Agree or disagree with each of the following statements and provide a short explanation. O Arnold...

 

 

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Agree or disagree with each of the following statements and provide a short explanation. O Arnold wanted to compare the effects of cardio exercise and weightlifting on weight loss. He ran the following two regressions on the same sample, weightloss on 1, cardio weightloss on 1, lifting He found that the coefficient from the first regression was larger than the coefficient from the second regression and therefore concluded that all else equal, an additional hour of cardio leads to more weight loss than an additional hour of lifting. O Michelle wants to understand the effect of mailing advertisements (maili = number of mailing advertisements per year) on charity contributions (charity = annual contributions). She started with the following regression charity, Bo+maili1 + inci2 + i She then added several more variables charityi = = Bo+maili1 + inci2 + colori3 + stampi4 + female; 5 + i Where color is the color of the envelope, stamp, is equal to one if there were flowers on the stamp, and female; is equal to one if their local letter carrier is female. After estimating both models, she found her R increase from .45 to .48 with the second model. She concluded that the second regression must have a better fit and therefore is preferred. Agree or disagree with each of the following statements and provide a short explanation. O Arnold wanted to compare the effects of cardio exercise and weightlifting on weight loss. He ran the following two regressions on the same sample, weightloss on 1, cardio weightloss on 1, lifting He found that the coefficient from the first regression was larger than the coefficient from the second regression and therefore concluded that all else equal, an additional hour of cardio leads to more weight loss than an additional hour of lifting. O Michelle wants to understand the effect of mailing advertisements (maili = number of mailing advertisements per year) on charity contributions (charity = annual contributions). She started with the following regression charity, Bo+maili1 + inci2 + i She then added several more variables charityi = = Bo+maili1 + inci2 + colori3 + stampi4 + female; 5 + i Where color is the color of the envelope, stamp, is equal to one if there were flowers on the stamp, and female; is equal to one if their local letter carrier is female. After estimating both models, she found her R increase from .45 to .48 with the second model. She concluded that the second regression must have a better fit and therefore is preferred.

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