Normalised MEC (fish example)

	A	B	C	D	E	F	G	H	I	J	K	M	N
1	Notes
2	I think I've done this correctly, but I'm not sure. I tried to follow the formula here: https://www.cs.cmu.edu/~epxing/Class/10810-07/lectures/normLec.pdf (slides 9 and 11). I didn't know for sure what should count as the population variance and population mean, so I used the variances and means across all theories and options. It's possible the "standardisation" approaches here are relevant, but I think that's something separate: https://medium.com/@swethalakshmanan14/how-when-and-why-should-you-normalize-standardize-rescale-your-data-3f083def38ff
3	Reasons to think I did it correctly: The variances of the normalised functions come out as equal, which is the goal. The pattern of results in the three-option case seems to make sense; playing around with the T1 credence (and by extension with the T2 credence) suggested this basically gives an answer that's less favourable to T1 than the non-normalised answer was, but can still go T1's way if T1 credence is high enough, and especially can mandate the compromise egg curry; this seems to make sense, because normalisation reduces the disproportionate apparent "stakes" for T1.
4	Things I'm still confused about: Does it make sense that in the two-option case, post-normalisation, it seems that all that matters is the credences (it basically seems to be My Favourite Theory), based on playing around with the credences? Does it matter that the normalised CW scores are negative in most cases? (I don't think so, as utility functions can be given a positive affine transformation.) Can/should I fix that? Why are the ranges the same (but opposite sign) in the two option case, but different (though similar) in the one option case?
5
6	With three options
7			Credence assigned	Non-normalised choice-worthiness	Expected CW of option	Mean of theory's (T's) CW function	Variance of T's CW function	Overall mean	Overall variance	Normalised CW	Expected CW of option	Variance of T's normalised CW functions (just to check I did my calculations right)	Ranges of normalised CW
8	Fish curry	T1	0.3205	-90	-22.05	-28.33333333	2858.333333	-10.33333333	1534.666667	-52.75736418	-101.528206	1534.666667	69.61041107
9	Fish curry	T2	0.6795	10		7.666666667	6.333333333			-124.5319659		1534.666667	77.83247868
10	Tofu curry	T1	0.3205	5	5					16.85304689	-132.1052385
11	Tofu curry	T2	0.6795	5						-202.3644446
12	Egg curry	T1	0.3205	0	5.436					13.18934104	-101.5471547
13	Egg curry	T2	0.6795	8						-155.6649574
14
15	Two options only
16			Credence assigned	Non-normalised choice-worthiness	Expected CW of option	Mean of theory's (T's) CW function	Variance of T's CW function	Overall mean	Overall variance	Normalised CW	Expected CW of option	Variance of T's normalised CW functions (just to check I did my calculations right)	Ranges of normalised CW
17	Fish curry	T1	0.25	-90	-15	-42.5	4512.5	-17.5	2341.666667	-46.82386793	-165.6844557	2341.666667	-68.43488389
18	Fish curry	T2	0.75	10		7.5	12.5			-205.3046517		2341.666667	68.43488389
19	Tofu curry	T1	0.25	5	5					21.61101597	-199.9018977
20	Tofu curry	T2	0.75	5						-273.7395356
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