How can I solve these problems USING R PROGRAM HELP ME PLZ (I NEED R CODE ) Estimating the costs of drilling oil wells is an important consideration for the oil industry DS 12 2 1 contains the total costs and the depths of 16 offshore oil wells located in the Philippines (taken from Identifying the major determinants of exploration drilling costs A first approximation using the Philippine case by Gary S Makasiar, Energy Exploration and Exploitation 1985) (a) Fit a linear regression model with cost as the dependent variable and depth as the explanatory variable (b) What does your model predict as the cost increase for an additional depth of 1000 feet (c) What cost would you predict for an oil well of 10,000 feet depth (d) What is the estimate of the error variance (e) What could you say about the cost of an oil well of depth 20,000 feet (f) Compute the analysis of variance table and calculate the coefficient of determination R2 Check that the F statistic is the square of the t statistic for testing Ho 0 (g) What is the sample correlation coefficient r (h) Show that t r( 2) (1 2) and t 1 s e ( 1) are same DS 12 2 1 'Depth (feet)' 'Cost ($1000)' 5000 2596 800048828125 5200 3328 6000 3181 10009765625 6538 3198 39990234375 7109 4779 89990234375 7556 5905 60009765625 8005 5769 2001953125 8207 8089 5 8210 4813 10009765625 8600 5618 7001953125 9026 7736 9197 6788 2998046875 9926 7840 7998046875 10813 8882 5 13800 10489 5 14311 12506 599609375

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Question: How can I solve these problems USING R PROGRAM? HELP ME PLZ! (I NEED R CODE!) Estimating the costs of drilling oil wells is an

How can I solve these problems USING R PROGRAM? HELP ME PLZ! (I NEED R CODE!)

Estimating the costs of drilling oil wells is an important consideration for the oil industry. DS 12.2.1 contains the total costs and the depths of 16 offshore oil wells located in the Philippines (taken from "Identifying the major determinants of exploration drilling costs: A first approximation using the Philippine case" by Gary S. Makasiar, Energy Exploration and Exploitation. 1985)

(a) Fit a linear regression model with cost as the dependent variable and depth as the explanatory variable.

(b) What does your model predict as the cost increase for an additional depth of 1000 feet?

(d) What is the estimate of the error variance?

(e) What could you say about the cost of an oil well of depth 20,000 feet?

(f) Compute the analysis of variance table and calculate the coefficient of determination R2. Check that the F-statistic is the square of the t-statistic for testing Ho: = 0

(g) What is the sample correlation coefficient r?

(h) Show that t = r( 2)/(1 2) and t = 1/s.e.( 1) are same.

DS 12.2.1

'Depth (feet)' 'Cost ($1000)' 5000 2596.800048828125 5200 3328 6000 3181.10009765625 6538 3198.39990234375 7109 4779.89990234375 7556 5905.60009765625 8005 5769.2001953125 8207 8089.5 8210 4813.10009765625 8600 5618.7001953125 9026 7736 9197 6788.2998046875 9926 7840.7998046875 10813 8882.5 13800 10489.5 14311 12506.599609375

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