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Thnx

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- Thread starter HeapofAsh
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Thnx

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Ray Vickson

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Thnx

If you are able to assume that the data are at least approximately normally distributed, this would be a two-way analysis-of-variance problem (ANOVA), where you have two brands (X and Y) along one "axis" and ingredient type (1,2,3,4) along the other "axis".

You should be aware that some of this type of material is often only covered in a second course in Applied Statistics, and that students have trouble grasping some of it---not to mention getting terminally confused and making lots of errors. Looking at a book (rather than a web page) is preferable, but it should probably not be an introductory textbook.

Anyway, for what it is worth, see, eg.,

http://www.stat.purdue.edu/~zhanghao/STAT514/handout/nested.pdf

http://www.itl.nist.gov/div898/handbook/ppc/section2/ppc233.htm

http://biol09.biol.umontreal.ca/PLcourses/Nested_and_two-way_anova.pdf

http://www3.imperial.ac.uk/pls/portallive/docs/1/1171923.PDF

Other issues arise if the data are not normally distributed (or at least, approximately so), and I know little to nothing about how to proceed in that case. Look up 'non-parametric methods'.

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You should be aware that some of this type of material is often only covered in a second course in Applied Statistics, and that students have trouble grasping some of it---not to mention getting terminally confused and making lots of errors. Looking at a book (rather than a web page) is preferable, but it should probably not be an introductory textbook.

Yeah it seems beyond my stat course level. How about doing hypothesis test on difference of means or proportion of each type of ingredient.

For the amount (weight) of flour in food by Brand x and Brand y:

H

H

And do the same for different ingredients. If they it turns out that the P

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