Question

Need help properly setting up in minitab. What are responses, columns labeled, etc.

A company markets its products by direct mail. An experiment was conducted to study the effects of three factors on the customer response rate for a particular product. The three factors are A = type of mail used (3rd class, 1st class), B = type of descriptive brochure (color, black-and-white), and C = offer price ($19.95, $24.95). The mailings are made to two groups of 8,000 randomly selected customers, with 1,000 customers in each group receiving each treatment combination. Each group of customers is considered as a replicate. The response variable is the number of orders placed. The experimental data is shown below.

Coded Factors Number of Orders 50 54 42 48 43 46 45 46 42 49 48 47 56 54 Factor Levels Low () High (+1) A (class 3rd B (type BW C(S) $19.95 $24.95 1st Color (a) Analyze the data from this experiment. Which factors significantly affect the customer response rate?

Answer 1

Consider (a) only. Ignore (b), (c)

Factorial Regression: Rep1 versus rep, A, B, C

* NOTE * This design is not orthogonal.

Method

Source	DF	Adj SS	Adj MS	F-Value	P-Value
Model	8	290.686	36.336	13.87	0.002
Blocks	1	0.286	0.286	0.11	0.752
Linear	3	67.911	22.637	8.64	0.013
A	1	27.161	27.161	10.37	0.018
B	1	1.786	1.786	0.68	0.441
C	1	30.754	30.754	11.74	0.014
2-Way Interactions	3	192.386	64.129	24.49	0.001
A*B	1	64.286	64.286	24.55	0.003
A*C	1	127.504	127.504	48.68	0.000
B*C	1	43.754	43.754	16.71	0.006
3-Way Interactions	1	0.004	0.004	0.00	0.968
A*B*C	1	0.004	0.004	0.00	0.968
Error	6	15.714	2.619
Total	14	306.400

Analysis of Variance

Model Summary

S	R-sq	R-sq(adj)
1.61835	94.87%	88.03%

(a)

a p-value for B and A*B*C is higher than 0.05 so it's a significantly affect the model.

(b)

here,

R-sq	R-sq(adj)
	94.87%	88.03%

hence, a model is better as R2 and adj R2 both is high for the model.

(c)

the only brochure color effect the company sells, hence company have to expend money only on it.