Bottling Company Case Study Manager

At a major bottling company the customers are dissatisfied regarding the weight of the product which prompts the management to investigate the same. Statistical techniques have been used to check for the validation of customer claims. The Case A major bottling company advertises that its product has 16 ounces in a bottle. Since recently, customers have begun to complain that the bottles of soda contain less than 16 ounces. To investigate the same, we pull 30 bottles of the line at random from all shifts at the bottling plant. The amount of soda in each bottle selected is as given below. BottleOuncesBottleOuncesBottleOunces114.511152114.12171215.12214.2314.713152317.1416.81416.42416.2514.91515.82517.1615.31616.32614.5714.917162716.4815.51816.12814.8914.81915.82916.21016.32016.33016.4Measurement of Central Tendency and Dispersal Mean ounces of soda per bottle (sum of weights of all observations)/number of observation, xbar (14.51714.716.216.4)/30 469.5/30 15.65 ounces Median ounces of soda per bottle average weight of bottles of middle observation after arranging the data increasing order So, the weights for median calculation is BottleOuncesBottleOuncesBottleOunces117.11116.22115217.11216.22214.93171316.12314.9416.814162414.8516.41515.82514.8616.41615.82614.7716.41715.52714.5816.31815.32814.5916.31915.12914.21016.320153014.1 As, we take the lower limit and upper limit from the mean, so we remove (100-95) 25 area from both sides for finding z value from the table The confidence interval for population mean is given as So, if the test statistics is less than the critical