QUESTION 1 001. A wildlife analyst gathered the data in the following table to develop a logistic regression model to predict the gender of bears. He used GENDER as the dependent variable and WEiGHT as the independent variable. For GENDER, he used male=0 and female=i . WEIGHT CHEST IENG'I'H GENDER 344 45.0 67.5 0 416 540 720 0 220 41.0 700 1 360 Ii911\"! 685 0 332 44.0 73.0 0 11] 320 63.0 1 436 480 3'20 0 132 33.0 610 1 356 430 691.0 1 13] 350 59.0 0 202 40.0 630 1 365 500 $115 0 Estimate the logistic regression model. Based on the computer output, at 5% level of signicance we can conclude that in the population WEIGHT is a significant predictor of GENDER. 0 True 0 False QUESTION 2 002. Based on raw data provided in Question 1, the absolute difference in mean weight between male and female cases is . OD 0 133.3, with the difference favoring females 0 133.3, with the difference favoring males 0 cannot calcuiate (there is insufcient information) QUESTION 3 Q03. Based on raw data provided in Question 1, without controlling for the effect of an).r other variable the odds of being a female (as opposed to being a male) are . O 1.400 O 0.714 O 0.336 O 0.008 QUESTION 4 Q04. Based on raw data provided in Question 'l, without controlling for the effect of an).r other variable the odds of being a male {as opposed to being a female} are . O 0.714 O 0.098 O 1.400 O 0.336 QUESTION 5 005. Based on your logistic regression output from Question 1, at 10% level of signicance we can conclude that in the population WEIGHT is a signicant predictor of GENDER. 0 True 0 False