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I. Ant thropologist Kiara Medina likes to use a linear model that relates femur length to height. The model allows her to determine the height of an individual when only a partial skeleton (including the femur) is found. In this problem use the data on t height for the eight males given in the table to answer the questions. (if needed, round all values to the nearest hundredths) emur length and Femur length (em) Heigh (em) Using DESMOS, create a scatter plot of the data and answer the questions 50.1 48.3 45.2 44.7 44.5 42.7 39.5 38.0 178.5 173.6 164.8 163.7 168.3 165.0 155.4 155.8 1. Find the equation for the line of best fit for the data 2. What is the value of m, and explain what it means to Kiara regarding this data? 3. What is the correlation coefficient, and what type is it? 4. Is the correlation strong? 5. If an anthropologist discovers a femur that is 58.6cm long,how tall would they predict the individual was?
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a) The computation table for the data 50.1 48.3 45.2 44.7 44.5 42.7 39.5 38 173.6 164.8 163.7 168.3 165 155.4 155.8 2510.01 2332.89 2043.04 1998.09 1980.25 1823.29 1560.25 1444 31862.25 30136.96 27159.04 26797.69 28324.89 27225 24149.16 24273.64 8942.85 8384.88 7448.96 7317.39 7489.35 7045.5 6138.3 5920.4 ΣΧ,-353 ΣΊτ 1325. 1 ΣΧ-1569 1.82 ΣΥ-2199286 ΣΧΊτ 58687.63 The following formulae are used to compute and using Least Squares Method (353) (1325.1) 5868763 467760.3 58687.63 58687.63-58470.04 217.5925 SSKY= 217.5925 2x 1569182-(353)2 15691.82-124609 15691.82-15576.13 - 115.695 SSX 115.695

With these values, we compute SSXY SSX 217.5925 115.695 1.880742 1.880742 The formulae for calculating the mean values of the variables X and Y 1325.1 = 165.6375 Y165.6375 353 44.125 X-44.125 With these values, compute 165.6375-(1.880742)44.125 165.6375-82.98776 82.64974 o 82.64974 The equation of the regression line is E. 82 64 974 + 1 880742X

(b) The interpretati on of the slope,m The slope,m The slope of the vari able is interpreted that, for a 1- unit increase in

(d) The interpretati on of correl ati on coefficient/ Yes, the coefficient of correlation is r = 0.96181 indicates about the correlation is very strong positive correlati on between the variables Femur length (X) and Height (Y) There exists a strong positive association between the variables X andY (e) The predicted value of the dependent vari able Height (Y) when the independent variable is X 58.6cm is Y-a+bx Height 82.64974+1.880742 Femur length 82.64974+1.880742X 82.64974 +1.880742 (586) 82.64974+110.2115 192.8612 Therefore, the predicted value of the dependent variable Height (Y). when the independent variable is X- 58.6cm is approximately Height 192.8612m

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