A medical center is concerned about the length of stay, measured in days, of its patients who undergo joint-replacement procedures.

To this end, it has asked you to compare the length of stay of patients who received a ceramic implant (coded as 1 in the predictor variable Ceramic) to the length of stay of patients who received a conventional implant (coded as 0 in the predictor variable Ceramic).

After drawing a small random sample of the patients who received a joint replacement at this medical center, you ran the following regression model:

Length of Stay	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	4.34	0.25	17.35	0.00	3.85	4.83
Ceramic	-0.81	0.26	-3.07	0.00	-1.33	-0.29

1.Was there a difference in predicted length of stay between the two groups in the small random sample of the patients who received a joint replacement at this medical center?

That is, was the estimated coefficient of Ceramic different from zero numerically?

Explain your answer.

2. At a 5% level of statistical significance, do you infer that there was a difference in length of stay between the two groups in the population of all patients who received a joint replacement at this medical center?

That is, was the estimated coefficient of Ceramic different from zero statistically?

Explain your answer.

3. Compute the predicted length of stay if 60% of patients receive a ceramic implant.

4. Compute the change in predicted length of stay when the percentage of patients receiving a ceramic implant increases from 60% to 100%.