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دسته بندی: ریاضیات ویرایش: نویسندگان: Adedeji B. Badiru سری: Systems Innovation Book Series ISBN (شابک) : 2020033885, 9781003083146 ناشر: CRC Press سال نشر: 2020 تعداد صفحات: 273 زبان: English فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود) حجم فایل: 7 مگابایت
در صورت تبدیل فایل کتاب Data Analytics: Handbook of Formulas and Techniques به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب تجزیه و تحلیل داده ها: کتابچه راهنمای فرمول ها و روش ها نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
تجزیه و تحلیل خوب داده ها اساس تصمیم گیری های موثر است. هر کسی که داده ها را در اختیار داشته باشد، می تواند اطلاعات را به سرعت و به طور موثر برای تصمیم گیری های مربوط استخراج کند. فرض این کتاب راهنما این است که کاربران و توسعه دهندگان ابزار را با مجموعه ای مناسب از فرمول ها و تکنیک ها برای تجزیه و تحلیل داده ها توانمند کند و به عنوان یک مرجع سریع برای نگه داشتن فرمول های مربوطه در دسترس خوانندگان باشد. این کتاب راهنما شامل فرمول هایی است که برای خوانندگان متمایل به ریاضی جذاب خواهد بود. در مورد چگونگی استفاده از تجزیه و تحلیل داده ها برای بهبود تصمیم گیری بحث می کند و برای کسانی که تازه از تجزیه و تحلیل داده استفاده می کنند ایده آل است تا نشان دهد چگونه افق استفاده خود را گسترش دهند. تکنیکهای کمی برای مدلسازی بیماریهای همهگیر مانند COVID-19 ارائه میکند. همچنین به مجموعه ابزارهای ریاضی برای حوزه های فنی نوظهور اضافه می کند. این کتاب راهنمای مفیدی برای محققان، پزشکان، مربیان و دانشجویان در زمینه هایی مانند مهندسی صنایع، مهندسی تولید، مدیریت پروژه، مهندسی عمران، مهندسی مکانیک، مدیریت فناوری و مدیریت کسب و کار در سراسر جهان است.
Good data analytics is the basis for effective decisions. Whoever has the data, has the ability to extract information promptly and effectively to make pertinent decisions. The premise of this handbook is to empower users and tool developers with the appropriate collection of formulas and techniques for data analytics and to serve as a quick reference to keep pertinent formulas within fingertip reach of readers. This handbook includes formulas that will appeal to mathematically inclined readers. It discusses how to use data analytics to improve decision-making and is ideal for those new to using data analytics to show how to expand their usage horizon. It provides quantitative techniques for modeling pandemics, such as COVID-19. It also adds to the suite of mathematical tools for emerging technical areas. This handbook is a handy reference for researchers, practitioners, educators, and students in areas such as industrial engineering, production engineering, project management, civil engineering, mechanical engineering, technology management, and business management worldwide.
Cover Half Title Series Page Title Page Copyright Page Dedication Table of Contents Preface Acknowledgments Author Chapter 1 Essentials of Data Analytics Introduction to COVID-19 Data Analytics Systems View of Data Analytics Global Growth of Data Analytics Background in Predictive Analytics Data Modeling Approaches Data Fanaticism Data and Measurements for Data Analytics What is Measurement? Data Measurement Systems Fundamental Scientific Equations Einstein’s Equation Einstein’s Field Equation Heisenberg’s Uncertainty Principle Schrödinger Equation Dirac Equation Maxwell’s Equations Boltzmann’s Equation for Entropy Planck–Einstein Equation Planck’s Blackbody Radiation Formula Hawking Equation for Black Hole Temperature Navier–Stokes Equation for a Fluid Lagrangian for Quantum Chromodynamics Bardeen–Cooper–Schrieffer Equation for Superconductivity Josephson Effect Fermat’s Last Theorem Methods for Data Measurement and Comparison Direct Comparison Indirect Comparison Data Measurement Scales Nominal Scale of Measurement Ordinal Scale of Measurement Interval Scale of Measurement Ratio Scale Measurement Reference Units of Measurements Common Constants Numeric Data Representation The Language of Data Analytics Quick Reference for Mathematical Equations Reference Chapter 2 Empirical Model Building Introduction to the Model Environment State-Space Modeling Calculus Reference for Data Analytics Integration Rules Solving Integrals with Variable Substitution Riemann Integral Integration by Parts Compound Functions Where the Inner Function is ax Integration by Parts Systems Modeling for Data Analytics Triple C Questions Communication Cooperation Coordination Conflict Resolution in Data Analytics References Chapter 3 Data Visualization Methods Introduction to Data Visualization Case Example of “Covidvisualizer” Website Dynamism and Volatility of Data Data Determination and Collection Choosing the Data Collecting the Data Relevance Check Limit Check Critical Value Coding the Data Processing the Data Control Total Consistency Check Scales of Measurement Using the Information Data Exploitation Raw Data Total Revenue Average Revenue Median Revenue Quartiles and Percentiles The Mode Range of Revenue Average Deviation Sample Variance Standard Deviation Chapter 4 Basic Mathematical Calculations for Data Analytics Introduction to Calculation for Data Analytics Quadratic Equation Overall Mean Chebyshev’s Theorem Permutations Combinations Failure Probability Distribution Probability Distribution Function Expected Value Variance Binomial Distribution Poisson Distribution Mean of a Binomial Distribution Variance Normal Distribution Cumulative Distribution Function Population Mean Standard Error of the Mean t-Distribution Chi-Squared Distribution Definition of Set and Notation Set Terms and Symbols Venn Diagrams Operations on Sets De Morgan’s Laws Probability Terminology Basic Probability Principles Random Variable Mean Value xˆ or Expected Value Series Expansions Mathematical Signs and Symbols Greek Alphabet Algebra Laws of Algebraic Operations Special Products and Factors Powers and Roots Proportion Arithmetic Mean of n Quantities A Geometric Mean of n Quantities G Harmonic Mean of n Quantities H Generalized Mean Solution of Quadratic Equations Solution of Cubic Equations Trigonometric Solution of the Cubic Equation Solution of Quadratic Equations Partial Fractions Non-repeated Linear Factors Repeated Linear Factors General Terms Repeated Linear Factors Factors of Higher Degree Geometry Triangles Right Triangle Equilateral Triangle General Triangle Menelaus’s Theorem Ceva’s Theorem Quadrilaterals Rectangle Parallelogram Rhombus Trapezoid General Quadrilateral Regular Polygon of n Sides Each of Length b Regular Polygon of n Sides Inscribed in a Circle of Radius r Regular Polygon of n Sides Circumscribing a Circle of Radius r Cyclic Quadrilateral Prolemy’s Theorem Cyclic-Inscriptable Quadrilateral Planar Areas by Approximation Trapezoidal Rule Durand’s Rule Simpson’s Rule (n even) Weddle’s Rule (n = 6) Solids Bounded by Planes Cube Rectangular Parallelepiped (or Box) Prism Pyramid Prismatoid Regular Polyhedra Sphere of Radius r Right Circular Cylinder of Radius r and Height h Circular Cylinder of Radius r and Slant Height l Cylinder of Cross-Sectional Area A and Slant Height l Right Circular Cone of Radius r and Height h Spherical Cap of Radius rand Height h Frustum of Right Circular Cone of Radii a, b and Height h Zone and Segment of Two Bases Lune Spherical Sector Spherical Triangle and Polygon Spheroids Ellipsoid Oblate Spheroid Prolate Spheroid Circular Torus Formulas from Plane Analytic Geometry Distance d between Two Points Slope m of Line Joining Two Points Equation of Line Joining Two Points Equation of Line in Terms of x Intercept a ≠ 0 and y intercept b ≠ 0 Normal Form for Equation of Line General Equation of Line Distance from Point (x[sub(1)], y[sub(1)]) to Line Ax + By + C = 0 Angle ψ between Two Lines Having Slopes m[sub(1)] and m[sub(2)] Area of Triangle with Verticles Transformation of Coordinates Involving Pure Translation Transformation of Coordinates Involving Pure Rotation Transformation of Coordinates Involving Translation and Rotation Polar Coordinates (r,θ) Plane Curves Catenary, Hyperbolic Cosine Cardioid Circle Cassinian Curves Cotangent Curve Cubical Parabola Cosecant Curve Cosine Curve Ellipse Gamma Function Hyperbolic Functions Inverse Cosine Curve Inverse Sine Curve Inverse Tangent Curve Logarithmic Curve Parabola Cubical Parabola Tangent Curve Ellipsoid Elliptic Cone Elliptic Cylinder Hyperboloid of One Sheet Elliptic Paraboloid Hyperboloid of Two Sheets Hyperbolic Paraboloid Sphere Distance d between Two Points Equations of Line Joining P[sub(1)](x[sub(1)], y[sub(1)], z[sub(1)]) and P[sub(2)](x[sub(2)], y[sub(2)], z[sub(2)]) in Standard Form Equations of Line Joining P[sub(1)](x[sub(1)], y[sub(1)],z[sub(1)]) and P[sub(2)](x[sub(2)], y[sub(2)], z[sub(2)]) in Parametric Form Angle between Two Lines with Direction Cosines General Equation of a Plane Equation of Plane Passing through Points Equation of Plane in Intercept Form Equations of Line through (x[sub(0)], y[sub(0)], z[sub(0)]) and Perpendicular to Plane Distance from Point (x, y, z) to Plane Ax + By + D= 0 Normal form for Equation of Plane Transformation of Coordinates Involving Pure Translation Transformation of Coordinates Involving Pure Rotation Transformation of Coordinates Involving Translation and Rotation Cylindrical Coordinates (r, θ, z) Spherical Coordinates (r, θ, φ) Logarithmic Identities Special Values Logarithms to General Base Series Expansions Limiting Values Inequalities Continued Fractions Polynomial Approximations Fundamental Properties Definition of General Powers Logarithmic and Exponential Functions Polynomial Approximations Slopes Trigonometric Ratios Sine Law Cosine Law Algebra Expanding Factoring Roots of Quadratic Law of Exponents Logarithms Chapter 5 Statistical Methods for Data Analytics Introduction Discrete Distributions Bernoulli Distribution Beta Binomial Distribution Beta Pascal Distribution Binomial Distribution Discrete Weibull Distribution Geometric Distribution Hypergeometric Distribution Negative Binomial Distribution Poisson Distribution Rectangular (Discrete Uniform) Distribution Continuous Distributions Arcsin Distribution Beta Distribution Cauchy Distribution Chi Distribution Chi-Square Distribution Erlang Distribution Exponential Distribution Extreme-Value Distribution F Distribution Gamma Distribution Half-Normal Distribution Laplace (Double Exponential) Distribution Logistic Distribution Lognormal Distribution Noncentral Chi-Square Distribution Noncentral F Distribution Noncentral t Distribution Normal Distribution Pareto Distribution Rayleigh Distribution t Distribution Triangular Distribution Uniform Distribution Weibull Distribution Distribution Parameters Average Variance Standard Deviation Standard Error Skewness Standardized Skewness Kurtosis Standardized Kurtosis Weighted Average Estimation and Testing 100(1 − α)% Confidence Interval for Mean 100(1 − α)% Confidence Interval for Variance 100(1 − α)% Confidence Interval for Difference in Means Equal Variance Unequal Variance 100(1 − α)% Confidence Interval for ratio of variances Normal Probability Plot Comparison of Poisson Rates Distribution Functions and Parameter Estimation Bernoulli Binomial Discrete Uniform Geometric Negative Binomial Poisson Beta Chi-Square Erlang Exponential F Gamma Lognormal System Displays Normal Student’s t Triangular Uniform Weibull Chi-Square Test for Distribution Fitting Kolmogorov–Smirnov Test ANOVA (Analysis of Variance) Notations Standard Error (Internal) Standard Error (Pooled) Interval Estimates Tukey Interval Scheffe Interval Cochran C-Test Bartlett Test Hartley’s Test Kruskal–Wallis Test Freidman Test Regression Notations Regression Statistics Predictions Nonlinear Regression Ridge Regression Quality Control Subgroup Statistics X-Bar Charts Capability Ratios R Charts S Charts C Charts U Charts P Charts NP Charts CuSum Chart for the Mean Multivariate Control Charts Time Series Analysis Notations Autocorrelation at Lag k Partial Autocorrelation at Lag k Cross-Correlation at Lag k Box-Cox Periodogram (Computed Using Fast Fourier Transform) Categorical Analysis Notations Totals Chi-Square Fisher’s Exact Test Lambda Uncertainty Coefficient Somer’s D Eta Contingency Coefficient Cramer’s V Conditional Gamma Pearson’s r Kendall’s Tau b Tau C Probability Terminology Basic Probability Principles Random Variable Mean Value x or Expected Value μ Discrete Distribution Formulas Bernoulli Distribution Beta Binomial Distribution Beta Pascal Distribution Binomial Distribution Discrete Weibull Distribution Geometric Distribution Hypergeometric Distribution Negative Binomial Distribution Poisson Distribution Rectangular (Discrete Uniform) Distribution Continuous Distribution Formulas Arcsin Distribution Beta Distribution Cauchy Distribution Chi Distribution Chi-Square Distribution Erlang Distribution Exponential Distribution Extreme-Value Distribution F Distribution Gamma Distribution Half-Normal Distribution Laplace (Double Exponential) Distribution Logistic Distribution Lognormal Distribution Noncentral Chi-Square Distribution Noncentral F Distribution Noncentral t Distribution Normal Distribution Pareto Distribution Rayleigh Distribution t Distribution Triangular Distribution Uniform Distribution Weibull Distribution Variate Generation Techniques Reference Chapter 6 Descriptive Statistics for Data Presentation Introduction Sample Average Sample Variance Sample Standard Deviation Sample Standard Error of the Mean Skewness Standardized Skewness Kurtosis Standardized Kurtosis Weighted Average Estimation and Testing 100(1 − α)% Confidence Interval for Mean 100(1 − α)% Confidence Interval for Variance 100(1 − α)% Confidence Interval for Difference in Means For Equal Variance For Unequal Variance 100(1 − α)% Confidence Interval for Ratio of Variances Normal Probability Plot Comparison of Poisson Rates Distribution functions and Parameter Estimation Bernoulli Distribution Binomial Distribution Discrete Uniform Distribution Geometric Distribution Negative Binomial Distribution Poisson Distribution Beta Distribution Chi-Square Distribution Erlang Distribution Exponential Distribution F Distribution Gamma Distribution Lognormal Distribution Normal Distribution Student’s t Triangular Distribution Uniform Distribution Weibull Distribution Chi-Square Test for Distribution Fitting Kolmogorov–Smirnov Test ANOVA (Analysis of Variance) Notations Standard Error Interval Estimates Tukey Interval Scheffe Interval Cochran C-test Bartlett Test Hartley’s Test Kruskal–Wallis Test Freidman Test Regression Notations Statistical Quality Control Subgroup Statistics X-Bar Charts Capability Ratios R Charts S Charts C Charts U Charts P Charts NP Charts CuSum Chart for the Mean Time Series Analysis Notations Autocorrelation at Lag k Partial Autocorrelation at Lag k Cross-Correlation at Lag k Box-Cox Computation Periodogram (Computed Using Fast Fourier Transform) Categorical Analysis Notations Totals Chi-Square Lambda Uncertainty Coefficient Somer’s D Measure Eta Contingency Coefficient Cramer’s V Measure Conditional Gamma Pearson’s r Measure Kendall’s Tau b Measure Tau C Measure Overall Mean Chebyshev’s Theorem Per mutation Combination Failure Chapter 7 Data Analytics Tools for Understanding Random Field Regression Models Introduction RFR Models Two Examples Bayesian Regression Models and Random Fields Data Analysis: Finding the Associated Regression Model Relating Eigenvectors to Regression Functions Some Special Random Field Models Gaussian Covariance as Damped Polynomial Regression Trigonometric Regression and Spline Covariance Discussion References Chapter 8 Application of DEJI Systems Model to Data Integration Introduction to Data Integration Leveraging the Input-Control-Output-Mechanism Model Data Types and Fidelity Data Collection and Sanitization DEJI Systems Model for Data Quality Data Value Model Data Quality Control References Index