Please answer all parts of the question. No need to show work.

Data on the cost (millions of dollars) and the running time (minutes) for films of a particular season are Dependent variable is: Budget($M) summarized in the computer output shown to the right and the plots below. Complete parts a and b. R squared = 25.0% s = 25.33 with 20 - 2 = 18 degrees of freedom Variable Coefficient SE(Coeff) t-ratio P-value Intercept -28.8955 34.53 - 0.84 0.4137 Run Time 0.695379 0.2838 2.45 0.0248 Click the icon to view the plots. . . . . . a) Check the assumptions and conditions for inference. Select all that apply. A. The scatterplot looks straight enough. B. The residual plot and the scatterplot show consistent variability. C. The residuals look random. D. The residuals are nearly normal. E. None of the assumptions and conditions for inference are satisfied. b) Find a 95% confidence interval for the slope and interpret it. I'm % confident that the cost of making longer movies at a rate of between and million dollars per minute. (Round to two decimal places as needed. Use ascending order.)X Plots 120- 80- 80- . 60- Residuals 0- Residuals Budget ($m) 0- . .. .. .... 0+ -80- -80- 60 120 180 20 50 80 -2 0 Run Time (minutes) Predicted Nscore