Linear Regression Fit, click "F test" under the Model Fit Measures Overall Model Overall Model Test Test heading Model R R2 F df1 df2 (You should 0.481 0.231 2.41 1 8 0.159 paste TWO tables here. If Model Coefficients - accuracy(%wError) they won't fit in Predictor Estimate SE the document, Intercept 2.016 3.548 0.568 0.585 orderDensity 0.865 0.558 1.552 0.159 you can add them as separate image files when you upload to Blackboard.) Questions 9. Write the linear regression equation based on the output. 10. Use the linear regression equation to predict the percent of orders with errors if the order density is 4. 11. Is the regression equation significant? How do you know? Make sure you say which value you used and where you found it. 12. What is the value of the Pearson correlation coefficient for the relationship between these two variables? 841 wordsQuestions 9. Write the linear regression equation based on the output. 10. Use the linear regression equation to predict the percent of orders with errors if the order density is 4. 11. Is the regression equation significant? How do you know? Make sure you say which value you used and where you found it. 12. What is the value of the Pearson correlation coefficient for the relationship between these two variables? 13. What is the R2 for this regression equation? 14. Regression doesn't always make logical sense. Imagine that no one is ever in the restaurant (order density is 0). What would the equation predict in terms of order accuracy? 15. Explain, in your own words and based on the answer from #14, why you think I asserted that regression doesn't always make logical sense