Regression
Solutions Manual to accompany Quantitative Methods
An Introduction for Business Management Provisional version of May 23, 2011
Paolo Brandimarte
A Wiley-Interscience Publication
JOHN WILEY & SONS, INC.
New York / Chichester / Weinheim / Brisbane / Singapore / Toronto
Contents
Preface 1 Quantitative Methods: Should We Bother? 1.1 Solutions 1.2 Computational supplements 1.2.1 Optimal mix problem Calculus 2.1 Solutions Linear Algebra 3.1 Solutions Descriptive Statistics: On the Way to Elementary Probability 4.1 Solutions Probability Theories 5.1 Solutions 5.2 Additional problems 5.3 Solutions of additional problems Discrete Random Variables 6.1 Solutions
vii 1 1 3 3 7 7 15 15 25 25 29 29 30 31 33 33 v 2
3
4
5
6
vi
CONTENTS
7
Continuous Random Variables 7.1 Solutions Dependence, Correlation, and Conditional Expectation 8.1 Solutions
37 37 43 43 47 49 49 57 58 60 62 65 66 67 69
8
Appendix A R – A software tool for statistics Appendix B Introduction to MATLAB B.1 Working with vectors and matrices in the MATLAB environment B.2 MATLAB graphics B.3 Solving equations and computing integrals B.4 Statistics in MATLAB B.5 Using MATLAB to solve linear and quadratic programming problems Appendix C Introduction to AMPL C.1 Running optimization models in AMPL C.2 Mean-variance efficient portfolios in AMPL C.3 The knapsack model in AMPL
Preface
This solutions manual contains • worked-out solutions to end-of-chapter problems in the book • additional problems (solved) • computational supplements illustrating the application of the following tools: – Microsoft Excel – R – MATLAB – AMPL Some software tools are introduced in the appendices, where I am giving you a few hints and clues about how they can be used to apply the methods described in the book. Some of these tools are free, some have free student demos, some can be obtained at a reduced price. Anyway, they are all widely available and I encourage you to try them.
An Introduction for Business Management Provisional version of May 23, 2011
Paolo Brandimarte
A Wiley-Interscience Publication
JOHN WILEY & SONS, INC.
New York / Chichester / Weinheim / Brisbane / Singapore / Toronto
Contents
Preface 1 Quantitative Methods: Should We Bother? 1.1 Solutions 1.2 Computational supplements 1.2.1 Optimal mix problem Calculus 2.1 Solutions Linear Algebra 3.1 Solutions Descriptive Statistics: On the Way to Elementary Probability 4.1 Solutions Probability Theories 5.1 Solutions 5.2 Additional problems 5.3 Solutions of additional problems Discrete Random Variables 6.1 Solutions
vii 1 1 3 3 7 7 15 15 25 25 29 29 30 31 33 33 v 2
3
4
5
6
vi
CONTENTS
7
Continuous Random Variables 7.1 Solutions Dependence, Correlation, and Conditional Expectation 8.1 Solutions
37 37 43 43 47 49 49 57 58 60 62 65 66 67 69
8
Appendix A R – A software tool for statistics Appendix B Introduction to MATLAB B.1 Working with vectors and matrices in the MATLAB environment B.2 MATLAB graphics B.3 Solving equations and computing integrals B.4 Statistics in MATLAB B.5 Using MATLAB to solve linear and quadratic programming problems Appendix C Introduction to AMPL C.1 Running optimization models in AMPL C.2 Mean-variance efficient portfolios in AMPL C.3 The knapsack model in AMPL
Preface
This solutions manual contains • worked-out solutions to end-of-chapter problems in the book • additional problems (solved) • computational supplements illustrating the application of the following tools: – Microsoft Excel – R – MATLAB – AMPL Some software tools are introduced in the appendices, where I am giving you a few hints and clues about how they can be used to apply the methods described in the book. Some of these tools are free, some have free student demos, some can be obtained at a reduced price. Anyway, they are all widely available and I encourage you to try them.