Leveled Texts: Probability of Events


Book Description

All students can learn about probability through text written at four different reading levels. Symbols on the pages represent reading-level ranges to help differentiate instruction. Provided comprehension questions complement the text.




Leveled Texts: Probability Experiments


Book Description

All students can learn about probability through text written at four different reading levels. Symbols on the pages represent reading-level ranges to help differentiate instruction. Provided comprehension questions complement the text.




Leveled Texts for Mathematics: Data Analysis and Probability


Book Description

With a focus on data analysis and probability, a guide to using leveled texts to differentiate instruction in mathematics offers fifteen different topics with high-interest text written at four different reading levels, accompanied by matching visuals and practice problems.




Leveled Texts: Collecting Data


Book Description

All students can learn about collecting data through text written at four different reading levels. Symbols on the pages represent reading-level ranges to help differentiate instruction. Provided comprehension questions complement the text.




Leveled Texts: Analyzing Bar Graphs


Book Description

All students can learn about analyzing bar graphs through text written at four different reading levels. Symbols on the pages represent reading-level ranges to help differentiate instruction. Provided comprehension questions complement the text.




Leveled Texts: Analyzing Circle Graphs


Book Description

All students can learn about analyzing circle graphs through text written at four different reading levels. Symbols on the pages represent reading-level ranges to help differentiate instruction. Provided comprehension questions complement the text.




Leveled Texts: Comparing Graphs


Book Description

All students can learn about comparing graphs through text written at four different reading levels. Symbols on the pages represent reading-level ranges to help differentiate instruction. Provided comprehension questions complement the text.




Introduction to Probability


Book Description

This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.




Leveled Texts: Mode and Range


Book Description

All students can learn about mode and range through text written at four different reading levels. Symbols on the pages represent reading-level ranges to help differentiate instruction. Provided comprehension questions complement the text.




Probability and Statistics


Book Description

Unlike traditional introductory math/stat textbooks, Probability and Statistics: The Science of Uncertainty brings a modern flavor based on incorporating the computer to the course and an integrated approach to inference. From the start the book integrates simulations into its theoretical coverage, and emphasizes the use of computer-powered computation throughout.* Math and science majors with just one year of calculus can use this text and experience a refreshing blend of applications and theory that goes beyond merely mastering the technicalities. They'll get a thorough grounding in probability theory, and go beyond that to the theory of statistical inference and its applications. An integrated approach to inference is presented that includes the frequency approach as well as Bayesian methodology. Bayesian inference is developed as a logical extension of likelihood methods. A separate chapter is devoted to the important topic of model checking and this is applied in the context of the standard applied statistical techniques. Examples of data analyses using real-world data are presented throughout the text. A final chapter introduces a number of the most important stochastic process models using elementary methods. *Note: An appendix in the book contains Minitab code for more involved computations. The code can be used by students as templates for their own calculations. If a software package like Minitab is used with the course then no programming is required by the students.