Free Report On Bottling Company Case Study
Calculate the Mean, Median and Standard Deviation for Ounces in the Bottles.
The mean is calculated by adding the total values of the data provided and then divide it by the sum. (Bluman, 2013). When the data is analysed of the bottling company the mean is calculated to be 14.9 approximately. The data is arranged to calculate the median by identifying the middle point of the entire data set which comes out to be 14.8, in this case. The standard deviation is the square root of the variance. The standard deviation of ounces in the bottle is 0.55 to be accurate.
Construct a 95% Confidence Interval For the Ounces in the Bottles.
A confidence interval is determined to measure the reliability of the estimates provided. The confidence interval provides with an approximate range of values that involves a population parameter that is relatively unknown, and the estimated ranges can be calculated from the sample data set that is provided. The issues in the bottling case are that the customers have complained that the companies provide less than sixteen ounces of product as advertised. It is imperative that the company determines whether the soda bottles contain less than sixteen ounces or not. The sample size as mentioned in the data set is 30, and the calculated mean is 14.9. The standard deviation already calculated is 0.55. These calculations when taken into consideration, and a confidence interval of 95 percent the confidence interval will be 0.2. This means that there is around 95 percent possibility that the true population falls within the range of 14.7 to 15.1.
Conduct a Hypothesis Test to Verify if Claim is Supported.
The hypothesis test is conducted in order to validate the decision-making process that helps in the assessment of the population (Bluman, 2013). Testing the hypothesis will eventually result in whether the test will be rejected or accepted. The main claim of the customers is that the bottles contain less than 16 ounces of soda ingredient as opposed to what is advertised by the company. The null hypothesis will be that the bottles contain sixteen ounces. The alternative hypothesis that will be developed is that less than 16 ounces are available in the bottle. The significance level is around 0.05 whereas the test method that will be used in this regard is t-score. The calculated statistics is -11.25 and the P-Value is 1.0. The P-value assumes that the null hypothesis is true, and a sample statistic is observed in this regard. The T Critical Value calculated is 1.699. This calculation clearly demonstrates that the soda bottles does not contain 16 ounces, and the customer complaint is right.
Three Possible Causes of Conclusion.
One main conclusion that can be reached is that probably the machine has major errors which mean that the values can be set wrong, and the machine has faults in some areas of calculations. Another possibility is that the soda product condense down or settles during storage that impacts its measurements. The third possibility is that a possible human error has occurred that means the bottles are taken off early from the assembly lines before the machine has properly filled the bottles and the correct amount (Bluman, 2013).
Suggest Strategies to Avoid the Deficit In the Future.
It is imperative that accuracy tests must be run on a regular basis in order to avoid any calibration errors. The employees must be held accountable for any possible human errors that are made in the assembly line. A quality control department must be established as this department is essential to maintain the product quality and improvise on any manufacturing errors. It is important that these errors should be eliminated or at least reduced to the major extent. The quality control department will train the employees to maintain quality standards, create quality benchmarks and test the products before the dispatch to ensure that the product quality is maintained (Bluman, 2013).
Bluman, A. G. (2013). Elementary statistics: A brief version (6th ed.). New York, NY: McGraw-
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