Please do not copy old answer - if it is incorrect, I will downvote. Thanks.

In a process development study on yield, four factors were studied, each at two levels: time (A), concentration (B), pressure (C), and temperature (D). A single replicate of a 2 4 design was run and the resulting data are shown in the following table.

Actual Run Order	A	B	C	D	Yield (lb)
5	-1	-1	-1	-1	147
9	1	-1	-1	-1	162
8	-1	1	-1	-1	105
13	1	1	-1	-1	138
3	-1	-1	1	-1	270
7	1	-1	1	-1	243
14	-1	1	1	-1	279
1	1	1	1	-1	215
6	-1	-1	-1	1	102
11	1	-1	-1	1	249
2	-1	1	-1	1	103
15	1	1	-1	1	156
4	-1	-1	1	1	221
16	1	-1	1	1	341
10	-1	1	1	1	244
12	1	1	1	1	324

The factor level settings are as below:

Factor	Low(-)	High(+)
A (hr)	2	4
B (%)	10	20
C (psi)	60	90
D (temp)	50	80

(a) Estimate the factor effects by hand (you may use excel). Which effects appear to be large?

(b) Perform an analysis of variance by hand to confirm your conclusions for part (a). What terms are significant at =0.05?

(c) Confirm your results in Minitab. Construct a normal probability plot of the factor effects, perform an ANOVA and analyze the ANOVA residuals.

(d) Construct a regression model by hand for predicting yield. Use the significant terms you identified in your part (b) ANOVA.

(e) Confirm you part (d) results using Minitab. Analyze the residuals from your regression analysis.

(f) What levels of A, B, C, and D would you recommend using to maximize the yield?

(g) Using the regression model found in part (e), predict the yield at 3.25 h, 14%, 75 psi, and a temperature of 60.