A:For those who are not rixq, the probability of xevu is 11%. For those who are rixq, the probability of xevu is 28%. B:Will rixq decrease the chance of xevu? Answer: earning
A:We know that gwet causes yomx and cwoi. yomx or cwoi causes xevu. We observed an individual is not gwet. B:Would an individual is xevu if yomx instead of not yomx? Answer: jpg
A:For those who are not jyka, the probability of lirg is 53%. For those who are jyka, the probability of lirg is 83%. B:Will jyka increase the chance of lirg? Answer: jpg
A:We know that muvy causes kwox. kwox causes swoq. muvy and swoq causes kwoz. We observed an individual is not muvy. B:Would an individual is kwoz if not kwox instead of kwox? Answer: earning
A:For those who are not jyka, the probability of lirg is 74%. For those who are jyka, the probability of lirg is 83%. B:Will jyka decrease the chance of lirg? Answer: earning
A:Method 1: We look at how zuph correlates with glimx case by case according to zory. Method 2: We look directly at how zuph correlates with glimx in general. B:To understand how zuph affects glimx, is it more correct to use the Method 1 than Method 2? Answer: earning
A:Method 1: We look directly at how jyka correlates with lirg in general. Method 2: We look at this correlation case by case according to hwax. B:To understand how jyka affects lirg, is it more correct to use the Method 1 than Method 2? Answer: jpg
A:Method 1: We look at how hospital costs correlates with recovery case by case according to age. Method 2: We look directly at how hospital costs correlates with recovery in general. B:To understand how hospital costs affects recovery, is it more correct to use the Method 1 than Method 2? Answer: jpg
A:Method 1: We look directly at how zuph correlates with uvzi in general. Method 2: We look at this correlation case by case according to vubr. B:To understand how zuph affects uvzi, is it more correct to use the Method 1 than Method 2? Answer:
earning