"LINEAR REGRESSION, SLOPE, INTERCEPT, CORRELATION COEFFICIENT. Linear regression, or first-order polynomial regression, is a least-squares process which generates the best estimate of the line: Y = SLOPE * X + INTERCPT for a given number of (X,Y) data pairs. The correlation coefficient R is a statistical estimate of how well the line respresents the data. A 'perfect' fit has R = ±1. The steps used to enter the data and calculate these values are: 1) Type ? then (end esc) 0 (enter) to set everything to 0.0. 2) Type M then x-value (ctrl enter) (enter) y-value (enter) 3) Type M and enter the next value and so on... Note: N is the number of (X,Y) data pairs and (ctrl enter) is used the enter thex-value without performing any calculations. (c) Copyright PCSCC, Inc., 1993 *** Answer(s) to problem *** The values of the variables at entry are set to the final values after the 5 data points are entered. The SLOPE is 0.04678 and INTERCPT is 0.2854. The correlation coeff. R of 0.9809 suggests that the thickness of the gold is well- correlated to the depostion time. Type any key to exit. ||Calculate the slope, intercept and correlation coefficient for a gold deposition process for which the time (min) vs. thickness (mm) data are: (1, .3351), (2, .3837), (3, .4244), (4, .4493) and (5, .5362). Type comma key to see answer. Type (F2) to return to application file."
