Statistical quality control is important because it uses statistical methods to monitor the quality of a product. This type of auditing maximizes manufacturing productivity and minimizes errors associated with human judgement.
Know MoreStatistical quality control relies on statistics and data reports to assess quality and is therefore an efficient means to evaluate a manufactured product. Statistical quality control helps maintain the consistency of how a product is made. Statistical quality control methods can include cause-and-effect analysis, check/tally sheets, histograms, Pareto and scatter analyses, data stratification, defect maps, events logs, progress centers and randomization. Graphical charts and graphs, the part of statistical process control that monitors the manufacturing process, help decipher the statistics and data from quality control reports. One important method of statistical quality control is acceptance sampling. In acceptance sampling, a sample of a product is randomly taken to determine whether or not to continue making the product. If the percentage of "good" or acceptable product is higher than "bad" or defective product in the sample, the product is approved as is and manufacturing continues. If not, the product is rejected and production stops. Any evaluation process that involves samples and human judgement usually assumes a margin of error. With statistical quality control, human error is reduced.
Learn MoreA poisson distribution displays discrete random variables, according to the University of Glasgow. Examples of discrete random variables include the numbers of cars that pass through an intersection in a given period of time. A discrete random variable is a representation of a countable number of separate values; this variable is always a finite number. Discrete random variables follow a poisson distribution.
Full Answer >Statistics are a methodology necessary in the field of statistics and are used to collect, analyze and evaluate data. Economics depends heavily on the use of statistics.
Full Answer >In statistics, common response refers to changes in both the explanatory and response variables that result from changes in another variable. The variable that triggers a common response is typically not part of the research design.
Full Answer >To find the IQR, find the median or center of the data, calculate the median of the lower and upper halves of the data, and find the difference between the medians of the lower and upper halves of data. You need a data set, a calculator, and pencil and paper to complete this task.
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