Bottling Company Case Study

As a manager at a major bottling company, customers have complained that the bottles of the brand of soda produced in the company contain less than the advertised sixteen (16) ounces of product. There is need to solve the problem at hand and has to be investigated. Employees are instructed to pull thirty (30) bottles off the line at random from all the shifts at the bottling plant and measure the amount of soda there is in each bottle.

The table (i) below shows the number of ounces of soda in each bottle randomly pulled off the line.

Soda bottle S/N Quantity of ounces contained Soda bottle S/N Quantity of ounces contained Soda bottle S/N Quantity of ounces contained

1 14.5 11 15 21 14.1

2 14.6 12 15.1 22 14.2

3 14.7 13 15 23 14*…show more content…*

For tests about one mean , when the population standard deviation s is known, we use s when calculating the test statistic. (for population standard deviation), , (for sample standard deviation), the equations above are called the z scores. Therefore in our case we use . Hence for bottle 19, , = 0.346.

Using Moore’s table the p-value = 1, and significant level = 0.1. Now since p-value is greater than the significance value, then the hypothesis is considered rejected. It therefore negates the claim that the mean number of ounces in each bottle is less than sixteen (16) therefore it is not true.

It therefore follows that the customers’ complaints may be right but not all soda bottles have less than 16 ounces each as it may be claimed. There is need for appropriate measures to be taken by ensuring that the right number of ounces are in each bottle of soda. The company should also ensure that such a thing does not happen in the future through routine checking of the machines and equipments used in the firm to ensure accuracy of the product. Enough quality assurance personnel should be employed to ensure close monitoring of all the processes of soda processing which will guarantee quality as per the

As a manager at a major bottling company, customers have complained that the bottles of the brand of soda produced in the company contain less than the advertised sixteen (16) ounces of product. There is need to solve the problem at hand and has to be investigated. Employees are instructed to pull thirty (30) bottles off the line at random from all the shifts at the bottling plant and measure the amount of soda there is in each bottle.

The table (i) below shows the number of ounces of soda in each bottle randomly pulled off the line.

Soda bottle S/N Quantity of ounces contained Soda bottle S/N Quantity of ounces contained Soda bottle S/N Quantity of ounces contained

1 14.5 11 15 21 14.1

2 14.6 12 15.1 22 14.2

3 14.7 13 15 23 14

For tests about one mean , when the population standard deviation s is known, we use s when calculating the test statistic. (for population standard deviation), , (for sample standard deviation), the equations above are called the z scores. Therefore in our case we use . Hence for bottle 19, , = 0.346.

Using Moore’s table the p-value = 1, and significant level = 0.1. Now since p-value is greater than the significance value, then the hypothesis is considered rejected. It therefore negates the claim that the mean number of ounces in each bottle is less than sixteen (16) therefore it is not true.

It therefore follows that the customers’ complaints may be right but not all soda bottles have less than 16 ounces each as it may be claimed. There is need for appropriate measures to be taken by ensuring that the right number of ounces are in each bottle of soda. The company should also ensure that such a thing does not happen in the future through routine checking of the machines and equipments used in the firm to ensure accuracy of the product. Enough quality assurance personnel should be employed to ensure close monitoring of all the processes of soda processing which will guarantee quality as per the

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