1. Make a scatterplot of diameter vs time for all tableware. Be sure you give it a title and axis labels.
2. Check the conditions for linear regression for this scatterplot .
3. Check the scatterplots for the subgroups – find 1 that is appropriate for linear regression.
4. For that subgroup, include the scatterplot, correlation coefficient, and formula for the least-squares regression line
5. Write a sentence interpreting the slope. Write a sentence interpreting the intercept.
6. Just overall, does it seem like predicting finishing time from diameter is going to work? Or are there too many other factors for this to be very useful? (If so, what factors?)

Description: Nambe Mills manufactures a line of tableware made from sand casting a special alloy of several metals. After casting, the pieces go through a series of shaping, grinding, buffing, and polishing steps. In 1989 the company began a program to rationalize its production schedule of some 100 items in its tableware line. The total grinding and polishing times listed here were a major output of this program.
Number of cases: 59
Variable Names:
DIAM: Diameter of item, or equivalent (inches)
TIME: Grinding and polishing time (minutes)

All Tableware			Bowls			Casseroles			Dishes			Trays			Plates
DIAM	TIME		DIAM	TIME		DIAM	TIME		DIAM	TIME		DIAM	TIME		DIAM	TIME
10.7	47.65		8	34.88		10.7	47.65		10	55.53		16	54.86		12.4	23.77
14	63.13		10.4	17.67		14	63.13		6.5	17.46		15	44.14		16	26.09
9	58.76		7.4	16.41		9	58.76		5	21.04		25	109.38		11.7	26.52
8	34.88		5.4	12.02		10.5	43.14		11	45.12		5.5	26.53		10	31.86
10	55.53		6	23.21		15.4	49.48		11.1	33.71		12.3	33.89		6	20.85
10.5	43.14		9	28.64		12.4	48.74		9.8	44.45		19.5	64.3		11	26.25
16	54.86		9	44.95		13.5	68.63		8.8	27.76		17.8	74.48		11.1	21.87
15	44.14		7.5	20.21		13	86.42					11.5	34.16		14.5	23.88
6.5	17.46		14	32.62		14	33.7					12.7	31.46		5	16.66
5	21.04		7	17.84		12.4	32.9					7.5	20.83

25	109.38		9	22.82
10.4	17.67		12	29.48
7.4	16.41		5.5	15.61
5.4	12.02		6	13.25
15.4	49.48		12	45.78
12.4	48.74		14.2	37.11
6	23.21		10	23.74
9	28.64		13	39.71
9	44.95		15.2	22.55
12.4	23.77		11	53.18
7.5	20.21		8	21.34
14	32.62		9	20.59
7	17.84		8.5	30.2
9	22.82

12	29.48
5.5	15.61
6	13.25
12	45.78
5.5	26.53
14.2	37.11
11	45.12
16	26.09
13.5	68.63
11.1	33.71
9.8	44.45
10	23.74
13	86.42
13	39.71
11.7	26.52
12.3	33.89
19.5	64.3
15.2	22.55
10	31.86
11	53.18
17.8	74.48
11.5	34.16
12.7	31.46
8	21.34
7.5	20.83
9	20.59
14	33.7
12.4	32.9
8.8	27.76
8.5	30.2
6	20.85
11	26.25
11.1	21.87
14.5	23.88
5	16.66