We can use the sign test in this situation. We suppose that random variable "X" corresponds to the values in row "Food A" and "Y" to the values in row "Food B". We formulate two hypotheses: "H_0: P(X>Y)=\\frac{1}{2}" and "H_1:P(X>Y)<\\frac{1}{2}" . As we can see from the values, for all samples holds "y_i<x_i" . Thus, we accept the alternative hypothesis "H_1" . It means that Food B is better than Food A.
We took the data from the table. As we can see, there are 8 entries. The differences between Food B and Food A are always positive. For the sign test we use the values from the table for binomial distribution (https://www.statisticshowto.com/tables/binomial-distribution-table/). We calculate the probability of 8 successes in 8 trials with the probability 0.5. It is equal to approximately 0.004. It means that the hypothesis "H_0:P(X>Y)=\\frac12" can be rejected. Thus, the Food B is better than Food A
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