Search Constraints
Number of results to display per page
Results for:
statistics
Remove constraint statistics
Search Results
-
e-book
Process controls is a mixture between the statistics and engineering discipline that deals with the mechanism, architectures, and algorithms for controlling a process. Some examples of controlled processes are: •Controlling the temperature of a water stream by controlling the amount of steam added to the shell of a heat exchanger. •Operating a jacketed reactor isothermally by controlling the mixture of cold water and steam that flows through the jacket of a jacketed reactor. •Maintaining a set ratio of reactants to be added to a reactor by controlling their flow rates. •Controlling the height of fluid in a tank to ensure that it does not overflow.
- Subjects:
- Chemistry
- Keywords:
- Chemical process control Chemical processes Textbooks
- Resource Type:
- e-book
-
e-book
The focus of this book is on using quantitative research methods to test hypotheses and build theory in political science, public policy and public administration. It is designed for advanced undergraduate courses, or introductory and intermediate graduate-level courses. The first part of the book introduces the scientific method, then covers research design, measurement, descriptive statistics, probability, inference, and basic measures of association. The second part of the book covers bivariate and multiple linear regression using the ordinary least squares, the calculus and matrix algebra that are necessary for understanding bivariate and multiple linear regression, the assumptions that underlie these methods, and then provides a short introduction to generalized linear models.The book fully embraces the open access and open source philosophies. The book is freely available in the SHAREOK repository; it is written in R Markdown files that are available in a public GitHub repository; it uses and teaches R and RStudio for data analysis, visualization and data management; and it uses publically available survey data (from the Meso-Scale Integrated Socio-geographic Network) to illustrate important concepts and methods. We encourage students to download the data, replicate the examples, and explore further! We also encourage instructors to download the R Markdown files and modify the text for use in different courses.
-
e-book
When you teach Introduction to Psychology, do you find it difficult — much harder than teaching classes in statistics or research methods? Do you easily give a lecture on the sympathetic nervous system, a lecture on Piaget, and a lecture on social cognition, but struggle with linking these topics together for the student? Do you feel like you are presenting a laundry list of research findings rather than an integrated set of principles and knowledge? Have you wondered how to ensure your course is relevant to your students? Introduction to Psychology utilizes the dual theme of behavior and empiricism to make psychology relevant to intro students. The author wrote this book to help students organize their thinking about psychology at a conceptual level. Five or ten years from now, he does not expect his students to remember the details of most of what he teaches them. However, he does hope that they will remember that psychology matters because it helps us understand behavior and that our knowledge of psychology is based on empirical study. This book is designed to facilitate these learning outcomes, and he has used three techniques to help focus students on behavior: Chapter Openers: Each chapter opens showcasing an interesting real world example of people who dealing with behavioral questions and who can use psychology to help them answer them. The opener is designed to draw the student into the chapter and create an interesting in learning about the topic. Psychology in Everyday Life: Each chapter contains one or two features designed to link the principles from the chapter to real-world applications in business, environment, health, law, learning, and other relevant domains. For instance, the application in Chapter 7 on Development, ”What makes good parents“ applies the concepts of parenting styles in a mini-handbook about parenting, and the application in Chapter 3 is about the difficulties that left-handed people face performing everyday tasks in a right-handed world. Research Foci: Introduction to Psychology emphasizes empiricism throughout, but without making it a distraction from the main story line. Each chapter presents two close-ups on research — well articulated and specific examples of research within the content area, each including a summary of the hypotheses, methods, results, and interpretations. This feature provides a continuous thread that reminds students of the importance of empirical research. The research foci also emphasize the fact that findings are not always predictable ahead of time (dispelling the myth of hindsight bias), and also help students understand how research really works. The author's focus on behavior and empiricism has produced, Introduction to Psychology, a text that is better organized, has fewer chapters, and is somewhat shorter than many of the leading books. Now, you don't have to believe us. Check the book out online or order your desk copy today.
- Subjects:
- Psychology
- Keywords:
- Psychology Textbooks
- Resource Type:
- e-book
-
e-book
This is a free textbook teaching introductory statistics for undergraduates in Psychology. This textbook is part of a larger OER course package for teaching undergraduate statistics in Psychology, including this textbook, a lab manual, and a course website. All of the materials are free and copiable, with source code maintained in Github repositories.
- Subjects:
- Psychology and Mathematics and Statistics
- Keywords:
- Textbooks Psychology Statistics Social sciences -- Statistical methods
- Resource Type:
- e-book
-
e-book
This is a first draft of a free (as in speech, not as in beer, [Sta02]) (although it is free as in beer as well) textbook for a one-semester, undergraduate statistics course. It was used for Math 156 at Colorado State University–Pueblo in the spring semester of 2017.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Textbooks Statistics
- Resource Type:
- e-book
-
e-book
Learning Statistics with R covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software. The book discusses how to get started in R as well as giving an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book.
- Subjects:
- Psychology and Mathematics and Statistics
- Keywords:
- Statistics -- Computer programs R (Computer program language) Textbooks Statistics Social sciences -- Statistical methods
- Resource Type:
- e-book
-
e-book
We hope readers will take away three ideas from this book in addition to forming a foundationof statistical thinking and methods. (1) Statistics is an applied field with a wide range of practical applications. (2) You don't have to be a math guru to learn from real, interesting data. (3) Data are messy, and statistical tools are imperfect. But, when you understand the strengths and weaknesses of these tools, you can use them to learn about the real world. Textbook overviewThe chapters of this book are as follows: 1. Data collection. Data structures, variables, and basic data collection techniques. 2. Summarizing data. Data summaries and graphics. 3. Probability. The basic principles of probability. 4. Distributions of random variables. Introduction to key distributions, and how the normal model applies to the sample mean and sample proportion. 5. Foundation for inference. General ideas for statistical inference in the context of estimating the population proportion. 6. Inference for categorical data. Inference for proportions using the normal and chisquare distributions. 7. Inference for numerical data. Inference for one or two sample means using the t distribution, and comparisons of many means using ANOVA. 8. Introduction to linear regression. An introduction to regression with two variables. Instructions are also provided in several sections for using Casio and TI calculators.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Textbooks Statistics
- Resource Type:
- e-book
-
e-book
We hope readers will take away three ideas from this book in addition to forming a foundation of statistical thinking and methods. (1) Statistics is an applied field with a wide range of practical applications. (2) You don't have to be a math guru to learn from interesting, real data. (3) Data are messy, and statistical tools are imperfect. However, when you understand the strengths and weaknesses of these tools, you can use them to learn interesting things about the world. Textbook overview The chapters of this book are as follows: 1. Introduction to data. Data structures, variables, summaries, graphics, and basic data collection techniques. 2. Foundations for inference. Case studies are used to introduce the ideas of statistical inference with randomization and simulations. The content leads into the standard parametric framework, with techniques reinforced in the subsequent chapters.1 It is also possible to begin with this chapter and introduce tools from Chapter 1 as they are needed. 3. Inference for categorical data. Inference for proportions using the normal and chi-square distributions, as well as simulation and randomization techniques. 4. Inference for numerical data. Inference for one or two sample means using the t distribution, and also comparisons of many means using ANOVA. A special section for bootstrapping is provided at the end of the chapter. 5. Introduction to linear regression. An introduction to regression with two variables. Most of this chapter could be covered immediately after Chapter 1. 6. Multiple and logistic regression. An introduction to multiple regression and logistic regression for an accelerated course. Appendix A. Probability. An introduction to probability is provided as an optional reference. Exercises and additional probability content may be found in Chapter 2 of OpenIntro Statistics at openintro.org. Instructor feedback suggests that probability, if discussed, is best introduced at the very start or very end of the course.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Textbooks Statistics
- Resource Type:
- e-book
-
e-book
Introductory Business Statistics is designed to meet the scope and sequence requirements of the one-semester statistics course for business, economics, and related majors. Core statistical concepts and skills have been augmented with practical business examples, scenarios, and exercises. The result is a meaningful understanding of the discipline, which will serve students in their business careers and real-world experiences.
- Subjects:
- Management and Statistics and Research Methods
- Keywords:
- Statistics Textbooks Commercial statistics
- Resource Type:
- e-book
-
e-book
As currently taught in the United States, introductory courses in analytical chemistry emphasize quantitative (and sometimes qualitative) methods of analysis along with a heavy dose of equilibrium chemistry. Analytical chemistry, however, is much more than a collection of analytical methods and an understanding of equilibrium chemistry; it is an approach to solving chemical problems. Although equilibrium chemistry and analytical methods are important, their coverage should not come at the expense of other equally important topics. The introductory course in analytical chemistry is the ideal place in the undergraduate chemistry curriculum for exploring topics such as experimental design, sampling, calibration strategies, standardization, optimization, statistics, and the validation of experimental results. Analytical methods come and go, but best practices for designing and validating analytical methods are universal. Because chemistry is an experimental science it is essential that all chemistry students understand the importance of making good measurements. My goal in preparing this textbook is to find a more appropriate balance between theory and practice, between “classical” and “modern” analytical methods, between analyzing samples and collecting samples and preparing them for analysis, and between analytical methods and data analysis. There is more material here than anyone can cover in one semester; it is my hope that the diversity of topics will meet the needs of different instructors, while, perhaps, suggesting some new topics to cover.
- Subjects:
- Chemistry
- Keywords:
- Chemistry Analytic -- Quantitative Textbooks
- Resource Type:
- e-book