(Questions 1 - 3) Based on data collected over several sessions, a statistically minded trainer of office typists modeled the linear relationship between the number of hours of training a typist receives and the e-mainten eneed (in words ner minute)
with the equation speed = 10.6 + 5.4hour
1)Which of these statements best interprets this equation?
(A) Typists increase their speed by 10.6 wpm for every 5.4 hours of training.
(B) Typists increase their speed by 5.4 wpm for every 10.6 hours of training.
© A typist who trains for an additional hour will benefit with a speed increase of 5.4 wpm.
(D) On average, typists tend to increase their speed by roughly 5.4 wpm for every hour of training.
(E) For every 5.4 hours of training, typists can increase their speed from 10.6 wpm to faster.
2)Which is the best interpretation of the y-intercept for this model?
(A) People who can't type need about 10.6 hours of training.
(B) Before undergoing this training, typist's average speed was about 10.6 wpm.
(C) The y-intercept is meaningless here because no one types at 0 wpm.
(D) The y-intercept is meaningless here because none of the typists had 0 hours of training.
( In regression models, the slope has meaning, but not the y-intercept.
3)After some training, one of the typists was told that the speed he attained had a residual of 4,3 word per minute.
How should he interpret this?
(A) He types slower than the model predicted, given the amount of time he spent training
(B) He types faster than the model predicted, given the amount of time he spent training.
(E) He can't interpret his residual without also knowing the correlation.
©) He can't interpret his residual without also knowing the size of the other people's residuals.
(E) He can't interpret his residual without also knowing the standard deviation of the residuals
