https://www.youtube.com/watch?v=Uua5GnarQIM&list=PLkiselvEzpM4AQEGTWF95pYy3ZqwTXkHc _ [+] What would be the correlation between the annual salaries of males and females at a company if for a certain type of position men always made a) $5,000 more than women? b) 25% more than women? c) 15% less than women?Consider a regression predicting weight (kg) from height (cm) for a sample of adult males. What are the units of the correlation coefficient, the vertical intercept, and the slope? O Correlation: no units, Intercept: no units, Slope: no units O Correlation: kg/cm, Intercept: no units, Slope: no units O Correlation: no units, Intercept: kg, Slope: kg/cm O Correlation: kg/cm, Intercept: kg/cm, Slope: kg/cmExercise 7.15 introduces data on shoulder girth and height of a group of individuals. The mean shoulder girth is 107.66 cm with a standard deviation of 10.14 cm. The mean height is 174.95 cm with a standard deviation of 9.01 cm. The correlation between height and shoulder girth is 0.672. a) Write the equation of the regression line for predicting height. Slope (round 3 decimal places): | Intercept (round to nearest whole number): I b) Interpret the slope and the intercept in this context. 0 When height is 0 cm, the shoulder girth in cm is expected to be 61 O For each additional cm in shoulder girth, the model predicts an additional bl cm in height 0 For each additional cm in height, the model predicts an additional bl cm in shoulder girth 0 When shoulder girth is 0 cm, the ehight in cm is expected to be 61 c) Calculate R2 of the regression line for predicting height from shoulder girth. Round to three decimal places. Interpret R2 in the context of the application. 0 About 100*(R2)% of data in shoulder girth is accounted for by the model, i.e. explained by height 0 About 100*(R2)% of the variability in height is accounted for by the model, i.e. explained by the shoulder girth 0 About 100*(R2)% of the data in height is accounted for by the model, i .e. explained by the shoulder girth 0 About 100*(R2)% of the variability in shoulder girth is accounted for by the model, i.e. explained by the height d) A randomly selected student from your class has a shoulder girth of 102 cm. Predict the height of this student using the model. Round to the nearest whole number. e) The student from part (d) is 168 cm tall. Calculate the residual and round to the nearest whole number. f) A one year old has a shoulder girth of 56 cm. Would it be appropriate to use this linear model to predict the height of this child? O No, this calculation would require interpolation. O No, this calculation would require extrapolation. 0 Yes, this calculation would require extrapolation. 0 Yes, this calculation would require interpolation. The scatterplot shows the relationship between socioeconomic status measured as the percentage of children in a neighborhood receiving reduced-fee lunches at school (lunch) and the percentage of bike riders in the neighborhood wearing helmets (helmet). The average percentage of children receiving reduced-fee lunches is 30.2% with a standard deviation of 25% and the average percentage of bike riders wearing helmets is 39% with a standard deviation of 17.7%. 60 .b O % Wearing helmets N O O 20 40 60 80 % Receiving reduced-fee lunch a) If the R2 for the least-squares regression line for these data is 0.749956, what is the correlation between lunch and helmet? Round to 3 decimal places. b) Calculate the slope and intercept for the leastsquares regression line for these data. Slope (round 3 decimal places): Intercept (round to nearest whole number): b) Interpret the intercept of the least-squares regression line in the context of the application. 0 For each unit increase in average percentage of children receiving reduced-fee lunches, the model predicts an additional bl percent on average of bike riders wearing helmets O For each unit increase in average percentage of bike riders wearing helment, the model predicts an additional b1 percent on average of children receiving reduced-fee lunches 0 When the average of children receiving reduced-fee lunches is 0%, the average percent of bike riders wearing helments is expected to be b1 0 When the average of bike riders wearing helments is 0%, the average percent of children receiving reduced-fee lunches is expected to be 121 c) Interpret the slope of the least-squares regression line in the context of the application. 0 When the average of bike riders wearing helments is 0%, the average percent of children receiving reduced-fee lunches is expected to be b0 0 For each unit increase in average percentage of children receiving reduced-fee lunches, the model predicts an additional be percent on average of bike riders wearing helmets 0 When the average of children receiving reduced-fee lunches is 0%, the average percent of bike riders wearing helments is expected to be b0 0 For each unit increase in average percentage of bike riders wearing helment, the model predicts an additional b0 percent on average of children receiving reduced-fee lunches d) What would the value of the residual be for a neighborhood where 40% of the children receive reduced- fee lunches and 40% of the bike riders wear helmets? Round to the nearest whole number