Sum of the ounces = 14.23 + 14.32 + 14.98 + 15.00 + 15.11 + 15.21 + 15.42 + 15.47 + 15.65 + 15.74 + 15.77 + 15.80 + 15.82 + 15.87 + 15.98 + 16.00 + 16.02 + 16.05 + 16.21 + 16.21 + 16.23 + 16.25 + 16.31 + 16.32 + 16.34 + 16.46 + 16.47 + 16.51 + 16.91 + 16.96 = 475.62
Mean = 475.62/30 = 15.854
Median = (15.98 +16.00) / 2 = 15.99
= square root of 0.423 = 0.65
A confidence level is a measure of the dependability of an appraisal. It gives an expected scope of qualities which is liable to incorporate an obscure populace parameter, the evaluated reach being ascertained from a given arrangement of sample data. The clients for this situation study have implored that the bottling organization gives not exactly the advertised sixteen ounces of the product. They have to figure out whether there is sufficient confirmation to conclude the soda bottles don’t contain sixteen ounces. The example size of the drinks is 30 and has a mean of 15.85. The standard deviation is observed to be 0.65. With these figures and a certainty level of 95%, the confidence interval would be 0.2. There is a 95% certainty that the true mean falls inside of the range of 15.65 to 16.05.
Hypothesis testing is a decision making procedure for assessing cases around a populace. This procedure is utilized to figure out whether one will acknowledge or dismiss a hypothesis or theory. The case is that the soda bottles contain less than 16 ounces. The null hypothesis is the soda bottles contain 16 ounces. The alternate hypothesis is the soda bottles contain less than 16 ounces. The significance level that will be used in this hypothesis testing will be 0.05. The test strategy to be utilized is a t-score. The test statistic is computed to be -11.24666539 and the P value is 1.0. The P-value is the likelihood of observing the sample measurement as compelling as the test measurement, if the null hypothesis is true then, the t critical value is 1.69912702. The computations show there is sufficient proof to support the case that the bottles don’t contain 16 ounces.
My conclusion is that there is less than sixteen ounces in a bottle of soda. One conceivable reason for the conclusion could be the machine has operational or mechanical issues. The alignment or calibration qualities could be set wrong or the machine could be broken in different parts. A second reason could be because of human blunder, for example, taking the container off of the mechanical production system before the machine has administered the right sum. Another conceivable reason for the conclusion could be that the sodas in the bottle are not stored properly therefore they could settle or condense making them deficient of the required ounces.
I prescribe that there will be a regular maintenance check on the production equipment and the information recorded. Likewise, workers will be observed in how exhaustive the item is reviewed before leaving the mechanical production system and packaged. I will convince the end users the likelihood that the soda may have encountered dissipation and gone flat contingent upon to what extent it remains unopened in storage. Another approach to keep away from the deficiency later on is to run technical tests consistently to maintain avoid adjustment and calibration mistakes. Quality control is a procedure through which a business looks to guarantee that item quality is kept up or enhanced and production errors are decreased (Grous, 2013). Quality control requires the business to train the faculty, make benchmarks for item quality, and test items to check for factually noteworthy varieties. This permits the business to make a domain in which both administration and the workforce make progress toward flawlessness.