Download Analyzing and Interpreting Continuous Data Using JMP:: A by Jose G. Ramirez Ph.D., Brenda S. Ramirez M.S. PDF

By Jose G. Ramirez Ph.D., Brenda S. Ramirez M.S.

In accordance with real-world functions, studying and analyzing non-stop facts utilizing JMP: A step by step advisor, by means of Jose Ramirez, Ph.D., and Brenda S. Ramirez, M.S., combines statistical directions with a robust and renowned software program platform to unravel universal difficulties in engineering and technology. within the many case reports supplied, the authors basically arrange the matter, clarify how the information have been amassed, convey the research utilizing JMP, interpret the output in a basic method, after which draw conclusions and make strategies. This step by step layout allows clients new to stats or JMP to benefit as they cross, however the publication can be worthy to these with a few familiarity with statistics and JMP. The booklet contains a foreword written by way of Professor Douglas C. Montgomery.

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Extra info for Analyzing and Interpreting Continuous Data Using JMP:: A Step-by-Step Guide

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Continuous or attribute. 4 Common Graphical Displays for Continuous Data Graph Name Graph Description Histogram A frequency distribution of data that shows the shape, center, spread, and outliers in a data sample. When the histogram is overlaid with specification limits, we can see how much room we have to move within the specifications. The number of bars in the histogram should be approximately 1 + Log2 (sample size). Trend Plot A plot that is easily constructed by plotting our measurements in a time order, with the response on the y-axis and time on the x-axis, and connecting the points with a line.

The underlying population must be normally distributed, or close to normally distributed, the data are homogeneous, and the experimental units must be independent from each other. The second type of statistics typographical convention that the reader will encounter is a callout box, like the one below. The information in the callout box is a snippet of a key point that is presented in the main text of the chapter. They are intended to be short and memorable. A p-value is an area under a probability density curve that quantifies the likelihood of observing a test statistic as large as, or larger than, the one obtained from the data.

There may be more than one mode. Count the occurrences for all unique data values. The mode has the largest number of occurrences. 3 (continued) Property Spread Center and Spread Summary Statistic Description Range The difference between the maximum and minimum values in the data. This estimate is usually affected by outliers. Standard deviation Square root of the average squared distance from the data points to the mean—its radius of rotation around the mean. Most data falls in the interval of mean ± 3s.

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