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Statistical Methods for Analyzing Tree-Structured Microbiome Data
Microbiome datasets typically consist of an abundance matrix, a phylogenetic tree, and metadata about the samples. Although experimental methods and...
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Estimation of Discrete Survival Function through Modeling Diagnostic Accuracy for Mismeasured Outcome Data
Standard survival methods are inappropriate for mismeasured outcomes. Previous research has shown that outcome misclassification can bias estimation...
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Statistical Methods for Pairwise Comparison of Metagenomic Samples
Next generation sequencing (NGS) technologies make it possible to sequence a large number of metagenomes economically and efficiently using either...
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Statistical Inference Using the Three-Parameter Generalized von Mises Distribution and Outlier Detection Method for Asymmetrically Distributed Circular Data
It is well known that circular data are rarely symmetrically distributed; therefore, symmetric distributions such as von Mises and wrapped Cauchy...
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Initializing k-means Clustering by Bootstrap and Data Depth
The k -means algorithm is widely used in various research fields because of its fast convergence to the cost function minima; however, it frequently...
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A partial least squares approach for function-on-function interaction regression
A partial least squares regression is proposed for estimating the function-on-function regression model where a functional response and multiple...
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Statistical Design of Experiments (DoE)
In a cause–effect relationship, the design of experiments (DoE) is a means and method of determining the interrelationship in the required accuracy...
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The Halfspace Depth Characterization Problem
The halfspace depth characterization conjecture states that for any two distinct (probability) measures P and Q in the d-dimensional Euclidean space,...
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Specialised Statistical Procedures
In this chapter, we explore more specialised statistical procedures as well as a fundamental concept, Bayesian statistical inference. The procedures...
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Comparing Groups: Statistical Tests
In Chap. 5 we saw how to break out data by groups and inspect them with tables and charts. In this chapter we continue our discussion and address...
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How Statistics Helps to Reduce Rejects
No company likes to produce defective goods (rejects). The Six Sigma method is a recognized statistical approach that helps to reduce reject rates....
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Other Commonly Used Statistical Procedures
In this chapter, we explore some other commonly used but less ‘traditional’ statistical procedures. While these procedures are commonly reported in...
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Statistical Learning as a Regression Problem
This chapter makes four introductory points: (1) regression analysis is defined by the conditional distribution of Y |X, not by a conventional linear...
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Difference Hypotheses for Up to Two Means: t-Tests
The t-test is one the most widely used statistical tests and it allows for testing difference hypotheses for up to two means. Strictly speaking, it...
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Correlation and Regression
The test procedures introduced across the preceding chapters were tailored to testing difference hypotheses. This chapter turns to the complementary...
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Introduction
Images are common in our lives. They come as simple photographs or as the result of various medical, technical, or scientific experiments and are...
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Decision Errors, Effect Sizes, and Power
Although researchers often aim to observe significant results, this chapter will show that the mere significance of a test does not necessarily yield...
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Purely Sequential Minimum Risk Point Estimation (MRPE) for a Survival Function in an Exponential Distribution: Illustration with Remission Times for Bladder Cancer Patients
A purely sequential minimum risk point estimation (MRPE) methodology with an associated stop** time N is designed to develop an appropriate...
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Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing
This chapter explains how to find the 95% confidence interval about the mean for a set of data, and how to test hypotheses about your data using this...
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Pseudo-value regression trees
This paper presents a semi-parametric modeling technique for estimating the survival function from a set of right-censored time-to-event data. Our...
