In this paper I am going to perform a one-tailed, one-sample tÃÂ¬-test in order to test the null hypothesis that the average number of ounces of cereal per box equals sixteen. A manufacturer of a particular brand of cereal maintains there is an average of sixteen ounces of cereal per box. On the other hand, a consumer group asserts the average is fewer than sixteen ounces per box. The consumer group is going to file a class action lawsuit for false advertising if the average is fewer than sixteen ounces per box. I was hired by the consumer group to determine whether the consumer group is correct or the cereal manufacturer is correct.

According to Sprinthall (2003, p. 249), ?Sometimes, however, a researcher not only assumes that a mean difference between samples will occur but also predicts the direction of the differenceÃÂ¬. When this happens, the statistical decision is not based on both tails of the distribution, but only one.

In this instance, the sign of the t ratio is crucial. When conducted in this way, the t test is called a one-tail t test. The calculation of a one- tail t test is identical to that of the two-tail t. The only differences are in the way the alternative hypothesis is written and in the method used for looking up the table value of t [italics in original].

I randomly selected 20 supermarkets, and from each supermarket I randomly selected one box of the manufacturer?s cereal. I then weighed the cereal in each box for all twenty boxes. I came up with numbers ranging from 12.4 being the lowest to 18.4 being the highest weight of the cereal. I then used the one-tailed, one-sample t test to test the null hypothesis that the average number of ounces of cereal...