Digital Signal Processing : a Practical Guide for Engineers and Scientists. by Smith, Steven W., ProQuest Ebook Subscriptions

Table of Contents: “…Statistics, Probability and Noise; Signal and Graph Terminology; Mean and Standard Deviation; Signal vs. Underlying Process; The Histogram, Pmf and Pdf; The Normal Distribution; Digital Noise Generation; Precision and Accuracy; Chapter 3. …”
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F♯ for quantitative finance : an introductory guide to utilizing F♯ for quantitative finance leveraging the .NET platform / by Astborg, Johan, Safari Books Online

Table of Contents: “…Floating-point numbersThe IEEE 754 floating-point standard; Learning about numerical types in F♯; Arithmetic operators; Learning about arithmetic comparisons; Math operators; Conversion functions; Introducing statistics; Aggregate statistics; Calculating the sum of a sequence; Calculating the average of a sequence; Calculating the minimum of a sequence; Calculating the maximum of a sequence; Calculating the variance and standard deviation of a sequence; Looking at an example application; Using the Math.NET library; Installing the Math.NET library; Introduction to random number generation.…”
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The Question of Meter in Biblical Hebrew Poetry. by Vance, Donald R., PALCI EBSCO books

Table of Contents: “…Accentual Meter: BeowulfAccentual- Syllabic Meter: Shakespeare's Sonnets (I-X); The NonMeterical Control; Birth of Moses (Exod 2:1-10); Ruth 1; Summary; The Texts; Words and Accents; Syllabification and Vocalization; Lamentations 1; Lamentations 2; Lamentations 3; Lamentations 4; Lamentations 5; A Worthy Woman (Prov 31:10-31); Psalm 25; Psalm 34; Psalm 37; Psalm 111; Psalm 112; Psalm 119; Psalm 145; David's Lament over Saul and Jonathan (2 Sam 1:19-27); Conclusions; Regularity; Standard Deviation; Range; Relative Frequency Distribution Histograms; Excursus: Qinah Meter; Chapter 4: Conclusions.…”
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A functional approach to educational research methods and statistics : qualitative, quantitative, and mixed methods approaches / by Ayiro, Laban P., PALCI EBSCO books

Table of Contents: “…Measures of VariabilityComputing the Standard Deviation in SPSS; Computing Correlation Coefficients; A Determined Effort: squaring the correlation coefficient!!…”
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Introduction to statistical methods in pathology by Momeni, Amir, SpringerLink (Online service)

Table of Contents: “…Preface; Contents; Chapter 1: Why Every Pathologist Needs to Know Statistics; Introduction; Outcomes and Variables in Pathology and Laboratory Medicine; Components of a Useful Diagnostic Test; Examples; Defining Test Objectives; Summary; References; Chapter 2: Assessing Diagnostic Tests; Technical Accuracy and Precision; Error; Standard Deviation; Confidence Interval; Calculating Reference Intervals; Calculating Sample Size for Reference Interval Estimation; Diagnostic Accuracy and Testing for Accuracy; Sensitivity and Specificity; Predictive Values; Receiver Operating Characteristic Curve…”
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Principles of programming & coding / by PALCI EBSCO books

Table of Contents: “…3D printing -- Algorithms -- American Standard Code for Information -- Interchange (ASCII) -- Android OS -- Application -- Autonomic computing -- Avatars and simulation -- Binary hexadecimal representations -- Boolean operators -- Branching logic -- Characters and strings -- Cloud computing -- Coding and encryption -- Color coding -- Combinatorics -- Comment programming -- Comparison operators -- Computer animation -- Computer memory -- Computer modeling -- Computer security -- Computer-aided design (CAD) -- Computer-aided design and computer-aided manufacturing software (CAD/CAM) -- Computer-assisted instruction (CAI) -- Conditional operators -- Constraint programming -- Control systems -- Cowboy coding -- CPU design -- Crowdfunding -- Crowdsourcing -- Cryptography -- Data mining -- Data warehouse -- Database design -- Database structuring conventions -- Debugging -- Device drivers -- Diffusion of innovations -- Digital divide -- Digital forensics -- Digital libraries -- Digital native -- Digital photography -- Digital signal processors (DSP) -- Digital watermarking -- Disk operating system (DOS) -- Drone warfare -- Drones -- E-banking -- E-learning -- Electronic circuits -- Electronic communication software -- Encryption -- Error handling -- Event-driven marketing (EDM) -- Expectancy theory -- Experimenter's bias -- Extreme programming -- Firewalls -- Firmware -- Functional electrical stimulation (FES) -- Game programming -- Gamification -- Graphical user interface (GUI) -- Graphics formats -- Guard clause -- HTTP cookie -- Imagined communities -- Incremental development -- Informational technology (IT) -- Information visualization -- Internet Protocol (IP) -- Inversion of control (Hollywood Principle) -- iOS -- Iterative constructs -- Java programming language -- JavaScript -- Knowledge worker -- Levels of processing theory -- Logic synthesis -- Logistics -- Machine learning -- Malware -- Massive open online course (MOOC) -- Meta-analysis -- Metacomputing -- Metadata -- Microprocessors -- Mixed methods research (MMR) -- Mobile apps -- Mobile technology -- Motherboards -- Multiprocessing operating systems (OS) -- Multi-user operating system (OS) -- Naming conventions -- Net neutrality -- Network security -- Neuro-linguistic programming (NLP) -- Neuromarketing -- Neuromorphic chips -- Objectivity -- Object-oriented design (OOD) -- Object-oriented programming (OOP) -- Privacy rights -- Programming languages -- Prototyping -- Quantum computing -- Random access memory (RAM) -- Rapid application development (RAD) -- Rational choice theory -- Search engine optimization (SEO) -- Semantic memory -- Semantics -- Signal processing -- Source code comments -- Spiral development -- Standard deviation -- Standpoint theory -- Statistical inference -- String-oriented symbolic languages (SNOBOL) -- Structural equation modeling (SEM) -- Technology in education -- Test doubles -- Theory of multiple intelligences -- Theory X and Theory Y -- Transformation priority premise (TPP) -- Tree structures -- Turing test -- Uncertainty reduction theory (URT) -- Unicode -- UNIX -- Variables and values -- Waterfall development -- Web design -- Web graphic design -- Working memory -- Worse-is-better -- Time Line of Inventions and Advancements in Programming and Coding.…”
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Mastering financial calculations : a step-by-step guide to the mathematics of financial market instruments / by Steiner, Bob, Safari Books Online

Table of Contents: “…Averages -- arithmetic & geometric means, weighted averages, median and mode -- Variance, standard deviation and volatility -- Correlation and covariance -- Histograms, probability density and the normal probability function -- Confidence levels and the normal probability table -- Exercises -- Part 2: Interest Rate Instruments -- The money market -- Overview -- Day/year conventions -- Money market instruments -- Money market calculations -- Discount instruments -- CDs paying more than one coupon -- Value dates -- Exercises -- Forward-forward interest rates and forward rate agreements (fras)…”
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Sexual behavior in the human male / by Kinsey, Alfred C. (Alfred Charles), 1894-1956, Pomeroy, Wardell B. (Wardell Baxter), 1913-2001, Martin, Clyde E. (Clyde Eugene), JSTOR

Table of Contents: “…Sample -- Statistical Analyses -- Individual frequencies -- Group frequencies -- Frequency curves -- Group Averages -- Means -- Standard deviation of the mean -- Medians -- Percents of individual outlet -- Percents of group outlet -- Correlation coefficients -- Accumulative incidence curves -- 4. …”
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Understanding Statistical Error : A Primer for Biologists. by Gierlinski, Marek, ProQuest Ebook Subscriptions

Table of Contents: “…-- 2.3 Mean, median, variance and standard deviation -- 2.4 Gaussian distribution -- 2.5 Central limit theorem -- 2.6 Log-normal distribution -- 2.7 Binomial distribution -- 2.8 Poisson distribution -- 2.9 Student's t-distribution -- 2.10 Exercises…”
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Quantitative and Statistical Research Methods : From Hypothesis to Results. by Martin, William E., ProQuest Ebook Subscriptions

Table of Contents: “…Intro -- Quantitative and Statistical Research Methods: From Hypothesis to Results -- Contents -- Tables and Figures -- Preface -- Acknowledgments -- The Authors -- Chapter 1: Introduction and Overview -- Review of Foundational Research Concepts -- Independent, Dependent, and Extraneous Variables -- Scales of Measurement of Variables -- Review of Foundational Statistical Information -- Measures of Central Tendency -- Measures of Variability (Dispersion) of Scores -- Variance of the Sample (s2) -- Standard Deviation of the Sample (s) -- Coefficient of Variation (C)…”
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Automation and computational intelligence for road maintenance and management : advances and applications / by Zakeri, Hamzeh, Nejad, Fereidoon Moghadas, Gandomi, Amir Hossein, Safari Books Online

Table of Contents: “…4.7.1 Examples of the Application of Fuzzy Methods in Infrastructure Management -- 4.8 Summary and Conclusion -- 4.9 Questions and Exercises -- Further Reading -- Chapter 5 Automatic Detection and Its Applications in Infrastructure -- 5.1 Introduction -- 5.1.1 Photometric Hypotheses (PH) -- 5.1.2 Geometric and Photometric Hypotheses (GPH) -- 5.1.3 Geometric Hypotheses (GH) -- 5.1.4 Transform Hypotheses (TH) -- 5.2 The Framework for Automatic Detection of Abnormalities in Infrastructure Images -- 5.2.1 Wavelet Method -- 5.2.2 High Amplitude Wavelet Coefficient Percentage (HAWCP) -- 5.2.3 High-Frequency Wavelet Energy Percentage (HFWEP) -- 5.2.4 Wavelet Standard Deviation (WSTD) -- 5.2.5 Moments of Wavelet -- 5.2.6 High Amplitude Shearlet Coefficient Percentage (HASHCP) -- 5.2.7 High-Frequency Shearlet Energy Percentage (HFSHEP) -- 5.2.8 Fractal Index -- 5.2.9 Moments of Complex Shearlet -- 5.2.10 Central Moments q -- 5.2.11 Hu Moments -- 5.2.12 Bamieh Moments -- 5.2.13 Zernike Moments -- 5.2.14 Statistic of Complex Shearlet -- 5.2.15 Contrast of Complex Shearlet -- 5.2.16 Correlation of Complex Shearlet -- 5.2.17 Uniformity of Complex Shearlet -- 5.2.18 Homogeneity of Complex Shearlet -- 5.2.19 Entropy of Complex Shearlet -- 5.2.20 Local Standard Deviation of Complex Shearlet Index (F_Local_STD) -- 5.3 Summary and Conclusion -- 5.4 Questions and Exercises -- Further Reading -- Chapter 6 Feature Extraction and Fragmentation Methods -- 6.1 Introduction -- 6.2 Low-Level Feature Extraction Methods -- 6.3 Shape-Based Feature (SBF) -- 6.3.1 Center of Gravity (COG) or Center of Area (COA) -- 6.3.2 Axis of Least Inertia (ALI) -- 6.3.3 Average Bending Energy -- 6.3.4 Eccentricity Index (ECI) -- 6.3.5 Circularity Ratio (CIR) -- 6.3.6 Ellipse Variance Feature (EVF) -- 6.3.7 Rectangularity Feature (REF) -- 6.3.8 Convexity Feature (COF).…”
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Machine learning with R : learn how to use R to apply powerful machine learning methods and gain an insight into real-world applications / by Lantz, Brett, Safari Books Online

Table of Contents: “…Measuring spread -- quartiles and the five-number summaryVisualizing numeric variables -- boxplots; Visualizing numeric variables -- histograms; Understanding numeric data -- uniform and normal distributions; Measuring spread -- variance and standard deviation; Exploring categorical variables; Measuring the central tendency -- the mode; Exploring relationships between variables; Visualizing relationships -- scatterplots; Examining relationships -- two-way cross-tabulations; Summary; Chapter 3: Lazy Learning -- Classification using Nearest Neighbors; Understanding classification using nearest neighbors.…”
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Blood donations : attitudes, safety and future directions / by PALCI EBSCO books

Table of Contents: “…Average and Range Charts; 6.2.3. Average and Standard Deviation Charts; 6.2.4. Interpreting Control Charts; 6.3. …”
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Machine learning with R : discover how to build machine learning algorithms, prepare data, and dig deep into data prediction techniques with R / by Lantz, Brett, Safari Books Online

Table of Contents: “…Measuring spread -- variance and standard deviationExploring categorical variables; Measuring the central tendency -- the mode; Exploring relationships between variables; Visualizing relationships -- scatterplots; Examining relationships -- two-way cross-tabulations; Summary; Chapter 3: Lazy Learning -- Classification Using Nearest Neighbors; Understanding nearest neighbor classification; The k-NN algorithm; Measuring similarity with distance; Choosing an appropriate k; Preparing data for use with k-NN; Why is the k-NN algorithm lazy?…”
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Advances on P2P, parallel, grid, cloud and Internet computing : proceedings of the 17th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC-2022)... by International Conference on P2P, Parallel, Grid, Cloud, and Internet Computing, SpringerLink (Online service)

Table of Contents: “…1 Introduction -- 2 Related Works -- 3 Experimentation Setup -- 3.1 Algorithm -- 3.2 Environment -- 4 Evaluation Results -- 4.1 Randomized Dataset -- 4.2 Directional Dataset -- 5 Conclusions and Future Work -- References -- An Approach to Orchestrating and Connecting Workloads Across Multi-clouds -- 1 Introduction -- 2 Orchestrators -- 3 Proposed Architecture -- 4 Experimental Environment -- 5 Test Results -- 5.1 Minimum and Average Latencies -- 5.2 Minimum and Maximum Latencies -- 5.3 Standard Deviation -- 5.4 Percentiles -- 6 Analysis of Results -- 7 Conclusion -- References…”
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Machine Learning with Python Cookbook : practical solutions from preprocessing to deep learning / by Gallatin, Kyle, Safari Books Online

Table of Contents: “…Solution -- Discussion -- 1.6 Describing a Matrix -- Problem -- Solution -- Discussion -- 1.7 Applying Functions over Each Element -- Problem -- Solution -- Discussion -- 1.8 Finding the Maximum and Minimum Values -- Problem -- Solution -- Discussion -- 1.9 Calculating the Average, Variance, and Standard Deviation -- Problem -- Solution -- Discussion -- 1.10 Reshaping Arrays -- Problem -- Solution -- Discussion -- 1.11 Transposing a Vector or Matrix -- Problem -- Solution -- Discussion -- 1.12 Flattening a Matrix -- Problem -- Solution -- Discussion -- 1.13 Finding the Rank of a Matrix -- Problem…”
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Analyzing Quantitative Data : An Introduction for Social Researchers. by Wetcher-Hendricks, Debra, ProQuest Ebook Subscriptions

Table of Contents: “…Basic Pie Chart -- Paneled Pie Charts -- 2.5 Conclusion -- Statistical Resources for SPSS -- Review Questions -- 3: Descriptive Statistics for Continuous Data -- 3.1 Introduction -- 3.2 Frequencies -- 3.2.1 Frequency Histograms -- Paneled Histograms -- Stacked Histograms -- Frequency Polygons -- 3.2.2 Stem-and-Leaf Charts -- 3.3 Measures of Central Tendency -- 3.3.1 Mean -- 3.3.2 Median -- 3.3.3 Mode -- 3.3.4 Deciding between Measures of Central Tendency -- 3.4 Measures of Dispersion -- 3.4.1 Maximum and Minimum -- 3.4.2 Range -- 3.4.3 Variance and Standard Deviation -- Basic Formulas…”
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Medical Statistics from Scratch : an Introduction for Health Professionals. by ProQuest Ebook Subscriptions

Table of Contents: “…-- Charting Nominal and Ordinal Data -- Charting Discrete Metric Data -- Charting Continuous Metric Data -- Charting Cumulative Data -- 4 Describing Data from its Shape -- Learning Objectives -- The Shape of Things to Come -- 5 Describing Data with Numeric Summary Values -- Learning Objectives -- Numbers R us -- Summary Measures of Location -- Summary Measures of Spread -- Standard Deviation and the Normal Distribution -- III Getting the Data -- 6 Doing it Right First Time -- Designing a Study -- Learning Objectives -- Hey ho! …”
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Data analytics : a theoretical and practical view from the EDISON Project / by Cuadrado-Gallego, Juan J., Demchenko, Yuri, SpringerLink (Online service)

Table of Contents: “…Theory -- 4.1 Introduction -- 4.2 Anomaly detection basic on Statistics -- 4.2.1 Anomaly detection Basic on the mean and the standard deviation -- 4.2.2 Anomaly detection based on the quartiles -- 4.2.3 Anomaly detection based errors of the residuals -- 4.3 Anomaly detection based on proximity. …”
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Security-related advanced technologies in critical infrastructure protection : theoretical and practical approach / by NATO Advanced Research Workshop on Security-Related Advanced Technologies in Critical Infrastructure Protection Budapest, Hungary, SpringerLink (Online service)

Table of Contents: “…2.3 Dynamic Behavior of Energy-Absorbing Building Materials -- 2.4 Evaluation Indexes of Energy Absorption -- 2.5 Conclusion -- References -- Chapter 3: A Method for Approximating Circular Error Probable -- 3.1 Introduction -- 3.2 Methods for Deriving CEP -- 3.2.1 Stochastic Approximation -- 3.3 Approximation CEP by SA -- 3.3.1 The Ratio of Standard Deviations in CEP Estimation -- 3.4 Numerical Analysis -- 3.5 Summary -- References -- Chapter 4: Machine Learning Aspects of Internet Firewall Data -- 4.1 Introduction -- 4.2 Modeling Network Firewall Rules by Neural Network…”
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