(a) Find the least-squares regression line, treating total length asthe explanatory variable and weight as the response variable.(b) Interpret the slope and y-intercept, if appropriate.(c) Suppose a 149.0-cm bear is captured in the field. Use theleast-squares regression line to predict the weight of the bear.

.3 DATA 20. American Black Bears (Refer to Problem 30, Section 4.1.) The American black bear (Ursus americanus) is one of eight SC bear species in the world. It is the smallest North American bear and the most common bear species on the planet. In 1969, Dr. Michael R. Pelton of the University of Tennessee initiated O a long-term study of the population in Great Smoky Mountains National Park. One aspect of the study was to develop a model ild that could be used to predict a bear's weight (since it is not practical to weigh bears in the field). One variable thought to be related to weight is the length of the bear. The data below represent the lengths of 12 American black bears. Total Length (cm), x Weight (kg), y 139.0 110 138.0 60 139.0 90 120.5 60 149.0 85 141.0 100 ,y, 141.0 95 150.0 85 166.0 155 151.5 140 129.5 105 150.0 an 110 Source: www.fieldtripearth.org