The following data show the daily closing prices (in dollars per share) for a stockDate Price ($)Nov .3. 82.79Nov 4. 83.09Nov 7. 83.64Nov 8. 83.23Nov 9. 82.84Nov 10. 83.97Nov 11. 84.64Nov 14. 84.30Nov 15. 85.56Nov 16. 86.63Nov 17. 86.97Nov 18. 87.86Nov 21. 87.38Nov 22. 88.04Nov 23. 88.86Nov 25. 88.70Nov 28. 89.12Nov 29. 89.18Nov 30. 88.94Dec 1. 89.21

the independent variable Period, where Period = 1 corresponds to the data for November 3, Period = 2 corresponds to the data for November 4, Period = 3 corresponds to the data for mber 7, and so on. Develop the estimated regression equation that can be used to predict the closing price (in dollars per share) given the value of Period. Use x for Period. (Round your erical values to two decimal places.) 7.17x + 6.47 X k which variable(s)/term(s) should be in your equation. he 0.05 level of significance, test for any positive autocorrelation in the residuals of the regression model. e the null and alternative hypotheses. H : P = 0 H: p 0 Ha: p = 0 H: P 0 Find the value of the test statistic. (Round your answer to two decimal places.) 0.2882 X What are the critical values? (Round your answers to two decimal places.) d = 168 d = X 9:18 PM