Measure - Six Sigma Data Classification, Sampling and Collection

Discrete Data

information that can be categorized into a classification. Discrete data is based on counts. Only a finite number of values is possible, and the values cannot be subdivided meaningfully. For example, the number of parts damaged in shipment. Ex. The number of times customers leave positive feedback The people who have access to sensitive company information

Continuous data

information that can be measured on a continuum or scale. Continuous data can have almost any numeric value and can be meaningfully subdivided into finer and finer increments, depending upon the precision of the measurement system. Ex.. The time it takes to serve coffee The range of temperatures comfortable at a restaurant

Which principles should you follow when collecting data samples?

Collect a sample that's big enough to detect trends Ensure that the sample represents the entire population you're studying Ensure that the sample is free from bias

Online analytical processing (OLAP)

It uses relational database to analyze data from multiple prespectives

Data Mining

It uses relational database to discover patterns in large datasets It transforms extracted data into information for process improvement

Data warehousing

Metadata is used to provide operational feedback data is collected as metadata from the source system

Match the levels of measurements to thier characteristics

Ordinal - Variables are ranked relative to each other and the distance between ranks is not indicated Ratio - The variables have a fixed 0 point and can be compared using percentages Nominal - Variables are discrete but not placed in a particular order Interval - The distance between ranks is equal and there are no absolute 0s

Which best practices should you follow when collecting data?

Provide people with complete training on the process Use an appropriate error correction system for digitally stored data Maintain accurate data collection tools Record the before and after values for variables to change over time Record the order in which data was collected Record classification identification information during data collection

Best sampling method for finding the standard deviation for tshirt deminsions within particular production lines as well as between production lines

Rational sampling

Rational Sampling

The population is divided into groups Typically used to collect realtime data from process operations Helpful for calculating standard deviations

Stratified sampling

The population is divided into groups the size of each group in the sample is proportional to it's size in the population The population groups should be proportionately reflected in the sample Population is diverse

What are some considerations to make when developing your data collection plan

Tools and teams involved in collecting the data Data source for collecting best data That the right data is being collected the purpose and goals of data collection

Qualitative

relating to, measuring, or measured by the quality of something rather than its quantity.

Quantitative

relating to, measuring, or measured by the quantity of something rather than its quality.

Systemactic Sampling

Every "nth" unit is sampled It's typically used to collect realtime data from process operations

You want to find out which t-shirt size sells the most. Which type of data will you collect?

Discrete data

Simple random sampling

Each unit had an equal chance of selection You have an accurate database of the population and no interviews are required