S.Djari 2020 MAT 120 PROJECT: American Black Bear (Lecture 4) American Black Bears: The American black bear ( Ursus Americanus) is one of the eight bear species in the world. It is the smallest North...

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S.Djari 2020 MAT 120 PROJECT: American Black Bear (Lecture 4) American Black Bears: The American black bear ( Ursus Americanus) is one of the eight 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 a long-term study of the population in the Great Smoky Mountains National Park. One aspect of the study was to develop a model 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 following data represent the lengths and weight of 12 American black bears. Total Length (cm) Weight (kg) Total Length(cm) Weight (kg) 139.0 110 141.0 95 138.0 60 150.0 85 139.0 90 166.0 155 120.5 60 151.5 140 149.0 85 129.5 105 141.0 100 150.0 110 (a) Which variable is explanatory variable based on the goals of the research? (b) Draw a scatter diagram of the data. (c) Determine the linear correlation coefficient (Pearson’s) between weight and height. (d) Does a linear relation exist between the weight of the bear and its height? (e) Find the least-squares regression line, treating total length as explanatory and weight as the response variable. (f) Suppose a 149.0 cm bear is captured in the field. Use the least-squares regression line to predict the weight of the bear. (g) Interpret the slope and y-intercept if appropriate. Note: 1) This project is simple. Because we are on distance online learning, we will be using EXCEL to obtain scatter plot, least regression line…etc, and perform simple operation to answer questions. Please use full sentences to answer questions. Questions (a), (d), and (g) are comprehensive. Please, refer to the PowerPoint presentation or the text book to answer them. 2) All papers must be typed. Please answer all the questions to get full credits. Cover page is required, titles, label axes, questions numbering. 3) I will have 30 minutes on Saturday 11/14/2020 for extra help. Due Date: The due date for the project is no Later than November 25, 2020. After correcting your paper, I will ask you to make changes if necessary and submit it on eprotfolio for grade improvement. Final submission on eportfolio is due on December 5, 2020. Please do not submit on eportfolio without getting feedback.