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The regression plots Hours (y) vs jobs (x). Let's say the equation is: y = 0.4x + 90

Is it okay to say that the time for each job is 0.4 hours?

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    $\begingroup$ The incremental time for each job is 0.4 hours. For the actual time you have to take into account the 90 hour constant $\endgroup$ – Jake Westfall Jan 22 at 21:12
  • $\begingroup$ The estimate of the expected marginal time for each job would be 0.4 hours (i.e. adding a job will on average add 0.4 hours). It may be that no job will take 0.4 hours, even on average, because that intercept term is large - it depends on how that 90 is allocated to jobs $\endgroup$ – Glen_b Jan 22 at 23:15
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I presume $x$ is number of jobs and $y$ is number of hours to complete it. It's not correct to say that time for each job is 0.4 hours because you have a (pretty large) bias term. This means you have a fix cost. Performing one job takes $90.4$ hours, two jobs $90.8$ hours etc. So, you can say that each additional job takes 0.4 hours. And, time for each job asymptotically approaches $0.4$ hours, i.e. as $x\rightarrow \infty$.

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Not exactly. Assuming a simple linear model $y = \beta_0 + \beta_1 x + \epsilon$, the parameter $\beta_1$ (in this case $0.4$) represents the effect of a one-unit change in the corresponding $x$ (here jobs) covariate on the mean value of the dependent variable, $y$ (here hours), assuming that any other covariates remain constant at some value. As the $\beta_0$ (the intercept) is $90$, probably there are some other factors that require on average $90$ hours to be taken into account. It is more relevant to say that each additional job requires an additional $0.4$ hours.

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