from above number of elements =59
number of variables =4 (type,diameter, polishing times , Price)
observations =59 (number of set of measurements)
measurements =59*4 =236
which variables are the data set are quantitative = Diameter, polishing time and Price
Nambe Mills manufactures a line of metal tableware called "Nambeware." A piece of Nambeware is produced...
Nambe Mills manufactures a line of metal tableware called "Nambeware." A piece of Nambeware is produced by sand casting a special alloy of several metals. After casting, the piece goes through a series of steps, including shaping, grinding, buffing, and polishing The top and bottom portions of the data set that Nambe Mills collected for a study of its production schedule are reproduced below; dots indicate that the intervening rows in the data set are not displayed. (Source: DASL [The...
Nambe manufactures a line of metal tableware called Nambeware. A piece of Nambeware is produced by sand-casting a special alloy of several metals. After casting, the piece goes through a series of shaping, grinding, buffing, and polishing steps. Nambe is analyzing how to adjust its production schedule to accommodate the polishing step of a new line of casseroles that it is adding to its product line. Nambe selects a random sample of its tableware pieces and collects data on the...
Goal
Your end goal is predict finishing time for all the dishes, or
one of the subgroups, whichever is best.
Steps
Make a scatterplot of diameter vs time for all tableware. Be
sure you give it a title and axis labels.
Check the conditions for linear regression for this scatterplot
(bottom of page 385)
Please use complete sentences for each condition.
Check the scatterplots for the subgroups – find 1 that is
appropriate for linear regression.
No need to include...