The bottling company measured a sample of 30 bottles to test if there is a significant likelihood that a bottle will have less than 16 ounces of liquid in it. The descriptive results of the test indicated that the average of the sample was 15.85, which is lower than the 16 ounce speculation. The median of the 30 bottles was 15.99, indicating that the median is relatively close to the 16 ounce speculation (Table 1). The standard deviation between measurements was .66. There was a 95% confidence interval of a lower limit for ounces of 15.60, however, the upper limit for ounces was 16.10. These statistics are indicative of the need to perform further statistical testing to measure the probability that a bottle will have less than 16 ounces.
H10: The probability that a bottle contains less than 16 ounces is not significant at p < .05.
H1A: The probability that a bottle contains less than 16 ounces is significant at p < .05.
Figure 1. A histogram of ounces per bottle.
Based on the results of the one-sample t-test, the null hypothesis is accepted. The results indicated that p=.12. The lack of significance means that there is an insignificant likelihood that a bottle will have less than 16 ounces. The insignificance of the issue means that management should not consider this a pressing issue to address, however, in order to make sure the customer is not shorted, management may not make this a high priority.
Based on this data set, the claim that there is less soda per bottle is not substantiated by this statistical test. In order to mitigate the issue in the future, there are a few things that can be done. One thing that can be done in order to mitigate this issue in the future is to implement a quality control mechanism where each bottle is measured before it is sent out. If bottles are determined to have less than 16 ounces, then the bottle can be rejected. One way that this can be effectively done is for the bottling machine to measure the amount of soda prior to being released in a staging mechanism of the bottling process. By doing this, the amount to be released into the bottle will be measured before the machine releases the soda into the bottle. Since this problem is insignificant, the firm should not invest a large amount in solving the problem.
Works Cited
Green, Samuel B., and Neil J. Salkind. Using SPSS for Windows and Macintosh: Analyzing and Understanding Data. Prentice Hall Press, 2010.
