In its latest press release, Pill International announced that they are working on a new drug that would stunt the deterioration of brain cells in Alzheimer's patients. If successful, the drug could prolong the life of patients and allow them to retain their basic mobility.
The R&D team is currently testing the drug, which comes in the form of a digestible tablet, for its ability to be dissolved and absorbed in the bloodstream. Based on their latest experiments, they have learned that there is a relationship between the amount of time that the tablet's powder spends in the tray dryer and the amount of time it takes to get dissolved (Y). As a member of this research team, you have been asked to establish the relationship between the two variables and to predict potential dissolution times based on the time spent in the dryer.
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Regress the time spent in the dryer against the dissolution time.
NOTE: Do not change the data values if you have outliers (negative observations) in the data set.
Q1 What is your intercept estimate for this model?
Q2 What is your parameter estimate for this model
Q3 If you want to set dryer time to 44 seconds, what would you expect the dissolution time to be (in seconds)?
Q4 What is the p-value for your dryer time estimate?
Using Minitab software,
Q.1) What is your intercept estimate for this model?
Ans- The intercept estimate is 112.2
Q.2) What is your parameter estimate for this model?
Ans- To use Normal distribution,
f(x)=
I got the location parameter is =48.8200
and Scale parameter is = 13.91181
In another method: Box-Cox transformation
location parameter is = 48.8200 and Scale parameter is = 13.91181
Q.3) If you want to sett dryer time to 44 seconds, what would you expect the dissolution time to be (in a sec)?
Ans- The regression equation is,
dissolution time = 112.2+ 4.622*time spend in dryer
we put dryer time is 44 seconds then I got dissolution time is 315.568 second.
Q.4) What is the p-value for the dryer estimate?
Ans- The probability value of the dryer estimate is 0.0000
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