pipeline                package:alr3                R Documentation

_A_l_a_s_k_a _p_i_p_e_l_i_n_e

_D_e_s_c_r_i_p_t_i_o_n:

     The Alaska pipeline data consists of in-field ultrasonic
     measurements of the depths of defects in the Alaska pipeline. The
     depth of the defects were then re-measured in the laboratory.
     These measurements were performed in six different batches. The
     data were analyzed to calibrate the bias of the field measurements
     relative to the laboratory measurements. In this analysis, the
     field measurement is the response variable and the laboratory
     measurement is the predictor variable.

     These data were originally provided by Harry Berger, who was at
     the time a scientist for the Office of the Director of the
     Institute of Materials Research (now the Materials Science and
     Engineering Laboratory) of NIST. These data were used for a study
     conducted for the Materials Transportation Bureau of the U.S.
     Department of Transportation.

_F_o_r_m_a_t:

     This data frame contains the following columns:

     _F_i_e_l_d Number of defects measured in the field. 

     _L_a_b Number of defects measured in the field. 

     _B_a_t_c_h Batch number 

_S_o_u_r_c_e:

     <URL:
     http://www.itl.nist.gov/div898/handbook/pmd/section6/pmd621.htm>

_R_e_f_e_r_e_n_c_e_s:

     Weisberg, S. (2005). _Applied Linear Regression_, 3rd edition. New
     York: Wiley, Problem 8.3.

_E_x_a_m_p_l_e_s:

     data(pipeline)

