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SEMATECH e-Handbook of Statistical Methods

SEMATECH e-Handbook of Statistical Methods

http://www.itl.nist.gov/div898/handbook/

Related:  R ResourcesDoE

Learning Statistics on Youtube Youtube.com is the second most accessed website in the world (surpassed only by its parent, google.com). It has a whopping 1 billion unique views a month. [1, 2] It is a force to be reckoned with. In the video sharing platform, there are many brilliant and hard-working content creators producing high-quality and free educational videos that students and academics alike can enjoy. I made a survey on Youtube content that could be useful for those interested in learning Statistics, and I listed and categorized them below. Truth be told, this post is a glorified Google search in many respects.

Design of Experiments (DOE) Tutorial Design of experiments (DOE) is a powerful tool that can be used in a variety of experimental situations. DOE allows for multiple input factors to be manipulated determining their effect on a desired output (response). By manipulating multiple inputs at the same time, DOE can identify important interactions that may be missed when experimenting with one factor at a time. All possible combinations can be investigated (full factorial) or only a portion of the possible combinations (fractional factorial). Fractional factorials will not be discussed here. When to Use DOE

Basic Steps of Applying Reliability Centered Maintenance (RCM) Part II Basic Steps of Applying Reliability Centered Maintenance (RCM) Part II Although there is a great deal of variation in the application of Reliability Centered Maintenance (RCM), most procedures include some or all of the seven steps shown below: Prepare for the Analysis Select the Equipment to Be Analyzed Identify Functions Identify Functional Failures Identify and Evaluate (Categorize) the Effects of Failure Identify the Causes of Failure Select Maintenance Tasks If we were to group the seven steps into three major blocks, these blocks would be: DEFINE (Steps 1, 2 and 3) ANALYZE (Steps 4, 5 and 6) ACT (Step 7) The previous issue of Reliability HotWire discussed the DEFINE stage.

The PValues Data Table The PValues data table contains a row for each pair of Y and X variables. If you specified a column for Group, the PValues data table contains a first column called Group. A row appears for each level of the Group column and for each pair of Y and X variables. The PValues data table also contains a table variable called Original Data that gives the name of the data table that was used for the analysis. If you specified a By variable, JMP creates a PValues table for each level of the By variable, and the Original Data variable gives the By variable and its level. PValues Data Table, Partial View shows the PValues data table created using the Probe.jmp sample data table. Exploratory data analysis In statistics, exploratory data analysis (EDA) is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis testing task. Exploratory data analysis was promoted by John Tukey to encourage statisticians to explore the data, and possibly formulate hypotheses that could lead to new data collection and experiments. EDA is different from initial data analysis (IDA),[1] which focuses more narrowly on checking assumptions required for model fitting and hypothesis testing, and handling missing values and making transformations of variables as needed.

Reliability Centered Maintenance (RCM) An Overview of Basic Concepts Reliability Centered Maintenance (RCM) analysis provides a structured framework for analyzing the functions and potential failures for a physical asset (such as an airplane, a manufacturing production line, etc.) with a focus on preserving system functions, rather than preserving equipment. RCM is used to develop scheduled maintenance plans that will provide an acceptable level of operability, with an acceptable level of risk, in an efficient and cost-effective manner. According to the SAE JA1011 standard, which describes the minimum criteria that a process must comply with to be called "RCM," a Reliability Centered Maintenance Process answers the following seven questions: What are the functions and associated desired standards of performance of the asset in its present operating context (functions)? In what ways can it fail to fulfill its functions (functional failures)?

Books I like If you’re serious about learning, you probably need to read a book at some point. These days if you want to learn applied statistics and data science tools, you have amazing options in the form of blogs, Q&A sites, and massive open online courses and even videos on You Tube. Wikipedia is also an amazing reference resource on statistics. What Can Classical Chinese Poetry Teach Us About Graphical Analysis? - Statistics and Quality Data Analysis A famous classical Chinese poem from the Song dynasty describes the views of a mist-covered mountain called Lushan. The poem was inscribed on the wall of a Buddhist monastery by Su Shi, a renowned poet, artist, and calligrapher of the 11th century. Deceptively simple, the poem captures the illusory nature of human perception. Written on the Wall of West Forest Temple --Su Shi From the side, it's a mountain ridge. Looking up, it's a single peak.

Introduction to the Temperature-Humidity Relationship Introduction to the Temperature-Humidity Relationship When performing accelerated life testing analysis, a life distribution and a life-stress relationship are required. The temperature-humidity (T-H) relationship, a variation of the Eyring relationship, has been proposed for predicting the life at use conditions when temperature and humidity are the accelerated stresses in a test. This combination model is given by: where: Two meanings of priors, part I: The plausibility of models by Angelika Stefan & Felix Schönbrodt When reading about Bayesian statistics, you regularly come across terms like “objective priors“, “prior odds”, “prior distribution”, and “normal prior”. However, it may not be intuitively clear that the meaning of “prior” differs in these terms.

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