Solve problem in steps. You may refer textbook "An Introduction to Statistical Inference and Its Applications with R" by Michael W. Trosset.

(Textbook pdf link : https://bit.ly/2OVKjxa )

(Dataset file link: https://www.filemail.com/d/qczwhptqcafjjqk )

The accompanying data on :3 diesel oil consumption rate measured by the drainweigh method and Y rate measured by the CItrace method, both in g/hr, was read from a graph in the article A New Measurement Method of Diesel Engine Oil Consumption Rate (J. Society Auto Engr., 1985: 2833). Assume that m and Y are related by the following simple linear regression model: K=0+1m+h i=1,...,n, where 61, . . . , eni'irlii'Nm, 0'2) are independent errors. Suppose the following data are collected: mgr-515811121617202228303139 y57101014151325202431283 The dataset is contained in the R list object Final_Q5 in the Final_Q5 .RData le. You may use the command load("Fina1_Q5.RData") to load the dataset inside you R workspace. (a) (1 point) Find the least squares estimates of n and ll. (b) (1 point) Find an unbiased estimator for 02. (c) (1 point) Find 95% condence intervals for 51. (d) (1 point) Test H0 : [31 = 0 against H1 : [31 75 0 at level 0: = 0.05. (e) (1 point) Complete the following ANOVA table for this regression model. Source of variation Degrees of freedom F statistic Regression Residual