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ISBN 10: 0321853083
ISBN 13: 9780321853080
Author: Michael Akritas
The author and publisher of this book have used their best efforts in preparing this book. These efforts include the development, research, and testing of the theories and programs to determine their effectiveness. The author and publisher make no warranty of any kind, expressed or implied, with regard to these programs or the documentation contained in this book. The author and publisher shall not be liable in any event for incidental or consequential damages in connection with, or arising out of, the furnishing, performance, or use of these programs. Reproduced by Pearson from electronic files supplied by the author. Copyright © 2016 Pearson Education, Inc. Publishing as Pearson, 501 Boylston Street, Boston, MA 02116. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America.
1. Basic Statistical Concepts
1.1 Introduction
1.2 Populations and Samples
1.3 Some Sampling Concepts
1.4 Random Variables and Statistical Populations
1.5 Basic Graphics for Data Visualization
1.6 Proportions, Averages, and Variances
1.7 Medians, Percentiles, and Boxplots
1.8 Comparative Studies
2. Introduction to Probability
2.1 Introduction
2.2 Sample Spaces, Events, and Set Operations
2.3 Experiments with Equally Likely Outcomes
2.4 Axioms and Properties of Probabilities
2.5 Conditional Probability
2.6 Independent Events
3. Random Variables and Their Distributions
3.1 Introduction
3.2 Describing a Probability Distribution
3.3 Parameters of Probability Distributions
3.4 Models for Discrete Random Variables
3.5 Models for Continuous Random Variables
4. Jointly Distributed Random Variables
4.1 Introduction
4.2 Describing Joint Probability Distributions
4.3 Conditional Distributions
4.4 Mean Value of Functions of Random Variables
4.5 Quantifying Dependence
4.6 Models for Joint Distributions
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Tags: Michael Akritas, Probability, Statistics
