ID	Sweetener	Batch	Score
1	C	3	62
2	C	7	65
3	S	1	93
4	B	5	55
5	A	4	85
6	C	6	70
7	B	2	87
8	S	3	85
9	C	6	63
10	A	1	75
11	B	5	76
12	S	4	100
13	B	5	86
14	C	3	78
15	A	2	86
16	S	6	75
17	C	1	78
18	B	4	94
19	A	3	72
20	B	7	77
21	B	5	78
22	C	6	70
23	S	4	75
24	C	7	51
25	B	2	59
26	A	3	70
27	C	6	62
28	S	5	66
29	B	4	70
30	C	1	96
31	A	3	76
32	S	2	94
33	A	7	69
34	A	1	84
35	B	5	78
36	A	7	67
37	A	2	81
38	C	3	64
39	S	1	89
40	B	7	61
41	S	5	87
42	B	4	76
43	S	7	88
44	C	1	66
45	B	2	90
46	S	6	74
47	A	5	73
48	C	4	80
49	S	2	87
50	A	1	82
51	C	6	60
52	A	2	79
53	B	6	65
54	A	3	86
55	S	7	61
56	S	4	70

SOLVE:

IMPORTANT: PLEASE HELP ME WITH DATA ANALYSIS PARTS 1 THROUGH 5. THIS IS A RANDOMIZED COMPLETE BLOCK DESIGN (RCB). SO, DO THE ANALYSIS WITH RESPECT TO IT.

ALSO PLEASE PLEASE CAN YOU PROVIDE THE IMAGES FOR THE OUTPUT THAT YOU GET IN SPSS OR RSTUDIO. ALSO CAN YOU PROVIDE EXPLANATION FOR EACH OF THE 5 PARTS OF THE DATA ANALYSIS?

IF YOU HAVE ANY QUESTIONS PLEASE LET ME KNOW. THANK YOU SO MUCH FOR THE HELP.

The Problem Three brands of non-sugar sweeteners (coded " A ", " B ", and " C ") claim their products taste just like sugar (coded " S "). The goal of the project is to test whether their claim can be justified when their products are used in cookies. Last week I made a batch of 8 cookies following the world's best cookie recipe. Two of the cookies were made with sweetener A, B, C or S, respectively. The amounts of non-sugar sweeteners are determined by the product instructions so that they are supposed to taste the same sweetness as the amount of sugar in the recipe. Then a friend of mine tasted and scored them from 0 (the worst taste ever) to 100 (the best taste ever). The scores are in the following table. Youaregoingtodesignalargerexperimenttotestwhetherthenon-sugarsweetenerstastejustlike sugar. You are going to an outdoor party, where around 50 people are expected to attend. Before the party, you plan to prepare the cookies made with each of four sweeteners A, B, C and S. At the party, you plan to ask the guests to taste your cookies without knowing the ingredients, and score the taste of the cookies from 0 to 100 . Each guest is limited to taste only one cookie. You have only one baking pan to bake at most 8 cookies at a time. Based on your baking experience, there might be slight variations from batch to batch, and the effect of batch may be different for different sweeteners. Therefore, you decide to record the batch number as well. In summary, for each cookie, you know which sweetener it is made of (A,B,C, or S), and you know its batch number (1st,2nd,3rd,), but the tasters don't know none of these and they will provide their score (0-100). DesignofExperiment In the design you definitely want to block the batches. Also, since you cannot control the characteristics of the tasters (gender, age, preference on sweetness, etc.) at the party, you also want to eliminate any possible effects of these factors by randomization. In order to determine how many cookies to make, you may use the data of my experiment as a reference. Make sure the test for the main effect has at least 90% power. To make the distribution of cookies smooth and blind to the tasters, you should prepare the cookies in advance in the order that you would like the tasters to taste. Carefully set up a design table, and you will present the cookies in the order of the cookie ID, starting with cookie ID \#1 to the first taster, and then record his/her score; and then give cookie ID \#2 to the second taster, and Data Analysis The primary goal is to determine whether cookies with different sweeteners taste differently on average based on the scores, adjusted for the batch order. There might be an interaction between sweetener and batch order on the taste. The full analysis must contain the following parts: 1. Test for the main effect of sweeteners, adjusted for batch effect. 2. Test for the interaction between sweetener and batch. Refit the model if necessary. 3. Point estimate and confidence interval of the mean score for each sweetener. 4. Post Hoc analysis comparing each pair of sweetener. 5. Model conditions assessment