{"product_id":"symbolic-mathematics-for-chemists-isbn-9781118798690","title":"Symbolic Mathematics for Chemists","description":"\u003cp\u003e\u003cb\u003eAn essential guide to using Maxima, a popular open source symbolic mathematics engine to solve problems, build models, analyze data and explore fundamental concepts\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eSymbolic Mathematics for Chemists\u003c\/i\u003e offers students of chemistry a guide to Maxima, a popular open source symbolic mathematics engine that can be used to solve problems, build models, analyze data, and explore fundamental chemistry concepts. The author — a noted expert in the field — focuses on the analysis of experimental data obtained in a laboratory setting and the fitting of data and modeling experiments. The text contains a wide variety of illustrative examples and applications in physical chemistry, quantitative analysis and instrumental techniques.\u003c\/p\u003e \u003cp\u003eDesigned as a practical resource, the book is organized around a series of worksheets that are provided in a companion website. Each worksheet has clearly defined goals and learning objectives and a detailed abstract that provides motivation and context for the material. This important resource:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eOffers an text that shows how to use popular symbolic mathematics engines to solve problems\u003c\/li\u003e \u003cli\u003eIncludes a series of worksheet that are prepared in Maxima\u003c\/li\u003e \u003cli\u003eContains step-by-step instructions written in clear terms and includes illustrative examples to enhance critical thinking, creative problem solving and the ability to connect concepts in chemistry\u003c\/li\u003e \u003cli\u003eOffers hints and case studies that help to master the basics while proficient users are offered more advanced avenues for exploration \u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eWritten for advanced undergraduate and graduate students in chemistry and instructors looking to enhance their lecture or lab course with symbolic mathematics materials, \u003ci\u003eSymbolic Mathematics for Chemists: A Guide for Maxima Users\u003c\/i\u003e is an essential resource for solving and exploring quantitative problems in chemistry.\u003c\/p\u003e \u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Fundamentals \u003c\/b\u003e\u003cb\u003e1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Getting Started With wxMaxima 1\u003c\/p\u003e \u003cp\u003e1.1.1 Input Cells 2\u003c\/p\u003e \u003cp\u003e1.1.2 The Toolbar 3\u003c\/p\u003e \u003cp\u003e1.1.3 The Menus 3\u003c\/p\u003e \u003cp\u003e1.1.4 Command History 4\u003c\/p\u003e \u003cp\u003e1.1.5 Basic Arithmetic 5\u003c\/p\u003e \u003cp\u003e1.1.6 Mathematical Functions 7\u003c\/p\u003e \u003cp\u003e1.1.7 Assigning Variables 8\u003c\/p\u003e \u003cp\u003e1.1.8 Defining Functions 10\u003c\/p\u003e \u003cp\u003e1.1.9 Comments, Images, and Sectioning 12\u003c\/p\u003e \u003cp\u003e1.2 A Tour of the General Math Pane 12\u003c\/p\u003e \u003cp\u003e1.2.1 Basic Plotting 13\u003c\/p\u003e \u003cp\u003e1.2.1.1 Plotting Multiple Curves 14\u003c\/p\u003e \u003cp\u003e1.2.1.2 Parametric Plots 15\u003c\/p\u003e \u003cp\u003e1.2.1.3 Discrete Plots 15\u003c\/p\u003e \u003cp\u003e1.2.1.4 Three-Dimensional Plots 17\u003c\/p\u003e \u003cp\u003e1.2.2 Basic Algebra 18\u003c\/p\u003e \u003cp\u003e1.2.2.1 Equations 18\u003c\/p\u003e \u003cp\u003e1.2.2.2 Substitutions 18\u003c\/p\u003e \u003cp\u003e1.2.2.3 Simplification 20\u003c\/p\u003e \u003cp\u003e1.2.2.4 Solving Equations 21\u003c\/p\u003e \u003cp\u003e1.2.2.5 Simplifying Trigonometric and Exponential Functions 21\u003c\/p\u003e \u003cp\u003e1.2.3 Basic Calculus 22\u003c\/p\u003e \u003cp\u003e1.2.3.1 Limits 22\u003c\/p\u003e \u003cp\u003e1.2.3.2 Differentiation 23\u003c\/p\u003e \u003cp\u003e1.2.3.3 Series 24\u003c\/p\u003e \u003cp\u003e1.2.3.4 Integration 25\u003c\/p\u003e \u003cp\u003e1.2.4 Differential Equations 28\u003c\/p\u003e \u003cp\u003e1.3 Controlling Execution 28\u003c\/p\u003e \u003cp\u003e1.4 Using Packages 30\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Storing and Transforming Data \u003c\/b\u003e\u003cb\u003e33\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Numbers 33\u003c\/p\u003e \u003cp\u003e2.1.1 Floating Point Numbers 33\u003c\/p\u003e \u003cp\u003e2.1.2 Integers and Rational Numbers 37\u003c\/p\u003e \u003cp\u003e2.1.3 Complex Numbers 38\u003c\/p\u003e \u003cp\u003e2.1.4 Constants 42\u003c\/p\u003e \u003cp\u003e2.1.5 Units and Physical Constants 43\u003c\/p\u003e \u003cp\u003e2.2 Boolean Expressions and Predicates 47\u003c\/p\u003e \u003cp\u003e2.2.1 Relational Operators 47\u003c\/p\u003e \u003cp\u003e2.2.2 Logical Operators 48\u003c\/p\u003e \u003cp\u003e2.2.3 Predicates 49\u003c\/p\u003e \u003cp\u003e2.3 Lists 51\u003c\/p\u003e \u003cp\u003e2.3.1 List Assignments 51\u003c\/p\u003e \u003cp\u003e2.3.2 Indexing List Items 52\u003c\/p\u003e \u003cp\u003e2.3.3 Arithmetic with Lists 52\u003c\/p\u003e \u003cp\u003e2.3.4 Building and Editing Lists 54\u003c\/p\u003e \u003cp\u003e2.3.4.1 Adding Items 54\u003c\/p\u003e \u003cp\u003e2.3.4.2 Deleting Items 55\u003c\/p\u003e \u003cp\u003e2.3.5 Nested Lists 55\u003c\/p\u003e \u003cp\u003e2.3.6 Sublists 56\u003c\/p\u003e \u003cp\u003e2.4 Matrices 57\u003c\/p\u003e \u003cp\u003e2.4.1 Row and Column Vectors 57\u003c\/p\u003e \u003cp\u003e2.4.2 Indexing Matrices 58\u003c\/p\u003e \u003cp\u003e2.4.3 Entering Matrices 59\u003c\/p\u003e \u003cp\u003e2.4.4 Assigning Matrices 60\u003c\/p\u003e \u003cp\u003e2.4.5 Editing Matrices 61\u003c\/p\u003e \u003cp\u003e2.4.6 Reading and Writing Matrices From Files 63\u003c\/p\u003e \u003cp\u003e2.4.7 Transforming Data in a Matrix 65\u003c\/p\u003e \u003cp\u003e2.5 Strings 66\u003c\/p\u003e \u003cp\u003e2.5.1 Using String Functions toWork with Files 67\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Plotting Data and Functions \u003c\/b\u003e\u003cb\u003e71\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Plotting in Two Dimensions 71\u003c\/p\u003e \u003cp\u003e3.1.1 Changing Plot Size and Resolution 71\u003c\/p\u003e \u003cp\u003e3.1.2 Plotting Multiple Curves 73\u003c\/p\u003e \u003cp\u003e3.1.3 Changing Axis Ranges 74\u003c\/p\u003e \u003cp\u003e3.1.4 Plotting Complex Functions 74\u003c\/p\u003e \u003cp\u003e3.1.5 Plotting Data 74\u003c\/p\u003e \u003cp\u003e3.1.5.1 Plotting Data in Separate X, Y Lists 75\u003c\/p\u003e \u003cp\u003e3.1.5.2 Plotting Data as Lists of X, Y Points 75\u003c\/p\u003e \u003cp\u003e3.1.5.3 Plotting Data in Matrices 76\u003c\/p\u003e \u003cp\u003e3.1.5.4 Plotting Data with Units 76\u003c\/p\u003e \u003cp\u003e3.1.5.5 Plotting Functions and Data Together 77\u003c\/p\u003e \u003cp\u003e3.1.6 Adding Text Labels to Graphs 77\u003c\/p\u003e \u003cp\u003e3.1.7 Plotting Rapidly Rising Functions 78\u003c\/p\u003e \u003cp\u003e3.1.7.1 Solving Axis Scaling Problems 81\u003c\/p\u003e \u003cp\u003e3.1.7.2 Positioning the Legend 83\u003c\/p\u003e \u003cp\u003e3.1.8 Parametric Plots 84\u003c\/p\u003e \u003cp\u003e3.1.9 Implicit Plots 87\u003c\/p\u003e \u003cp\u003e3.1.10 Histograms 89\u003c\/p\u003e \u003cp\u003e3.2 Plotting inThree Dimensions 91\u003c\/p\u003e \u003cp\u003e3.2.1 Plotting Functions of x, y, andz 91\u003c\/p\u003e \u003cp\u003e3.2.2 Plotting Multiple Surfaces 93\u003c\/p\u003e \u003cp\u003e3.2.3 Plotting in Spherical Coordinates 94\u003c\/p\u003e \u003cp\u003e3.2.4 Plotting in Cylindrical Coordinates 95\u003c\/p\u003e \u003cp\u003e3.2.5 Parametric Surface Plots 96\u003c\/p\u003e \u003cp\u003e3.2.6 Plotting DiscreteThree-Dimensional Data 98\u003c\/p\u003e \u003cp\u003e3.2.7 Contour Plotting 99\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Programming Maxima \u003c\/b\u003e\u003cb\u003e103\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Nouns and Verbs 103\u003c\/p\u003e \u003cp\u003e4.2 Writing Multiline Functions 106\u003c\/p\u003e \u003cp\u003e4.3 Decision Making 108\u003c\/p\u003e \u003cp\u003e4.4 Recursive Functions 109\u003c\/p\u003e \u003cp\u003e4.5 Contexts 110\u003c\/p\u003e \u003cp\u003e4.6 Iteration 114\u003c\/p\u003e \u003cp\u003e4.6.1 Indexed Loops 114\u003c\/p\u003e \u003cp\u003e4.6.2 Conditional Loops 116\u003c\/p\u003e \u003cp\u003e4.6.3 Looping Over Lists 117\u003c\/p\u003e \u003cp\u003e4.6.4 Nested Loops 118\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Algebra \u003c\/b\u003e\u003cb\u003e119\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Series 119\u003c\/p\u003e \u003cp\u003e5.1.1 Simplifying Sums 120\u003c\/p\u003e \u003cp\u003e5.1.2 Reindexing and Combining Sums 122\u003c\/p\u003e \u003cp\u003e5.1.3 Applying Functions to Sums and Products 123\u003c\/p\u003e \u003cp\u003e5.2 Products 124\u003c\/p\u003e \u003cp\u003e5.3 Equations 126\u003c\/p\u003e \u003cp\u003e5.3.1 Simplifying Equations 126\u003c\/p\u003e \u003cp\u003e5.3.2 Simplifying Trigonometric and Exponential Functions 127\u003c\/p\u003e \u003cp\u003e5.3.3 Extracting Expressions From an Equation 128\u003c\/p\u003e \u003cp\u003e5.3.4 Expanding Expressions 131\u003c\/p\u003e \u003cp\u003e5.3.5 Factoring Expressions 134\u003c\/p\u003e \u003cp\u003e5.3.6 Substitution 135\u003c\/p\u003e \u003cp\u003e5.3.7 Solving an Equation Symbolically 138\u003c\/p\u003e \u003cp\u003e5.3.7.1 Handling Multiple Solutions 139\u003c\/p\u003e \u003cp\u003e5.3.8 Solving an Equation Numerically 140\u003c\/p\u003e \u003cp\u003e5.4 Systems of Equations 141\u003c\/p\u003e \u003cp\u003e5.4.1 Eliminating Variables 141\u003c\/p\u003e \u003cp\u003e5.4.2 Solving Systems of EquationsWithout Elimination 143\u003c\/p\u003e \u003cp\u003e5.5 Interpolation 144\u003c\/p\u003e \u003cp\u003e5.5.1 Piecewise Linear Interpolation 146\u003c\/p\u003e \u003cp\u003e5.5.2 Spline Interpolation 147\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Differentiation, Integration, and Minimization \u003c\/b\u003e\u003cb\u003e149\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1.1 Limits for Discontinuous Functions 151\u003c\/p\u003e \u003cp\u003e6.1.2 Limits for Indefinite Functions 152\u003c\/p\u003e \u003cp\u003e6.2 Differentials 153\u003c\/p\u003e \u003cp\u003e6.3 Derivatives 154\u003c\/p\u003e \u003cp\u003e6.3.1 Explicit Partial and Total Derivatives 156\u003c\/p\u003e \u003cp\u003e6.3.2 Derivatives Evaluated at a Specific Point 157\u003c\/p\u003e \u003cp\u003e6.3.3 Higher-Order Derivatives 158\u003c\/p\u003e \u003cp\u003e6.3.4 Mixed Derivatives 159\u003c\/p\u003e \u003cp\u003e6.3.5 Assigning Partial Derivatives 160\u003c\/p\u003e \u003cp\u003e6.3.5.1 Partial Derivatives from Total Differential Expansions 161\u003c\/p\u003e \u003cp\u003e6.3.5.2 Writing Total Differential Expansions in Terms of New Variables 161\u003c\/p\u003e \u003cp\u003e6.3.6 Implicit Differentiation 162\u003c\/p\u003e \u003cp\u003e6.4 Maxima, Minima, and Inflection Points 164\u003c\/p\u003e \u003cp\u003e6.4.1 Critical Points of Surfaces 167\u003c\/p\u003e \u003cp\u003e6.4.2 Numerical Minimization 169\u003c\/p\u003e \u003cp\u003e6.5 Integration 173\u003c\/p\u003e \u003cp\u003e6.5.1 Integration Constants 174\u003c\/p\u003e \u003cp\u003e6.5.2 Definite Integration 174\u003c\/p\u003e \u003cp\u003e6.5.3 When Symbolic Integration Fails 175\u003c\/p\u003e \u003cp\u003e6.5.4 Numerical Integration 178\u003c\/p\u003e \u003cp\u003e6.5.4.1 Numerical Integration over Infinite Intervals 179\u003c\/p\u003e \u003cp\u003e6.5.4.2 Numerical Integration with Strongly Oscillating Integrands 180\u003c\/p\u003e \u003cp\u003e6.5.4.3 Numerical Integration with Discontinuous Integrands 181\u003c\/p\u003e \u003cp\u003e6.5.5 Multiple Integration 182\u003c\/p\u003e \u003cp\u003e6.5.6 Discrete Integration 183\u003c\/p\u003e \u003cp\u003e6.6 Power Series 186\u003c\/p\u003e \u003cp\u003e6.6.1 Testing Power Series for Convergence 186\u003c\/p\u003e \u003cp\u003e6.7 Taylor Series 187\u003c\/p\u003e \u003cp\u003e6.7.1 Exploring Function Properties with Taylor Series 188\u003c\/p\u003e \u003cp\u003e6.7.2 The Remainder Term 190\u003c\/p\u003e \u003cp\u003e6.7.3 Taylor Series for Multivariate Functions 191\u003c\/p\u003e \u003cp\u003e6.7.4 Approximating Taylor Series 191\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Matrices and Vectors \u003c\/b\u003e\u003cb\u003e193\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Vectors 193\u003c\/p\u003e \u003cp\u003e7.1.1 Vector Arithmetic 194\u003c\/p\u003e \u003cp\u003e7.1.2 The Dot Product 195\u003c\/p\u003e \u003cp\u003e7.1.3 Vector Lengths and Angles 196\u003c\/p\u003e \u003cp\u003e7.1.4 The Cross Product 197\u003c\/p\u003e \u003cp\u003e7.1.5 Angular Momentum 198\u003c\/p\u003e \u003cp\u003e7.1.6 Vector Algebra 199\u003c\/p\u003e \u003cp\u003e7.2 Matrices 200\u003c\/p\u003e \u003cp\u003e7.2.1 Matrix Arithmetic 201\u003c\/p\u003e \u003cp\u003e7.2.2 The Transpose 201\u003c\/p\u003e \u003cp\u003e7.2.3 The Matrix Product 202\u003c\/p\u003e \u003cp\u003e7.2.4 Determinants 203\u003c\/p\u003e \u003cp\u003e7.2.5 The Inverse of a Matrix 206\u003c\/p\u003e \u003cp\u003e7.2.6 Matrix Algebra 207\u003c\/p\u003e \u003cp\u003e7.2.7 Eigenvalues and Eigenvectors 211\u003c\/p\u003e \u003cp\u003e7.2.7.1 Application: Energies and Molecular Orbitals of Ethylene 212\u003c\/p\u003e \u003cp\u003e7.2.7.2 Eigenvalues and Eigenvectors for Symmetric Matrices 214\u003c\/p\u003e \u003cp\u003e7.2.7.3 Matrix Diagonalization 216\u003c\/p\u003e \u003cp\u003e7.3 Vector Calculus 217\u003c\/p\u003e \u003cp\u003e7.3.1 Derivative of a Vector with Respect to a Scalar 217\u003c\/p\u003e \u003cp\u003e7.3.2 The Jacobian 218\u003c\/p\u003e \u003cp\u003e7.3.3 The Gradient 220\u003c\/p\u003e \u003cp\u003e7.3.4 The Laplacian 222\u003c\/p\u003e \u003cp\u003e7.3.5 The Divergence 224\u003c\/p\u003e \u003cp\u003e7.3.6 The Curl 225\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Error Analysis \u003c\/b\u003e\u003cb\u003e227\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Classifying Experimental Errors 227\u003c\/p\u003e \u003cp\u003e8.1.1 Systematic Error 229\u003c\/p\u003e \u003cp\u003e8.1.2 Random Error 230\u003c\/p\u003e \u003cp\u003e8.2 Probability Density 230\u003c\/p\u003e \u003cp\u003e8.2.1 Discrete Probability Distributions 230\u003c\/p\u003e \u003cp\u003e8.2.2 The Poisson Distribution 232\u003c\/p\u003e \u003cp\u003e8.2.3 Continuous Probability Distributions 235\u003c\/p\u003e \u003cp\u003e8.2.4 The Normal Distribution 236\u003c\/p\u003e \u003cp\u003e8.3 Estimating Precision 238\u003c\/p\u003e \u003cp\u003e8.3.1 Standard Error of the Mean 240\u003c\/p\u003e \u003cp\u003e8.3.2 Confidence Interval of the Mean 240\u003c\/p\u003e \u003cp\u003e8.4 Hypothesis Testing 241\u003c\/p\u003e \u003cp\u003e8.4.1 Comparing a Mean with a True Value 243\u003c\/p\u003e \u003cp\u003e8.4.2 Comparing Variances 244\u003c\/p\u003e \u003cp\u003e8.4.3 Comparing Two Sample Means 246\u003c\/p\u003e \u003cp\u003e8.5 Propagation of Error 249\u003c\/p\u003e \u003cp\u003e8.5.1 Propagation of Independent Systematic Errors 249\u003c\/p\u003e \u003cp\u003e8.5.2 Propagation of Independent Random Errors 251\u003c\/p\u003e \u003cp\u003e8.5.3 Covariance and Correlation 253\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Fitting Data to a Straight Line \u003c\/b\u003e\u003cb\u003e257\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 The Ordinary Least-Squares Method 259\u003c\/p\u003e \u003cp\u003e9.1.1 Using Built-In Functions 260\u003c\/p\u003e \u003cp\u003e9.1.2 Error Estimates for the Slope and the Intercept 263\u003c\/p\u003e \u003cp\u003e9.1.3 The Determination Coefficient 266\u003c\/p\u003e \u003cp\u003e9.1.4 Residual Analysis 268\u003c\/p\u003e \u003cp\u003e9.1.5 Testing the Fit Parameters 271\u003c\/p\u003e \u003cp\u003e9.1.6 Testing for Lack-of-Fit 272\u003c\/p\u003e \u003cp\u003e9.2 Multiple Linear Regression 274\u003c\/p\u003e \u003cp\u003e9.2.1 Matrix Form of Multiple Linear Regression 275\u003c\/p\u003e \u003cp\u003e9.2.2 Estimating the Errors in the Fit Parameters in MLR 277\u003c\/p\u003e \u003cp\u003e9.2.3 Example: Microwave Rotational Spectrum of HCl 278\u003c\/p\u003e \u003cp\u003e9.2.4 Detecting and Dealing with Outliers 281\u003c\/p\u003e \u003cp\u003e9.3 WLS 285\u003c\/p\u003e \u003cp\u003e9.3.1 The Fit Parameters inWLS 286\u003c\/p\u003e \u003cp\u003e9.3.2 Error Estimates for theWLS Fit Parameters 286\u003c\/p\u003e \u003cp\u003e9.3.3 Finding theWeights 287\u003c\/p\u003e \u003cp\u003e9.3.4 Residual Analysis inWLS 288\u003c\/p\u003e \u003cp\u003e9.3.5 Evaluating Goodness-of-Fit 288\u003c\/p\u003e \u003cp\u003e9.4 Fitting Data to a Line with Errors in Both X and Y 289\u003c\/p\u003e \u003cp\u003e9.4.1 Finding Fit Parameters in TLS 290\u003c\/p\u003e \u003cp\u003e9.4.2 Error Estimates for the TLS Fit Parameters 292\u003c\/p\u003e \u003cp\u003e9.4.3 Assessing Goodness-of-Fit in TLS 293\u003c\/p\u003e \u003cp\u003e9.4.4 Multiple Linear Regression with TLS 293\u003c\/p\u003e \u003cp\u003e9.5 Calibration and Standard Additions 294\u003c\/p\u003e \u003cp\u003e9.5.1 Error Estimates for Calibrated Values 294\u003c\/p\u003e \u003cp\u003e9.5.2 Standard Additions 295\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Fitting Data to a Curve \u003c\/b\u003e\u003cb\u003e299\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Transforming Data to a Linear Form 299\u003c\/p\u003e \u003cp\u003e10.2 Polynomial Least-Squares Fitting 302\u003c\/p\u003e \u003cp\u003e10.2.1 How Many Fit Parameters Are Needed? 304\u003c\/p\u003e \u003cp\u003e10.3 Nonlinear Least-Squares Models 306\u003c\/p\u003e \u003cp\u003e10.4 Estimating Error in Nonlinear Fit Parameters 310\u003c\/p\u003e \u003cp\u003e10.4.1 Estimating Parameter Errors with the Jackknife Method 311\u003c\/p\u003e \u003cp\u003e10.4.2 Estimating Parameter Errors with the Bootstrap Method 313\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Differential Equations \u003c\/b\u003e\u003cb\u003e317\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Symbolic Solutions of ODEs 318\u003c\/p\u003e \u003cp\u003e11.1.1 Initial Value Problems 320\u003c\/p\u003e \u003cp\u003e11.1.2 Boundary Value Problems 322\u003c\/p\u003e \u003cp\u003e11.2 Power Series Solution of ODEs 325\u003c\/p\u003e \u003cp\u003e11.3 Direction Fields 329\u003c\/p\u003e \u003cp\u003e11.3.1 Direction Fields with Adjustable Parameters 331\u003c\/p\u003e \u003cp\u003e11.3.2 Direction Fields and Autonomous Equations 332\u003c\/p\u003e \u003cp\u003e11.4 Solving Systems of Linear Differential Equations 335\u003c\/p\u003e \u003cp\u003e11.5 Numerical Solution of ODEs 338\u003c\/p\u003e \u003cp\u003e11.6 Solving Partial Differential Equations 340\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Operators and Integral Transforms \u003c\/b\u003e\u003cb\u003e343\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Defining Operators 344\u003c\/p\u003e \u003cp\u003e12.2 Fourier Series 347\u003c\/p\u003e \u003cp\u003e12.3 Fourier Transforms 351\u003c\/p\u003e \u003cp\u003e12.3.1 The Fast Fourier Transform 355\u003c\/p\u003e \u003cp\u003e12.4 The Laplace Transform 357\u003c\/p\u003e \u003cp\u003eGlossary 359\u003c\/p\u003e \u003cp\u003eReferences 367\u003c\/p\u003e \u003cp\u003eIndex 371\u003c\/p\u003e \u003cp\u003e\t\t \u003c\/p\u003e\u003cp\u003e\u003cb\u003eProfessor Fred Senese\u003c\/b\u003e is a computational chemist at Frostburg State University with a particular focus on chemical education. His research interests include applications of artificial intelligence in chemical education, development of web-based narratives and construction kits for chemical education, remote control and access of instrumentation, and environmental chemical analysis applied to problems in ethnobotany.   \u003c\/p\u003e\u003cp\u003e\u003cb\u003eAn essential guide to using Maxima, a popular open source symbolic mathematics engine to solve problems, build models, analyze data and explore fundamental concepts\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003ci\u003eSymbolic Mathematics for Chemists\u003c\/i\u003e offers students of chemistry a guide to Maxima, a popular open source symbolic mathematics engine that can be used to solve problems, build models, analyze data, and explore fundamental chemistry concepts. The author — a noted expert in the field — focuses on the analysis of experimental data obtained in a laboratory setting and the fitting of data and modeling experiments. The text contains a wide variety of illustrative examples and applications in physical chemistry, quantitative analysis and instrumental techniques. \u003c\/p\u003e\u003cp\u003eDesigned as a practical resource, the book is organized around a series of worksheets that are provided in a companion website. Each worksheet has clearly defined goals and learning objectives and a detailed abstract that provides motivation and context for the material. This important resource: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eOffers an text that shows how to use popular symbolic mathematics engines to solve problems\u003c\/li\u003e \u003cli\u003eIncludes a series of worksheet that are prepared in Maxima\u003c\/li\u003e \u003cli\u003eContains step-by-step instructions written in clear terms and includes illustrative examples to enhance critical thinking, creative problem solving and the ability to connect concepts in chemistry\u003c\/li\u003e \u003cli\u003eOffers hints and case studies that help to master the basics while proficient users are offered more advanced avenues for exploration\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eWritten for advanced undergraduate and graduate students in chemistry and instructors looking to enhance their lecture or lab course with symbolic mathematics materials,\u003ci\u003eSymbolic Mathematics for Chemists: A Guide for Maxima Users\u003c\/i\u003e is an essential resource for solving and exploring quantitative problems in chemistry.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47990121660645,"sku":"NP9781118798690","price":85.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781118798690.jpg?v=1761786596","url":"https:\/\/k12savings.com\/es\/products\/symbolic-mathematics-for-chemists-isbn-9781118798690","provider":"K12savings","version":"1.0","type":"link"}