- Know the common sampling distributions used for quality control and how to use them
- Normal distribution
- T-distribution
- Chi-square distribution
- F distribution
- Binomial distribution

- Given a sample data set, be able to calculate the sample mean, sample variance, or sample proportion.
- Given a sample mean, variance, or proportion be able to conduct a hypothesis test on
- true mean given a sample mean and known variance
- true mean given a sample mean and sample variance
- mean difference given a paired test
- difference of two means where variances are known
- difference of two means where variances are unknown
- true variance given a sample variance
- ratio of two variances
- true proportion given a sample proportion

- Know how to create and interpret the magnificent 7
- process flow chart
- check sheet
- histogram
- pareto diagram
- cause and effect diagram
- scatter plot
- control chart

**Given upper and lower specification limits and the mean and standard deviation of a process, be able to determine the capability index for the process.****Given data, summary statistics, and a factors table for control charts, be able to calculate****the upper and lower control limits for X-bar and R charts for small sample sizes,****the upper and lower control limits for X-bar and s charts for larger sample sizes,****the upper and lower control limits for X and moving R charts for individual observations,****the upper and lower control limits for a Q-Sum chart.**

**Given a sample data set and summary statistics for attribute data, be able to calculate****the upper and lower control limits for percent defective,****the upper and lower control limits for number defective,****the upper and lower control limits for the number of defects.**

**Given a description of a process be able to suggest which type of control chart should be created by the engineering manager.****Given a control chart be able to suggest whether or not the process is in control and, if not, whether it is likely caused by common cause or special cause variation**.**Given a control chart, be able to identify a process shift, potential shift, cycle, or trend for the process.****Given a control chart with specified control limits, be able to utilize the summary statistics to estimate the capability of the process.**

- Given summary statistics, be able to calculate upper and lower control limits for short run (DNOM) charts.
- Given data, be able to calculate standardized data.
- Given standardized data, be able to calculate upper and lower control limits for a standardized chart.
- Given summary measurement data, be able to calculate the standard deviation of measurement error and the Precision-to-tolerance ratio.
- Given summary data and acceptable quality level, be able to calculate the probability of accepting a lot.
- Given summary data and a lot tolerance percent defective that is important to the consumer, be able to calculate the probability a bad lot will be accepted.
- Given AQL, LTPD, alpha, and beta risk levels, be able to use the Binomial Nomograph to determine a sampling plan.
- Given summary data for a single factor randomized design, be able to calculate the mean square for treatments, the mean square error, and the F test to determine if treatment factors are significant.
- Given the output of a two factor replicated design and a partial anova output, be able to complete the anova table to determine if factor A or factor B is significant.
- Given the output of a two factor replicated design and an anova output, be able to determine if there is significant interaction between the two factors.